Seasonal Abundance and Diversity of Birds of Prey and Owls in Al Wathba Wetland Reserve in Abu Dhabi, UAE

Inland wetlands in Abu Dhabi Emirate are wintering and stopover sites for migratory birds of prey. We conducted long-term regular monitoring surveys in Al Wathba Wetland Reserve (AWWR) from January 1995 to December 2022. Both diurnal and occasionally nocturnal surveys were undertaken to record the migratory raptors and owls in the Wetland Reserve. During the study, a total of 1282 regular monitoring visits were undertaken and 27 species of diurnal raptors and owls representing five families and three orders were detected. These represent 57% of the total species of birds of prey recorded in the UAE. Overall, 63% of all the species that we observed were Accipitriformes followed by 26% Falconiformes and 11% Strigiformes. We found that changes in mean daily temperature have a positive effect on raptor species diversity and abundance in the Wetland Reserve. The species encounter rate was higher in low temperature as compared to high temperature and overall regression equation was statistically significant F (4, 1126) = 8.49), p = 0.00). However, the numbers of raptors did not vary significantly across the years (p = 0.51). Western Marsh-harrier (Circus aeruginosus) and Greater Spotted Eagle (Clanga clanga) were recorded to be the most abundant species in the wetland reserve followed by Common Kestrel (Falco tinnunculus). However, the encounter rate of globally threatened Greater Spotted Eagle was detected to have significantly decreased since 2016. Moreover, 63% of the species detected were uncommon and rarely recorded such as 1) Saker Falcon 2) Lanner Falcon 3) Long-eared Owl & Merlin, which were the rare records from the wetland reserve. Furthermore, 27 years of regular monitoring in the wetland have yielded diverse diurnal raptors and owl fauna (H) = 0.83, (E) = 1.43 (Shannon Diversity Index). The results demonstrate that long-term monitoring surveys in arid environments are essential to determine the trends in the raptor populations and to document rare and globally important species.

Probing the Efficiency of PPMG-Based Composite Electrolytes for Applications of Proton Exchange Membrane Fuel Cell

PPMG-based composite electrolytes were fabricated via the solution method using the polyvinyl alcohol and polyvinylpyrrolidone blend reinforced with various contents of sulfonated inorganic filler.Sulfuric acid was employed as the sulfonating agent to functionalize the external surface of the inorganic filler,i.e.,graphene oxide.The proton conductivities of the newly prepared proton exchange membranes(PEMs)were increased by increasing the temperature and content of sulfonated graphene oxide(SGO),i.e.,ranging from 0.025 S/cm to 0.060 S/cm.The induction of the optimum level of SGO is determined to be an excellent route to enhance ionic conductivity.The single-cell performance test was conducted by sandwiching the newly prepared PEMs between an anode(0.2 mg/cm^(2) Pt/Ru)and a cathode(0.2 mg/cm^(2) Pt)to prepare membrane electrode assemblies,followed by hot pressing under a pressure of approximately 100 kg/cm^(2) at 60℃for 5–10 min.The highest power densities achieved with PPMG PEMs were 14.9 and 35.60 mW/cm^(2) at 25℃and 70℃,respectively,at ambient pressure with 100%relative humidity.Results showed that the newly prepared PEMs exhibit good electrochemical performance.The results indicated that the prepared composite membrane with 6 wt%filler can be used as an alternative membrane for applications of high-performance proton exchange membrane fuel cell.

Maternal Risk Factors and Short Term Outcome of Prematurity: A Descriptive Study at a Secondary Care Hospital

Background: Approximately 15 million babies are born premature (before 37 weeks of gestation) and 1 million babies die due to prematurity complications every year. Less is known about risk factors of prematurity in middle and low-income countries. The prevalence of prematurity ranges from 5% - 18%. Objective: To determine the prevalence of premature births and to assess the rate of survival, along with the morbidity, among preterm newborns. Furthermore, to document our experience with different gestational age groups of preterm births;and to analyze the association among these strata and their clinical outcomes. Study Design: A descriptive study. Place and Duration of Study: The Aga Khan Maternal and Childcare Centre Hyderabad, Pakistan, from 1st January 2017 to 31st December 2018. Methodology: All pregnant women registered at the obstetric clinic before 24 weeks of gestation having at least three subsequent visits at the same clinic were included in the study. The women who were lost to follow up before completing three visits were excluded from the study. All un-booked women were also excluded from the study. Demographic profile was recorded including maternal age, parity, no of visits at the clinic, gestational age, mode of delivery, birth weight and pregnancy outcome. Newborns were subsequently followed at nursery or well-baby till discharge. Further subgroups were made for gestational age to assess the frequency of various morbidities in each group. Results: One thousand and ninety-one (1091) women were included in the study period that fulfilled the inclusion criteria. Two pregnancies were terminated before 24 weeks due to major congenital malformations. The prevalence of prematurity was recorded as 13.4% (146/1089). Perinatal mortality rate (no of stillbirths plus the number of early neonatal death/1000 live birth) was 17 (15.6/1000 live births) out of them, 12 were still births and 5 were early neonatal death. Out of the total preterm babies born, 59.5% (87/146) were admitted to the nursery. In the study group (2%/3146) were extreme preterm, while 7.5% were severe preterm (11/146). Moderate preterm was 11.6% (17/146) and the majority were late preterm accounting for 78.7% (115/146). Though the incidence of birth asphyxia were noted more in late preterm babies i.e. 10 as the number of these babies are also high in our study but the overall percentage was low (8.7%) as compared with the babies of extreme prematurity (100%) and moderate late prematurity (23.5%) respectively. In pregnancy outcome, 12 were still births in which six (50%) were in the late preterm group. Total of 17 newborns suffered from birth asphyxia in which ten newborns (58.8%) were in late preterm group. Overall, it was noted that the decreasing gestational age was directly correlated to morbidity and mortality. Conclusion: Among the different strata, the late preterm group has been observed to be associated with greater morbidity and mortality. Prior awareness of the morbidities associated with late preterm babies is helpful for the health care providers to anticipate and manage potential complications in preterm infants.

The Psychosocial and Financial Ramifications of Thalassemia on Parents of Thalassemic Children Presented at Tertiary Care Hospitals

Thalassemia major is a disease that requires frequent admission of patients to medical facilities along with unremitting medicinal and blood transfusion aids. The families of such patients suffer in different aspects of their lives. The severity of the challenges they are subject to has been examined in this research with reference to Karachi and Hyderabad. Chief focus is rendered to the assessment of psychological, social, and economical implications. Objective: The aim of this study is to assess the social, financial and psychological impact of thalassemia on parents of children suffering from thalassemia. Study Design: Cross-sectional study. Place and Duration of Study: The study was conducted at PNS Shifa Hospital Karachi, Jinnah Post Graduate Medical Institute Karachi, and Civil Hospital Hyderabad. Methodology: A cross-sectional study which was aimed at establishing the social, financial and psychological impact of thalassemia on families of affected children was conducted at PNS Shifa Hospital, Jinnah Post Graduate Medical Institute Karachi, and Civil Hospital Hyderabad. The data was collected using a structured questionnaire as tool for data collection. The questionnaires were filled by interviewing the parents of registered thalassemia major patients by the researchers. Data was analyzed and interpreted using the SPSS 25.0 version. Results: The total number of participants which were meeting the inclusion criteria was 237. Study population with high income (above PK rupees 35,000) is demonstrated to be less severely affected than the low earning study group. 17% of the parents in the study admitted to having negative impact of their child’s illness on their relationship while 40% of study participants reveal their child is ignored/marginalized by relatives. About 80% of participants acknowledged feeling sad and depressed sometimes but only 25% of them take antidepressant medication.

Automatic License Plate Recognition System for Vehicles Using a CNN

Automatic License Plate Recognition(ALPR)systems are important in Intelligent Transportation Services(ITS)as they help ensure effective law enforcement and security.These systems play a significant role in border surveillance,ensuring safeguards,and handling vehicle-related crime.The most effective approach for implementing ALPR systems utilizes deep learning via a convolutional neural network(CNN).A CNN works on an input image by assigning significance to various features of the image and differentiating them from each other.CNNs are popular for license plate character recognition.However,little has been reported on the results of these systems with regard to unusual varieties of license plates or their success at night.We present an efficient ALPR system that uses a CNN for character recognition.A combination of pre-processing and morphological operations was applied to enhance input image quality,which aids system efficiency.The system has various features,such as the ability to recognize multi-line,skewed,and multifont license plates.It also works efficiently in night mode and can be used for different vehicle types.An overall accuracy of 98.13%was achieved using the proposed CNN technique.

Packet Optimization of Software Defined Network Using Lion Optimization

There has been an explosion of cloud services as organizations take advantage of their continuity,predictability,as well as quality of service and it raises the concern about latency,energy-efficiency,and security.This increase in demand requires new configurations of networks,products,and service operators.For this purpose,the software-defined network is an efficient technology that enables to support the future network functions along with the intelligent applications and packet optimization.This work analyzes the offline cloud scenario in which machines are efficiently deployed and scheduled for user processing requests.Performance is evaluated in terms of reducing bandwidth,task execution times and latencies,and increasing throughput.A minimum execution time algorithm is used to compute the completion time of all the available resources which are allocated to the virtual machine and lion optimization algorithm is applied to packets in a cloud environment.The proposed work is shown to improve the throughput and latency rate.

Mapping Potential Infiltration Patterns Using Digital Elevation Model

This study attempts to simulate the spatial heterogeneity of infiltration in a drainage basin using digital elevation models. Infiltration capacity is one of the controlling factors in the formation of stream channels. Channel formation is also a function of the slope and the contributing area. Natural stream channels, if properly graded and adjusted to the present climate, reflect the interactions of local slope, contributing area, and permeability of surface materials. Channel networks can be delineated from a Digital Elevation Model (DEM) using a variety of algorithms using different thresholds for channel initiation. These algorithms delineate a channel network on the basis of local slope, curvature, and contributing area, without considering the permeability of surface cover. Hence, the difference in the structure of the two drainage networks,?i.e.?the surveyed drainage network obtained from field observation and the simulated network generated from the DEM, is indicative of the spatial heterogeneities in the permeability of the surface cover as shown in this paper. Spatially variable drainage density maps corresponding to the two networks have been used here to obtain normalized difference maps that characterize the potential infiltration anomalies within the catchment. The simulated spatial pattern is compared with the actual infiltration measurements in the field using infiltration tests. Strong positive correlation between the observed and modeled infiltration confirms the effectiveness of this technique in the rapid assessment of potential infiltration variability.

Significance of Precipitation Chemistry for Delineating Polluted Parts of Maheshwaram Aquifer System,Andhra Pradesh

The chemistry of subsurface water bodies is difficult to understand unless precipitation chemistry and atmospheric processes are taken into consideration. Limited pioneer work has been carried out on considering precipitation chemistry.Polluted zone delineation is very much significant before the planning for any of the remedial measures.The dual contamination is a common problem noticed

Fluoride Hydro-geochemistry Studies:A Case Study from Granitic Aquifer System of Maheshwaram,Hyderabad,India

The impact of population pressure has been observed on several systems,groundwater resource is one among them.Mismanagement and over-exploitation has not only caused the decline of groundwater levels but also causes deterioration in water quality. Fluoride is one of such parameters where impact of over exploitation has been observed.Fluoride is

An AW-HARIS Based Automated Segmentation of Human Liver Using CT Images

In the digestion of amino acids,carbohydrates,and lipids,as well as protein synthesis from the consumed food,the liver has many diverse responsibilities and functions that are to be performed.Liver disease may impact the hormonal and nutritional balance in the human body.The earlier diagnosis of such critical conditions may help to treat the patient effectively.A computationally efficient AW-HARIS algorithm is used in this paper to perform automated segmentation of CT scan images to identify abnormalities in the human liver.The proposed approach can recognize the abnormalities with better accuracy without training,unlike in supervisory procedures requiring considerable computational efforts for training.In the earlier stages,the CT images are pre-processed through an Adaptive Multiscale Data Condensation Kernel to normalize the underlying noise and enhance the image’s contrast for better segmentation.Then,the preliminary phase’s outcome is being fed as the input for the Anisotropic Weighted—Heuristic Algorithm for Real-time Image Segmentation algorithm that uses texture-related information,which has resulted in precise outcome with acceptable computational latency when compared to that of its counterparts.It is observed that the proposed approach has outperformed in the majority of the cases with an accuracy of 78%.The smart diagnosis approach would help the medical staff accurately predict the abnormality and disease progression in earlier ailment stages.

Application of ferrous sulfate alleviates negative impact of cadmium in rice(Oryza sativa L.)

Soil contamination with toxic heavy metals[such as cadmium(Cd)]is becoming a serious global problem due to rapid development of social economy.Iron(Fe),being an important element,has been found effective in enhancing plant tolerance against biotic and abiotic stresses.The present study investigated the extent to which different levels of Ferrous sulphate(FeSO_(4))modulated the Cd tolerance of rice(Oryza sativa L.),when maintained in artificially Cd spiked regimes.A pot experiment was conducted under controlled conditions for 146 days,by using natural soil,mixed with different levels of CdCl_(2)[0(no Cd),0.5 and 1 mg/kg]together with the exogenous application of FeSO_(4) at[0(no Fe),1.5 and 3 mg/kg]levels to monitor different growth,gaseous exchange characteristics,oxidative stress,antioxidative responses,minerals accumulation,organic acid exudation patterns of O.sativa.Our results depicted that addition of Cd to the soil significantly(P<0.05)decreased plant growth and biomass,gaseous exchange parameters,mineral uptake by the plants,sugars(soluble,reducing,and non-reducing sugar)and altered the ultrastructure of chloroplasts,plastoglobuli,mitochondria,and many other cellular organelles in Cd-stressed O.sativa compared to those plants which were grown without the addition of Cd in the soil.However,Cd toxicity boosted the production of reactive oxygen species(ROS)by increasing the contents of malondialdehyde(MDA),which is the indication of oxidative stress in O.sativa and was also manifested by hydrogen peroxide(H_(2)O_(2))contents and electrolyte leakage to the membrane bounded organelles.Although,activities of various antioxidative enzymes like superoxidase dismutase(SOD),peroxidase(POD),catalase(CAT)and ascorbate peroxidase(APX)and non-enzymatic antioxidants like phenolics,flavonoid,ascorbic acid,anthocyanin and proline contents increased up to a Cd level of 0.5 mg/kg in the soil but were significantly diminished at the highest Cd level of 1 mg/kg in the soil compared to those plants which were grown without the addition of Cd in the soil.The negative impacts of Cd injury were reduced by the application of FeSO_(4) which increased plant growth and biomass,improved photosynthetic apparatus,antioxidant enzymes,minerals uptake together with diminished exudation of organic acids as well as oxidative stress indicators in roots and shoots of O.sativa by decreasing Cd retention in different plant parts.These results shed light on the effectiveness of FeSO_(4) in improving the growth and upregulation of antioxidant enzyme activities of O.sativa in response to Cd stress.However,further studies at field levels are required to explore the mechanisms of FeSO_(4)-mediated reduction of the toxicity of not only Cd,but possibly also other heavy metals in plants.

An Effective Online Collaborative Training in Developing Listening Comprehension Skills

The COVID-19 outbreak severely affected formal face-to-face classroom teaching and learning.ICT-based online education and training can be a useful measure during the pandemic.In the Pakistani educational context,the use of ICT-based online training is generally sporadic and often unavailable,especially for developing English-language instructors’listening comprehension skills.The major factors affecting availability include insufficient IT resources and infrastructure,a lack of proper online training for speech and listening,instructors with inadequate academic backgrounds,and an unfavorable environment for ICT-based training for listening comprehension.This study evaluated the effectiveness of ICT-based training for developing secondary-level English-language instructors’listening comprehension skills.To this end,collaborative online training was undertaken using random sampling.Specifically,60 private-school instructors in Chakwal District,Pakistan,were randomly selected to receive online-listening training sessions using English dialogs.The experimental group achieved significant scores in the posttest analysis.Specifically,there were substantial improvements in the participants’listening skills via online training.Given the unavailability of face-to-face learning during COVID-19,this study recommends using ICT-based online training to enhance listening comprehension skills.Education policymakers should revise curricula based on online teaching methods and modules.

Multi-Features Disease Analysis Based Smart Diagnosis for COVID-19

Coronavirus 2019(COVID-19)is the current global buzzword,putting the world at risk.The pandemic’s exponential expansion of infected COVID-19 patients has challenged the medical field’s resources,which are already few.Even established nations would not be in a perfect position to manage this epidemic correctly,leaving emerging countries and countries that have not yet begun to grow to address the problem.These problems can be solved by using machine learning models in a realistic way,such as by using computer-aided images during medical examinations.These models help predict the effects of the disease outbreak and help detect the effects in the coming days.In this paper,Multi-Features Decease Analysis(MFDA)is used with different ensemble classifiers to diagnose the disease’s impact with the help of Computed Tomography(CT)scan images.There are various features associated with chest CT images,which help know the possibility of an individual being affected and how COVID-19 will affect the persons suffering from pneumonia.The current study attempts to increase the precision of the diagnosis model by evaluating various feature sets and choosing the best combination for better results.The model’s performance is assessed using Receiver Operating Characteristic(ROC)curve,the Root Mean Square Error(RMSE),and the Confusion Matrix.It is observed from the resultant outcome that the performance of the proposed model has exhibited better efficient.

Unified Computational Modelling for Healthcare Device Security Assessment

This article evaluates the security techniques that are used to maintainthe healthcare devices, and proposes a mathematical model to list these in theorder of priority and preference. To accomplish the stated objective, the articleuses the Fuzzy Analytic Network Process (ANP) integrated with Technical forOrder Preference by Similarities to Ideal Solution (TOPSIS) to find the suitablealternatives of the security techniques for securing the healthcare devices fromtrespassing. The methodology is enlisted to rank the alternatives/ techniquesbased on their weights’ satisfaction degree. Thereafter, the ranks of the alternatives determine the order of priority for the techniques used in healthcare security.The findings of our analysis cite that Machine Learning (ML) based healthcaredevices obtained the highest priority among all the other security techniques.Hence the developers, manufacturers and researchers should focus on the MLtechniques for securing the healthcare devices. The results drawn through theaid of the suggested mathematical model would be a corroborative referencefor the developers and the manufacturers in assessing the security techniques ofthe healthcare devices.

Seroprevalence of Dengue Virus IgG among Children 1 - 15 Years, Selected from an Urban Population in Karachi, Pakistan: Population Based Study

Objectives: This was to estimate the proportion of Dengue virus specific IgG ELISA among asymptomatic children between the ages of 1 year to 15 years, residing in an urban population of Karachi. Design: Cross-sectional study. Settings: Subjects were selected from Garden, Karachi;an urban area located adjacent to the Central district of Karachi. Participants: Children of ages 1 year to 15 years, of either sex, residing in the urban area of Garden, Karachi for more than 1 year were selected for the study. Those with a history of yellow fever or using corticosteroids within 1 month of recruitment were excluded. Outcome measures: Data were collected on socioeconomic status of households, medical history, including previous dengue infection, general examination findings and anthropometric indices. Blood samples were collected and sent to Research Laboratories, AKU for determining complete blood counts and serum IgG antibodies for Dengue. All collected information was then analyzed for ascertaining the predicting factors for positive IgG among children less than 15 years. Results: From a total of 900 subjects, 46% were found to have positive IgG in their bloods. Our results revealed that a male child of age more than 10 years was more likely to be IgG positive. Other risk factors identified with the seropositivity included lower household income and absence of anemia, thrombocytopenia and lack of hand washing. Conclusions: The study indicated a significant proportion of children under 15-year-old infected with Dengue virus, with a potential risk of severe complications, if re-infected with dengue. Stringent measures are still needed by both public and private authorities to contain dengue outbreaks, and reducing the proportion of associated mortality, as seen in the previous years. Trial registration: Seed Money Grant (ID# SM090101) was awarded to the corresponding author by Research Committee, Faculty of Health Sciences, Aga Khan University, Pakistan.

Spectrum of Upper GI Endoscopy in Pediatric Population at a Tertiary Care Centre in Pakistan

Although upper GI endoscopy is considered to be a gold standard in diagnosis of many pediatric gastrointestinal disorders, there is limited data about its utility from developing countries. We carried out this retrospective study at Aga khan University Hospital, Karachi, Pakistan from 2008-2012. During the study period, a total of 200 procedures were performed. Mean age of patients was 8.5 years. 66% of patients received general anesthesia for the procedure. Failure to thrive with suspected coeliac disease was the most common indication for the procedure, seen in 31% of patients. Gastritis was the most common abnormal endoscopic finding, seen in 14.5% of patients. Gastritis was the most common histopathological finding on biopsy, seen in 31% of the patients (n = 62). Findings?were consistent with coeliac disease in 18% (n = 36), duodenitis, 10.5% (n = 21) and esophagitis, 4%?(n = 8) of patients. No immediate post procedure complication was noted in our study.

Power Factor Improvement of AC-DC Converter Based on Separately Excited DC Motor Using Passive Filter

In industries DC motor drives are very essential due to their high performance applications such as its reliability, ease of control, low cost and simplicity. And speed control of these motors is very easy due to power electronic AC-DC converters. These power electronic converters are with prominent low power factor and higher Total Harmonic Distortion (THD). These converters operate only for short time resulting non-sinusoidal waveform. This problem of harmonic distortion can be mitigated by reshaping the non-sinusoidal waveform to pure sine wave. Different wave shaping techniques have been developed by using different filters among which one is tuned passive filter. This paper proposed power factor improvement and harmonic mitigation of AC-DC converters based on separately excited DC motor using tuned passive filter. In this context experimental model is designed and results are analyzed by power quality analyzer.

Light-induced tumor theranostics based on chemical-exfoliated borophene

Among 2D materials(Xenes)which are at the forefront of research activities,borophene,is an exciting new entry due to its uniquely varied optical,electronic,and chemical properties in many polymorphic forms with widely varying band gaps including the lightest 2D metallic phase.In this paper,we used a simple selective chemical etching to prepare borophene with a strong near IR light-induced photothermal effect.The photothermal efficiency is similar to plasmonic Au nanoparticles,with the added benefit of borophene being degradable due to electron deficiency of boron.We introduce this selective chemical etching process to obtain ultrathin and large borophene nanosheets(thickness of ~4 nm and lateral size up to ~600 nm)from the precursor of AlB_(2).We also report first-time observation of a selective Acid etching behavior showing HCl etching of Al to form a residual B lattice,while HF selectively etches B to yield an Al lattice.We demonstrate that through surface modification with polydopamine(PDA),a biocompatible smart delivery nanoplatform of B@PDA can respond to a tumor environment,exhibiting an enhanced cellular uptake efficiency.We demonstrate that borophene can be more suitable for safe photothermal theranostic of thick tumor using deep penetrating near IR light compared to gold nanoparticles which are not degradable,thus posing longterm toxicity concerns.With about 40 kinds of borides,we hope that our work will open door to more discoveries of this top-down selective etching approach for generating borophene structures with rich unexplored thermal,electronic,and optical properties for many other technological applications.

Zeolites for food applications:A review Cristian

Zeolites have been little investigated for food applications,despite their chemical composition is similar to clays and clay minerals,which have been extensively analyzed for various applications,including food.Zeolites can be distinguished from clay materials,since the former have a porous microstructure characterized by intracrystalline cavities and channels,while the latter have a laminar microstructure.The goal of this review paper was to give a comprehensive perspective in terms of the different food applications found so far for zeolites,namely:antimicrobial materials,ethylene scavengers,fillers for food packaging materials,food nanoreactors,food substance sensors,immobilizers and stabilizers of active compounds and enzymes,molecular sieves for the pretreatment of food samples,as well as intelligent food contact materials.The main food applications from zeolites are related to their good properties as adsorbent materials,and these properties can be altered and tuned by ion exchange,surface organo-modification,among others,for a specific designed application.Zeolites for food applications have been investigated primarily as antimicrobial materials,concentrators of target analytes and sensors for food substances.However,the other potential food applications indicated above from zeolites are booming,since they are harmless materials recognized by various organizations.