Prevalence of Fasciolosis in Buffaloes of Bahawalpur, Punjab, Pakistan

Fasciolosis is a trematode borne parasitic disease that infects liver of large ruminants widely prevalent throughout the world. During the present study fecal samples from buffaloes were collected on random basis from the all tehsils of Bahawalpur district form February 2012 to October 2012. Of total 1800 fecal samples, 284 (15.8%) were found to be positive. Highest prevalence was recorded in Yazman (21.7%) followed by Bahawalpur (16.7%), Khairpur (15.6%), Hasilpur (14.4%) and the lowest was recorded in Ahmedpur (10.6%). Statically chi-square (?2) showed non significant (p>0.05) difference between all areas. Monthly overall highest prevalence was recorded in September (31%), while the lowest was found in the month of May (3.5%). Statistically a significant (p<0.05) difference was recorded in all months. Overall highest seasonal wise prevalence was found in autumn (28.3%) followed by winter (21%), summer (12%) and lowest in spring (8.3%). In age wise prevalence the adult buffaloes were highly (19.9%) infected than young ones (5.3%). Statistically a significant difference (p<0.05) was found between all seasons and age groups. Gender wise the prevalence was slightly higher but statistically non significant (p>0.05) in females (15.9%) than males (15.1%). Bahawalpur (Pakistan) has a significant prevalence (%) of fasciolosis that may cause economic loss. Keys word: Fasciolosis, baffaloes, Bahawalpur, prevalence

A Mosaic of Risk Factors for Female Infertility in Pakistan

Background: To identify different risk factors for female infertility including hormonal imbalance (FSH, LH and Prolactin) Methods: Infertile women were enrolled in this prospective study. A questionnaire was designed to collect information regarding socio-demographic and clinical characteristics of the study participants. Serum FSH, LH and Prolactin levels were estimated between 1-5 days of post menstrual period. Independent sample t- test, Spearman correlation and multivariate logistic regression were performed to find the association of different risk factors with female infertility. Results: Highest percentage (57.7%) of infertile females was in the age bracket of 26 to 35 years. The prevalence of primary infertility was 60.4% . Mean levels of LH and prolactin were significantly higher in women with primary infertility compared to those with secondary infertility. No significant difference was observed in the mean level of FSH . A significant positive correlation was found between infertility and age , marital history and infertility duration. On multivariate logistic regression analysis women with secondary infertility were more likely to be hypertensive(OR=2.126,95%CI:1.020-4.474, p-value0.044), using contraceptive OR = 5.876, 95% CI: 2.491–13.86, p-value .001),have hyperprolactenemia (OR=1.289,95%CI:0.960-1.996,p-value0.001) and have marital history of more than 16 years OR=12.166,95%CI:5.048-29.322, p-value0.001). Conclusion:Highest prevalence of infertility was seen in the age group of 26-35 years. Advanced age, hypertension, hyperprolactemia, use of contraceptive and marital history of more than 16 years are significantly associated with female infertilit

Fuzzy-Based Segmentation for Variable Font-Sized Text Extraction from Images/Videos

Textual information embedded in multimedia can provide a vital tool for indexing and retrieval. A lot of work is done in the field of text localization and detection because of its very fundamental importance. One of the biggest challenges of text detection is to deal with variation in font sizes and image resolution. This problem gets elevated due to the undersegmentation or oversegmentation of the regions in an image. The paper addresses this problem by proposing a solution using novel fuzzy-based method. This paper advocates postprocessing segmentation method that can solve the problem of variation in text sizes and image resolution. The methodology is tested on ICDAR 2011 Robust Reading Challenge dataset which amply proves the strength of the recommended method

A Survey of the Techniques for The Identification and Classification of Human Actions from Visual Data

Recognition of human actions form videos has been an active area of research because it has applications in various domains. The results of work in this field are used in video surveillance, automatic video labeling and human-computer interaction, among others. Any advancements in this field are tied to advances in the interrelated fields of object recognition, spatio- temporal video analysis and semantic segmentation. Activity recognition is a challenging task since it faces many problems such as occlusion, view point variation, background differences and clutter and illumination variations. Scientific achievements in the field have been numerous and rapid as the applications are far reaching. In this survey, we cover the growth of the field from the earliest solutions, where handcrafted features were used, to later deep learning approaches that use millions of images and videos to learn features automatically. By this discussion, we intend to highlight the major breakthroughs and the directions the future research might take while benefiting from the state-of-the-art methods

علی عباس جلال پوری کی افسانہ نگاری

Ali Abbas Jalal Puri is a prominent writer of twentieth century. Criticism and philosophy are his recognized fields but he started his literary journey by writing short stories in the renowned journals of that time which are under fog now. Now it is necessary to document and understand his short stories with special reference of his philosophical views. This article is research base discovery of his short stories and their critical description as well.</p

Empirical Analysis of Signature-Based Sign Language Recognition

The significance of automated SLR (Sign Language Recognition) proved not only in the deaf community but in various other spheres of life. The automated SLR are mainly based on the machine learning methods.PSL (Pakistani Sign Language)is an emerging area in order to benefit a big community in this region of the world. This paper presents recognition of PSL using machine learning methods. We propose an efficient and invariant method of classification of signs of PSL. This paper also presents a thorough empirical analysis of signature-based classification methods. Six different signatures are analyzed for two distinct groups of signs having total of forty five signs. Signs of PSL are close enough in terms of inter-sign similarity distancetherefore, it is a challenge to make the classification. Methodical empirical analysis proves that proposed method deals with these challenges adequately and effectivel

A Transfer Learning Approach for Clinical Detection Support of Monkeypox Skin Lesions

Monkeypox (MPX) is a disease caused by monkeypox virus (MPXV). It is a contagious disease and has associated symptoms of skin lesions, rashes, fever, and respiratory distress lymph swelling along with numerous neurological distresses. This can be a deadly disease, and the latest outbreak of it has shown its spread to Europe, Australia, the United States, and Africa. Typically, diagnosis of MPX is performed through PCR, by taking a sample of the skin lesion. This procedure is risky for medical staff, as during sample collection, transmission and testing, they can be exposed to MPXV, and this infectious disease can be transferred to medical staff. In the current era, cutting-edge technologies such as IoT and artificial intelligence (AI) have made the diagnostics process smart and secure. IoT devices such as wearables and sensors permit seamless data collection while AI techniques utilize the data in disease diagnosis. Keeping in view the importance of these cutting-edge technologies, this paper presents a non-invasive, non-contact, computer-vision-based method for diagnosis of MPX by analyzing skin lesion images that are more smart and secure compared to traditional methods of diagnosis. The proposed methodology employs deep learning techniques to classify skin lesions as MPXV positive or not. Two datasets, the Kaggle Monkeypox Skin Lesion Dataset (MSLD) and the Monkeypox Skin Image Dataset (MSID), are used for evaluating the proposed methodology. The results on multiple deep learning models were evaluated using sensitivity, specificity and balanced accuracy. The proposed method has yielded highly promising results, demonstrating its potential for wide-scale deployment in detecting monkeypox. This smart and cost-effective solution can be effectively utilized in underprivileged areas where laboratory infrastructure may be lacking

Remote Sensing Assessment of Small Dam Sites in Swat District, Pakistan: Inferences from Water Resource Scenarios

In a world where water is indispensable, Pakistan grapples with the challenge of ensuring its availability. Freshwater demand from domestic, industrial, and agricultural uses has strained the country's reservoirs.  Financial and political barriers have hindered the construction of large dams, making it imperative to seek alternative solutions. However, small dams have the potential to address Pakistan's water security concerns. This study uses advanced technology, engineering expertise, socioeconomic factors, and environmental awareness to find multi-purpose small dam sites in Swat District, Pakistan. Water storage and community and economic development are goals. This study examines criteria using RS and GIS. Dam site selection considers rainfall patterns, slopes, land use, soil types, and drainage density. The study uses Elevation Area Capacity (EAC) curves to view potential reservoirs. The map divides areas into High, Moderate, and Low suitability. This analysis yields some sites where R4 is impressive for its suitability and storage capacity of 358,237 at 2080 m. R1 and R2 are promising with moderate suitability and large storage capacities of 121,346 and 271,964, respectively. These sites are more than numbers on a map they represent local aspirations. Their benefits include electricity, flood protection, irrigation, and drinking water. Small dams are progress catalysts with low maintenance and political support. This study concludes that socioeconomic and environmental factors should be considered when engineering small dams. This small dam can store water and provide essential services to local communities and economies. These multi-purpose small dams advance water security