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Abstract Background Hemoglobinopathies, including sickle cell disease (SCD), have been recognized as a major health problem globally. SCD is caused by a mutation in the GAG codon that converts glutamate to valine, resulting in sickle hemoglobin (HbS) and various clinical symptoms. Main body An estimated 300,000 new-borns are diagnosed with SCD every year which makes it a very important clinical manifestation to study. The present review aims to comprehensively explore the pathophysiology, diagnostics, and management approaches for populations affected by sickle cell disease. Different genetic forms of SCDs are also mentioned in this review. Short conclusion HbS polymerization contributes to the overall pathophysiological process of SCD. Several treatment options are available, though the US Food and Drug Administration-approved low-toxicity medication hydroxyurea is commonly used to treat SCD complications. Besides, hemopoietic stem cell transplantation and gene therapy are also two potential curative approaches. For SCD management, genetic counseling and neonatal screening at different stages play a crucial role.

Venous aneurysms of the external jugular vein are rare vascular anomalies due to the low pressure in the venous circulation i.e. the superior vena cava. A review of the literature reveals that external jugular vein aneurysms are reported rarely but the exact incidence of such aneurysms is not known. The presentation of external jugular vein aneurysms can vary widely but generally, they present as a soft cervical mass which gradually increases in size. These aneurysms pose a diagnostic and management challenge for the clinician as their clinical spectrum ranges from being asymptomatic, to cosmetic concerns or they can potentially cause thrombosis, embolism, or thrombophlebitis. Diagnosis is confirmed via Color Doppler ultrasound and computerized tomogram angiography. We present the clinical features and diagnosis of a saccular external jugular vein pseudoaneurysm in a 58-year-old female, which was most likely to be congenital and was diagnosed using computerized tomogram angiography.

Papaya (Carica papaya) fruit has a short shelf life and suffers significant postharvest losses due to climacteric, instant ripening and perishable nature. Pre-storage hot water treatment (HWT) has significant potential to delay decay incidence in horticultural commodities. The present study was designed to evaluate effectiveness of HWT on ‘Red lady’ papaya fruit for minimizing the fruit decay and maintaining the quality during storage. Physiologically mature unripe ‘Red lady’ papaya fruit harvested from a commercial papaya orchard. Selected fruits were treated at three different hot water temperatures (50 °C, 52 °C and 54 °C) along with a control (room temp) for 10 minutes thereafter stored at 12 °C and 85–90% RH for four weeks. Different sensory evaluation, fruit quality scales and enzymatic activities were observed at weekly intervals. Fruit stored after 54 °C HWT showed lower weight loss (4.63%), decay incidence (5.1%) and higher fruit firmness (12.92 N) relative to control. Fruit treated at 52 °C HWT improved the fruit acidity, but total soluble solids decreased than control. The results revealed that ascorbic acid (33.33 mg/100 g), total phenolic contents (35 mg/g FW) total antioxidants (47.50% DPPH inhibition), and antioxidative enzyme activities were improved by 52 °C HWT. It is concluded that pre storage papaya fruit treatment (HWT @ 52 °C) preserves the quality of fruit throughout storage on the other hand at 54 °C HWT helps in decreased fruit decaying. It can be summarized that papaya fruit can be treated with hot water in the range of 52–54 °C to support the fruit shelf life and suppress fruit decay along with maintaining fruit quality.Practical applications: Papaya (Carica papaya L.) is a climacteric fruit which is highly susceptible to fungal attacks after harvest. Due to its perishable nature, it becomes decayed and huge amount of highly nutritious and medicinally important fruit is wasted. Recently people are more concerned about food safety which limits the use of fungicides for controlling the fruit decay in papaya. However, heat treatment has tremendous potential to control microbial decay, and keep food commodities safe from hazardous chemicals. In this study, the hot water treatment has successfully suppressed the fruit decay and maintained fruit quality of papaya in the course of entire period of cold storage. These findings indicated that use of hot water treatment is a practical approach for increasing the shelf life of papaya fruit.

Energy is integral to the socio-economic development of every country. This development leads to a rapid increase in the demand for energy consumption. However, due to the constraints and costs associated with energy generation resources, it has become crucial for both energy generation companies and consumers to predict energy consumption well in advance. Forecasting energy needs through accurate predictions enables companies and customers to make informed decisions, enhancing the efficiency of both energy generation and consumption. In this context, energy generation companies and consumers seek a model capable of forecasting energy consumption both in the short term and the long term. Traditional models for energy prediction focus on either short-term or long-term accuracy, often failing to optimize both simultaneously. Therefore, this research proposes a novel hybrid model employing Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), and Bi-directional LSTM (Bi-LSTM) to simultaneously predict both short-term and long-term residential energy consumption with enhanced accuracy measures. The proposed model is capable of capturing complex temporal and spatial features to predict short-term and long-term energy consumption. CNNs discover patterns in data, LSTM identifies long-term dependencies and sequential patterns and Bi-LSTM identifies complex temporal relations within the data. Experimental evaluations expressed that the proposed model outperformed with a minimum Mean Square Error (MSE) of 0.00035 and Mean Absolute Error (MAE) of 0.0057. Additionally, the proposed hybrid model is compared with existing state-of-the-art models, demonstrating its superior performance in both short-term and long-term energy consumption predictions.

ومن الموثق أن منطقة شبه القارة الهندية لها تاريخ طويل من أصل قديم، وهي من أخصب الأماكن على وجه الأرض من حيث الثقافة والعلوم والفن. وكانت مركزًا للفنون والعلوم. وقد أنتجت هذه المنطقة العديد من العلماء وخاصة في مجال الدراسات الإسلامية. ومنهم الشيخ أبو الحسن علي الندوي r. والشيخ أبو الحسن على الندوي درّة يتيمةٌ وعقد فريد من هذه الحلقة الميمونة من العلماء والمفكرين. وهو من الشخصيات البارزة في القرن الماضي، وقد أسهم الشيخ بمؤلفاته القيّمة وآرائه السديدة ومحاضراته النيرّة في مجالات متعددة، مثل الأدب والتاريخ والدعوة والتربية. وقد بذل الشيخ جهوداً مضنية في تناول الجوانب الدينية والأدبية والفكرية والدعوية، وحياة الندوي عبارة عن الجهود المتواترة في سبيل إحقاق الحق وإبطال الباطل، وإرشاد الأمة وإخراجها من ظلمات الحضارة الغربية وبراثن المادية والإباحية. تدور هذا البحث حول: الملامح البلاغية في كتاب أبي الحسن علي الندويr"ماذا خسر العالم بانحطاط المسلمين" وفي هذا البحث أركز على المباحث التالية : المبحث الأول: حياة الندوي بالإيجاز المبحث الثاني: "ماذا خسر العالم بإنحطاط المسلمين" أهميته وأسلوبه المبحث الثالث: أسلوب الندوي والسمات البلاغية في كتابه. نتائج البحث الكلمات المفتاحية: النثر الأدبي، الندوي، الملامح البلاغية، ماذا خسر العالم بإنحطاط المسلمين

Simple sequence repeats (SSRs) are present across both coding & non-coding regions of the genomes of all organisms with diversity in incidence, complexity, and repetition. The present study is focused on Adenoviridae which are non-enveloped viruses consisting of linear double-stranded DNA genome. The members of Adenoviridae are known to cause respiratory illnesses like the common cold (cough, runny nose, mild fever), pneumonia (occasionally), keratoconjunctivitis (infection in the eye known as pink eye), croup and cystitis (inflammation of the bladder). Our investigation aims to extract and analyse SSRs from 68 Adenoviridae genomes. Virus genome sequences were retrieved from NCBI and SSRs extracted from MISA. ETE3 and iTOL were used for the phylogenetic tree construction, annotation and visualization. The genome length of Adenoviridae genomes ranged from 26163 bp to 45667 bp while GC content varied from 33.6 % to 66.9 %. Genome wide analysis revealed a total incidence of 9861 SSRs and 793 cSSRs. The minimum and maximum range of SSR incidence is 112 (A67) to 203 (A61) respectively. The most prevalent mono, di and tri-SSR motif is “A”, “GC/CG” and “GAG/CTC” comprised of 1177, 1859 and 201 occurrences respectively. About 78 % SSRs are present in the coding region in the studied genomes. In terms of protein specific distribution, DNA polymerase enzyme had the highest incidence of 485 SSRs. The presence of mono-SSRs in the A/T region is a marker for host determination and divergence. The average mono-SSRs present in A/T region is 67.14 % and it ranged from 16.22 % to 99.11 %. The high prevalence of mono-SSRs in the A/T region was associated with human and related species as hosts. Further, the clustering of viruses as per their hosts was observed in the phylogenetic tree suggesting the role of host in viral evolution. The presence of unique and conserved cSSRs as genome markers has also been highlighted.

The detection of hate speech on online platforms is essential for maintaining safe and inclusive digital environments. Although significant progress has been made in binary classification for hate speech detection, challenges persist in multilingual and fine-grained classification. This study presents a comprehensive model for hate speech detection across English, Urdu, and Sindhi, utilizing advanced deep learning models like Bidirectional Encoder Representations from Transformers (BERT) and its multilingual variants. Additionally, the research employs Explainable Artificial Intelligence (XAI) techniques, such as Local Interpretable Model-Agnostic Explanations (LIME), to gain insights into model performance. This work curated a multilingual hate speech detection dataset and a robust fine-grained hate speech detection model. The dataset includes non-hate and hate speech classes. Furthermore, the hate speech class is categorized into five fine-grained categories, including Disability, Gender, Nationality, Race, and Religion. The experimental findings of this study showed 91% F-score in binary class classification and 86% weighted F-score in fine-grained hate speech detection for multilingual datasets using XLM-RoBERTa technique. Notably, the Religion class achieved the highest F-score of 92%. It is believed that this study contributes to reducing the spread of hate speech (written in Either Urdu, English, or Sindhi) on various social media platforms.

In order to protect the web against automated attacks, CAPTCHAs are most widely used mechanism on the internet. Numerous types of CAPTCHAs are introduced due to weaknesses in the earlier designs. Animated CAPTCHAs are one of the design alternatives. Instead of presenting the whole information at once, animated CAPTCHAs present information in various frames over the specific interval of time. As CATPCHAs are ubiquitously used to avoid the serious threats from bots therefore it is important to verify their effectiveness. In this research we have verified their robustness against machine learning attacks. It has been proved that adding the extra time dimension does not necessarily ensure protection against automated attacks. We have attacked the Hello CAPTCHA scheme, which is the most popular animated CAPTCHA scheme available on the internet. By applying novel image processing and machine learning techniques, these CAPTCHAs are decoded with high precision. A pre-trained CNN is used to recognize the extracted characters. In this research, 6 popular types of animated CAPTCHAs along with 41 sub types were successfully deciphered with an overall precision of up to 99.5 %.

Background: As the world settles down from the COVID-19 pandemic, many countries are faced with an unexpected outbreak of monkeypox infection. Monkeypox is a zoonotic disease caused by monkeypox virus (MPXV), which is an enveloped, double stranded DNA virus belonging to the Poxviridae family. Presently, we construct and analyze the phylo-geo-network and the corresponding haplogroups. Presently, we performed the haplogroup analysis with their defining mutations and phylogenetic lineage study along with geographical distributions with the aim to understand the evolutionary path of the MPXV across the world. Results: Information about 719 full length genomes of MPXV were collected from GISAID repository and the sequences extracted from NCBI. The alignment of 719 MPXV genomes and their subsequent analysis revealed a total of 1530 segregating sites of which 330 were parsimony informative (PI) sites. The variations had a positive value of Tajima’s D statistic indicating some mutations being prevalent and hence balancing selection. A total of 39 haplogroups were observed in the phylo-geo-network and their defining mutations along with the evolutionary path has been discussed. The phylo-geo-network revealed the nodal haplogroup is represented by GISAID ID 13889450, haplogroup A1, an isolate from Germany, having a total of 296 identical sequences in the study incident across 22 countries. The localized evolution is highlighted by country specific sequences and haplogroups. USA had a total of 58 genomes and 13 haplogroups as compared to Peru (89 genomes, 7 haplogroups) and Germany (26 genomes, 6 haplogroups). Conclusions: The evolution of MPXV can be happening in a localized manner and hence accumulation of variations in the MPXV genomes needs to be monitored in order to be prepared for any possible threats.

Without a well-defined energy management plan, achieving meaningful improvements in human lifestyle becomes challenging. Adequate energy resources are essential for development, but they are both limited and costly. In the literature, several solutions have been proposed for energy management but they either minimize energy consumption or improve the occupant’s comfort index. The energy management problem is a multi-objective problem where the user wants to reduce energy consumption while keeping the occupant’s comfort index intact. To address the multi-objective problem this paper proposed an energy control system for a green environment called PMC (Power Management and Control). The system is based on hybrid energy optimization, energy prediction, and multi-preprocessing. The combination of GA (Genetic Algorithm) and PSO (Particle Swarm Optimization) is performed to make a fusion methodology to improve the occupant comfort index (OCI) and decrease energy utilization. The proposed framework gives a better OCI when compared with its counterparts, the Ant Bee Colony Knowledge Base framework (ABCKB), GA-based prediction framework (GAP), Hybrid Prediction with Single Optimization framework (SOHP), and PSO-based power consumption framework. Compared with the existing AEO framework, the PMC gives practically the same OCI but consumes less energy. The PMC framework additionally accomplished the ideal OCI (i-e 1) when compared with the existing model, FA–GA (i-e 0.98). The PMC model consumed less energy as compared to existing models such as the ABCKB, GAP, PSO, and AEO. The PMC model consumed a little bit more energy than the SOHP but provided a better OCI. The comparative outcomes show the capability of the PMC framework to reduce energy utilization and improve the OCI. Unlike other existing methodologies except for the AEO framework, the PMC technique is additionally confirmed through a simulation by controlling the indoor environment using actuators, such as fan, light, AC, and boiler.

Background: Cryptotanshinone (CPT), a Traditional Chinese Medicine (TCM) has recently gained remarkable interest as a potent alternative cancer therapeutic. The sole objective of this review is to accumulate the anti-tumour activity of CPT against major cancers as well as the underlying mechanisms. Methods: This comprehensive review focuses on the experimental outcome of in vivo and in vitro investigations targeting multiple signalling pathways of various cancers and molecular mechanisms involved in hindering cancer growth. Results: CPT targets different cell signalling pathways, transcription factors (STAT1, 3, 4, 5, c-Myc), cellular markers (PD-1, CTLA-4, PDL-1), kinases (Tyrosine kinase such as IGF-1R, Bcr-Abl, Src, JAK, FAK, Serine/Threonine kinase such as Aurora A, Cyclin dependent kinase such as CDK1, 2) which are associated with stemness, growth, division, proliferation, metastasis, angiogenesis and drug resistance of a cancer cell. CPT suppresses cancer progression by inhibiting the phosphorylation of intermediate signalling molecules like STAT3, hence disrupting the STAT3 signalling pathway amongst several other signalling pathways involved in cancer progression. CPT may also induce apoptosis by modulating several pro-apoptotic (Bax, Bak, Bcl-10) and anti-apoptotic (Bcl-2, Bcl-x, Bcl-xL) proteins. Furthermore, CPT showed potential drug synergism with other chemotherapeutic drugs resulting in strategizing better cancer treatment. Conclusion: This review summarizes that CPT, being a natural product with less side-effects in long-term cancer use, may be considered as a potential alternative to the traditional cancer therapies. Although, there is substantial evidence of success in laboratory, its efficacy for clinical application may be increased with an appropriate drug delivery approach and the accurate formulation or dosage.

Forests play a significant role for maintaining the biodiversity. In order to manage sustainable forests, tree species history, distribution, and their future prospects are vital. Using standardized quantitative approaches, the age, radial growth, and size class distribution of Abies pindrow (Himalayan fir) were determined from three different altitudinal sites (i.e. high, middle, and lower). The results indicate that Himalayan fir growing in the high-altitude site (Ayubia, 2 917 m a.s.l.) of moist temperate forests of the Himalayan mountains showed lower radial growth (0.13 cm) than in the middle (Bara Gali, 2 617 m a.s.l.; radial growth = 0.13 cm) and lower (Kuldana, 2 455 m a.s.l.; radial growth = 0.22 cm) altitude sites. Correlation analysis demonstrated that age showed a significant positive correlation (P < 0.001) with diameter at breast height. The tree-ring width chronology (totally 80 core samples) of Himalayan fir was developed from moist temperate forests of Himalayan mountains of Pakistan. At Ayubia site it possesses a long time-span (1703-2020 C.E.), followed by Bara Gali (1862-2020 C.E.) and Kuldana (1864-2020 C.E.). Further, the tree-ring width (TRW) chronology of Ayubia showed a significant positive correlation (P < 0.05) with May and June temperature, and a significant negative correlation (P < 0.05) with June and October precipitation, indicating that summer temperatures are the key factor for the radial growth of Himalayan fir. For the Kuldana site, the response of TRW chronology to temperature and precipitation was the same, however, it was significant only for June temperature at Bara Gali. The size class distribution of the high-altitude region (Ayubia) showed a higher number of individuals than the lower altitude region, indicating the lowest disturbance conditions. The absence of individuals in the early size classes and the gap in middle and mature size classes indicate a lower regeneration potential and anthropogenic impact. The pointer year analysis indicated that the Bara Gali forest is more sensitive to abnormal climate events than the other sites. Based on the present study, we suggest that proper attention and conservation strategy should be provided to Himalayan fir growing in the moist temperate forests of Pakistan.

Objective: To determine the frequency of depression in patients with vitamin B12 deficiency. Methodology: This cross-sectional study was carried out from January 2020 to March 2021 on a total sample size of n=100 patients (age 49.84 ± 0.91 years) using a simple random sampling technique, visiting the medical department of the federal government polyclinic hospital, in Islamabad. Patients presenting with macrocytic anaemia secondary to vitamin B12 deficiency were included while the patients with previously diagnosed depression were excluded from the study. Serum vitamin B12 levels were measured through the ELISA technique. Patient Healthcare Questionnaire-9 (PHQ-9) was designed and presented to patients with vitamin B12 deficiency for depression assessment. Patients with PHQ-9 score ≤5 were rated as having no depression and the patients with score ≥5 were rated as having depression. Data were analyzed using GraphPad Prism and the correlation coefficient was measured through non-linear fit and linear regression curves while ordinary ANOVA (non-parametric) was applied for study variables. Results: The average level of vitamin B12 in the serum and PHQ-9 score were recorded as 158 ± 4.94 (pg/uL) and 5.85 ± 0.30, respectively. Vitamin B12 levels and PHQ-9 score depicted an inverse correlation, however, no association was found between gender and PHQ-9 score. Conclusion: Data depicted that the patients presenting low levels of vitamin B12 in their serum have shown corresponding high PHQ-9 scores which is an indicator of depression. However, depression prevails in all age groups without any discrimination of gender.

In this study, landslide susceptibility analysis were undertaken in the Astore region, Pakistan. The Geographical Information System (GIS) and Remote Sensing (RS) techniques were used along with the analytical hierarchy process (AHP) to find out the landslide susceptibility of the region. The Astore, lying in the Himalayan mountains, experiences frequent landslides due to several triggering factors. Factors including slope, lithology, aspect, topographic wetness index (TWI), plan curvature, stream power index (SPI), distance from drainage, land use land cover (LULC) and soil were used. Each factor was processed in the GIS environment and weighted through the AHP technique. AHP weights were derived with a consistency ratio of 0.06. Finally, the five zones, very low, low, moderate, high, and very high are respectively covering 20.5% (28.98 km2), 33.1% (46.78 km2), 30.6% (43.26 km2), 10.8% (15.28 km2), and 4.9% (6.92 km2). Slope, lithology and LULC were the most important factors in triggering landslides.

Abstract Background Hepatitis E virus (HEV) is small (27–34 nm diameter) non-enveloped with positive sense ssRNA genome. Microsatellites or simple sequence repeats (SSR) are short tandem repeat sequences present across coding and non-coding regions of both prokaryotes and eukaryotes. They are involved with genome function and evolution at multiple levels. Results The complete genome sequences of 22 HEV genomes of the family Hepeviridae and genus Orthohepevirus (21 species) and Piscihepevirus (1 species) were extracted from NCBI database ( http://www.ncbi.nlm.nih.gov/ ). The extraction of microsatellites was done using Imperfect Microsatellite Extractor (IMEx) in ‘Advance-Mode’. The average genome size of the studied HEV genomes was 7003nt and it ranged from 6649nt (HEV11) to 7310nt (HEV22). The average GC content of the genomes was ~ 55%. A total of 519 SSRs and 21 cSSRS were extracted from the HEV genomes with an average incidence of 24 per genome ranging from 14 (HEV13) to 34 (HEV19). The cSSR incidence ranged from 0 (eight species) to 4 (HEV19). The genomes with no cSSR incidence had an SSR incidence range from 14 to 28. There were just four hexa-nucleotide repeat motifs and 5 penta-nucleotide repeat motifs observed. The most prevalent mono-, di-, and tri-nucleotide repeat motifs were “C”, “GT/TG”, and “GAC/CTG” respectively. The studied genomes had a minimum of ~ 90% incident SSRs present in the coding regions. Viruses with same or similar hosts are placed together on the phylogenetic tree implicating viral host being one of the driving forces for evolution. Conclusions Host range in viruses is being decided by multiple factors aided by the unique genome SSR signature and genomes of varied compositions need to be analyzed to forge a widely acceptable rule for predicting the same.

Bitter gourd (Momordica charantia L.) belongs to family Cucurbitaceae, and is a popular vegetable crop in the tropical and sub-tropical countries. It is an annually grown herbaceous vine that requires warm climate for growth. The leaves, stem and roots of bitter gourd contains a lot of bio-active components having nutritional and medicinal importance. Alternaria leaf blight (Alternaria cucumerina Ellis & Everh.) is a fungus which causes leaf blight on bitter gourd and leads to significant crop damage. The present study investigated the efficacy of five different fungicides against Alternaria leaf blight (ALB) of bitter gourd under in vivo and in vitro conditions. The single hyphal tip method was used to isolate and purify the fungal pathogen from the ALB infected leaves of bitter gourd. Five commercially available fungicides (1. Melody duo 66.8% WP, 2. Polyram DF 70%, 3. Score 250 EC, 4. Tilt 250 EC, 5. Flumax 60% EC) were evaluated at concentrations of 50 ppm and 100 ppm for effective ALB diseased control. Among tested fungicides, maximum inhibition (90 %) of fungal growth was given by Melody duo @ 100 ppm concentration followed by Polyram (81 %), Score (77 %) and Tilt (70 %), whereas Flumax resulted in minimum (45 %) fungal inhibition under in vivo. Melody duo revealed minimum disease incidence (15.67 %) compared to disease incidence recorded in polyram (17.83 %), Score (20.50 %) and Tilt (22.33 %) treated crop. Flumax was not tested in vitro because it gave minimum disease control in in vitro experiments. The control plants showed high disease incidence (56%).

The newly identified Omicron (B.1.1.529) variant of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has steered concerns across the world due to the possession of a large number of mutations leading to high infectivity and vaccine escape potential. The Omicron variant houses 32 mutations in spike (S) protein alone. The viral infectivity is determined mainly by the ability of S protein Receptor Binding Domain (RBD) to bind to the human Angiotensin I Converting Enzyme 2 (hACE2) receptor. In this paper, the interaction of the RBDs of SARS-CoV-2 variants with hACE2 was analyzed by using protein-protein docking and compared with the novel Omicron variant. Our findings reveal that the Omicron RBD interacts strongly with hACE2 receptor via unique amino acid residues as compared to the Wuhan and many other variants. However, the interacting residues of RBD are found to be the same in Lamda (C.37) variant. This unique binding of Omicron RBD with hACE2 suggests an increased potential of infectivity and vaccine evasion potential of the new variant. The evolutionary drive of the SARS-CoV-2 may not be exclusively driven by RBD variants but surely provides for the platform for emergence of new variants.

A sketch is a black-and-white, 2-D graphical representation of an object and contains fewer visual details as compared to a colored image. Despite fewer details, humans can recognize a sketch and its context very efficiently and consistently across languages, cultures, and age groups, but it is a difficult task for computers to recognize such low-detail sketches and get context out of them. With the tremendous increase in popularity of IoT devices such as smartphones and smart cameras, etc., it has become more critical to recognize free hand-drawn sketches in computer vision and human-computer interaction in order to build a successful artificial intelligence of things (AIoT) system that can first recognize the sketches and then understand the context of multiple drawings. Earlier models which addressed this problem are scale-invariant feature transform (SIFT) and bag-of-words (BoW). Both SIFT and BoW used hand-crafted features and scale-invariant algorithms to address this issue. But these models are complex and time-consuming due to the manual process of features setup. The deep neural networks (DNNs) performed well with object recognition on many large-scale datasets such as ImageNet and CIFAR-10. However, the DDN approach cannot be carried out for hand-drawn sketches problems. The reason is that the data source is images, and all sketches in the images are, for example, ‘birds’ instead of their specific category (e.g., ‘sparrow’). Some deep learning approaches for sketch recognition problems exist in the literature, but the results are not promising because there is still room for improvement. This article proposed a convolutional neural network (CNN) architecture called Sketch-DeepNet for the sketch recognition task. The proposed Sketch-DeepNet architecture used the TU-Berlin dataset for classification. The experimental results show that the proposed method beats the performance of the state-of-the-art sketch classification methods. The proposed model achieved 95.05% accuracy as compared to existing models DeformNet (62.6%), Sketch-DNN (72.2%), Sketch-a-Net (77.95%), SketchNet (80.42%), Thinning-DNN (74.3%), CNN-PCA-SVM (72.5%), Hybrid-CNN (84.42%), and human recognition accuracy of 73% on the TU-Berlin dataset.

The streamflow data acquisition with various techniques and dispersing of River’s locations demand improvement of reliability and frequency aspects. One of the reliability measurement characteristics is data ownership. The authority sharing data authorizes its quality and is also responsible for the wrong decision triggered by incorrect data. The consensus-based crowdsourcing data contribute to aggregated streamflow records’ generation. The aggregated streamflow records are stored on a streamflow ledger, a Hyperledger fabric-based ledger for rivers’ streamflow data. In contrast, InterPlanery File System (IPFS) distributed file storage system is helpful for policy documents and distribution scheme storage. Blockchain-based techniques for improvement of data-intensive decision support systems. The distributed river streamflow data measured and shared by distributed gauging officials and stored on the blockchain-based distributed storage system contributes to scalability, transparency, availability, and accessibility of shareable data. All stakeholders require quality data with trust and provenance management through a persistent, linked, and immutable copy of data. This technique resolves the conflict or disagreement on streamflow optimization and flood mitigation decisions. In a nutshell, the blockchain technology with IPFS for off-chain large files storage would contribute twofold to irrigation systems and flood mitigation domains. On one side, the streamflow data aggregation has consensus from streamflow assessment for software agents and stakeholders. Secondly, the persistent data copy is shared among distributed stakeholders using IPFS-based content addressed file-sharing protocol for a common operating picture to improve effective collaboration and coordination among managers of irrigation systems and flood mitigation activities.

Assessing the spatial distribution of organic matter and total nitrogen in soil is essential for management and optimum utilization of fertilizers. Therefore, the present field experiment was conducted to evaluate the impact of different planting pattern arrangements on the spatial distribution of soil total nitrogen and organic matter content under a maize/soybean strip relay intercropping system. The planting was arranged in a manner such that soil sampling could be done from continuous maize/soybean relay strip intercropping (MS1), maize/soybean relay strip intercropping in rotation (MS2), traditional maize/soybean intercropping (MS3), sole maize (M), sole soybean (S), and fallow land (FL) from 2018 to 2020. The results showed significant variations for soil organic matter and total nitrogen content under different planting pattern arrangements of maize and soybean in the strip relay intercropping system. Across all systems, the highest soil organic matter (29.19 g/kg) and total nitrogen (10.19 g/kg) were recorded in MS2. In contrast, the lowest soil organic matter (1.69 g/kg) and total nitrogen (0.64 g/kg) were observed in FL. Soil organic matter and total nitrogen in MS2 increased by 186.45% and 164.06%, respectively, when compared with FL. Soil organic matter and total nitrogen in MS2 increased by 186.45% and 164.06%, respectively, when compared with FL. Furthermore, under MS2, the spatial distribution of soil organic matter was higher in both maize and soybean crop rows as compared with other cropping patterns, whereas the soil total nitrogen was higher under soybean rows as compared with maize in all other treatment. However, correlation analysis of the treatments showed variations in organic matter content. It can be concluded that different planting patterns can have varying effects on soil organic matter and total nitrogen distribution under the strip relay intercropping system. Moreover, it is recommended from this study that MS2 is a better planting pattern for the strip relay intercropping system, which can increase the spatial distribution of soil organic matter and total nitrogen, thereby improving soil fertility, C:N ratio, and crop production. This study will serve as a foundation towards the scientific usage of chemical fertilizers in agricultural sector.

A temporal analysis of landscape change patterns and consequent evaluation of urban expansion has been studied for the Dera Ghazi Khan city which is developing fast since 2000 as an emerging metropolis of South Punjab. The geospatial techniques particularly remote sensing augmented with GIS are vital tools and are mostly used in studying landscape changes and decision making for sustainable urban development. Four Landsat images (1991, 2001, 2011 and 2021) obtained from the free web of GLFC have been analysed. A supervised classification algorithm was applied to all images and results have been presented in both tabular and graphic forms. Present study, focuses upon two land-use classes i.e. built up and open areas, which will be monitored by land-use patterns of Dera Ghazi Khan city during 1991 to 2021 using satellite images. The graphical depiction of all the landscape changes, which have taken place in D. G. Khan city in the form of tables and maps provides detailed information about the degree and ratio of urban expansion and the changes in land use that occurred during the stipulated period.The classification was based on four categories i.e., urban land, bare soil, vegetation, and water; while maps were prepared to present the temporal changes in D. G. Khan city. A total of 52 sq./kms areas was selected for this study designated as the Dera Ghazi Khan city. According to the results, 33% of the urban area has been expanded in Dera Ghazi Khan from 1991 to 2021 and 19% vegetation cover has been reduced. It is a very alarming situation that agricultural land is decreasing because of urban expansion. The results revealed the significance of remote sensing and GIS in evaluating landscape changes.

Anthracnose leaf spot caused by Colletotrichum gloeosporioides is an important disease of apples, resulting in serious damage to the fruit production. In this paper, the pathogenic and physiological characters of sixteen isolates and the wild isolate "Stj16" were studied. In the current study, we generated C. gloeosporioides strains expressing green fluorescence by introducing a GFP gene via an Agrobacterium tumefaciens-mediated transformation (ATMT). To confirm the subcellular localisation of the A2799 gene, an A2799gfp fusion expression mutant was constructed. After observation of the fusion expression, the A2799gfp fusion expression protein was located in the peroxisomes of the cell. The pathogenicity results showed that the mutants A4204, M44, A1919, A3638 and A1598 lost the pathogenic capability and virulence, however, the virulence of the mutants A1764, A439, A3885, G1183, A3144, A1649 and A2675 increased significantly to the apple fruits compared to the wild isolate "Stj16". The biological study indicated that a Rose Bengal Agar (RBA) medium decreased the mycelium growth, but it can increase the sporulation for most of the isolates. The mutant A4204 does not grow well at pH 4.0 and pH 8.0, and mutant M44 just has the optimum growth at pH 8.0, and a 12 h light and 12 h dark condition stimulates the sporulation for most of the tested mutants, but the A1764 mutant more sporulated at regular dark conditions. All the mutants and "Stj16" grew vigorously at 25 °C-30 °C, for "Stj16", it produced the highest number of conidia at 30 °C compared with the other temperatures. Based on the biological study, we found the best growing and sporulation conditions for all the tested isolates. The information generated in the present study will facilitate molecular research on this devastating fungus.

Abstract The Ebola outbreak in 2014 caused many infections and deaths. Some literature works have proposed some models to study Ebola virus, such as SIR, SIS, SEIR, etc. It is proved that the fractional order model can describe epidemic dynamics better than the integer order model. In this paper, we propose a fractional order Ebola system and analyze the nonnegative solution, the basic reproduction number R 0 $R_{0}$ , and the stabilities of equilibrium points for the system firstly. In many studies, the numerical solutions of some models cannot fit very well with the real data. Thus, to show the dynamics of the Ebola epidemic, the Gorenflo–Mainardi–Moretti–Paradisi scheme (GMMP) is taken to get the numerical solution of the SEIR fractional order Ebola system and the modified grid approximation method (MGAM) is used to acquire the parameters of the SEIR fractional order Ebola system. We consider that the GMMP method may lead to absurd numerical solutions, so its stability and convergence are given. Then, the new fractional orders, parameters, and the root-mean-square relative error g ( U ∗ ) = 0.4146 $g(U^{*})=0.4146$ are obtained. With the new fractional orders and parameters, the numerical solution of the SEIR fractional order Ebola system is closer to the real data than those models in other literature works. Meanwhile, we find that most of the fractional order Ebola systems have the same order. Hence, the fractional order Ebola system with different orders using the Caputo derivatives is also studied. We also adopt the MGAM algorithm to obtain the new orders, parameters, and the root-mean-square relative error which is g ( U ∗ ) = 0.2744 $g(U^{*})=0.2744$ . With the new parameters and orders, the fractional order Ebola systems with different orders fit very well with the real data.

Background: The main cause for low mungbean [Vigna radiata (L.) R. Wilczek] productivity is mungbean yellow mosaic virus (MYMV). Generally, the management of MYMV relies upon frequent insecticide sprays to control its vector (whitefly) and genetic resistance. However, disease forecast models can help to economize the pesticide sprays. Hence current study was designed to identifying environmental factor that promote disease development and developing a disease prediction model. Methods: One hundred and twenty-seven mungbean accessions were planted for two years (2012 and 2013) and infection was dependent on natural inoculum. Weekly and daily data on disease incidence and environmental variables were collected and analyzed using correlation and stepwise regression analysis. Results: Wind velocity and high temperature had a negative relation with disease occurrence during both years, whereas low temperature, rainfall, and relative humidity, had positive relationship based on linear regression. The environmental conditions responsible for the highest disease incidence were, maximum temperature (32–34 °C), relative humidity (72–75 %), minimum temperature (27–29 °C), rainfall (1.8–2.1 mm) and wind velocity (3–4.5 km/hr) during both growing seasons Overall, five environmental variable multiple regression model encompassing relative humidity, wind speed, rainfall, suboptimum temperature, and optimum temperatures accommodate the data rightly explaining 83 % variation in disease outgrowth. Conclusion: The observed MYMV disease occurrence values for most of the mungbean genotypes, and those predicted by the model were very close. This multi-environmental variable model can be utilized to provide early warning forecasts for the management of MYMV in Pakistan.

Dengue virus (DENV) infection is one of the major health issues and a substantial epidemic infectious human disease. More than two billion humans are living in dengue susceptible regions with annual infection mortality rate is about 5%–20%. At initial stages, it is difficult to differentiate dengue virus symptoms with other similar diseases. The main objective of this research is to diagnose dengue virus infection in human blood sera for better treatment and rehabilitation process. A novel and robust approach is proposed based on Raman spectroscopy and deep learning. In this regard, the ResNet101 deep learning model is modified by exploiting transfer learning (TL) concept on Raman spectroscopic data of human blood sera. Sample size was selected using standard statistical tests. The proposed model is evaluated on 2,000 Raman spectra images in which 1,200 are DENV-infected of human blood sera samples, and 800 are healthy ones. It offers 96.0% accuracy on testing data for DENV infection diagnosis. Moreover, the developed approach demonstrated minimum improvement of 6.0% and 7.0% in terms of AUC and Kappa index respectively over the other state-of-the-art techniques. The developed model offers superior performance to capture minute Raman spectral variations due to the better residual learning capability and generalization ability compared to others deep learning models. The developed model revealed that it might be applied for diagnosis of DENV infection to save precious human lives.

A microbiological and sanitation survey of ready-to-eat (RTE) food samples, cutlery, utensils, and hands of food handlers, food preparation surfaces, serving counters, washing areas, and refrigerator handles were conducted. The samples were collected using environmental swabs, and these samples were analyzed using standard plating techniques. Samples were characterized after aerobic plate counts (APC) and isolated for mesophilic aerobic bacteria (MAB), total coliforms, Staphylococcus aureus, Escherichia coli., Salmonella spp., Shigella spp., Pseudomonas spp., Enterobacter spp., Klebsiella spp., and yeast. This study suggested that good-hygiene practices can minimize bacterial counts, thereby decreasing the reservoirs for bacterial contamination. It also improves the hygienic condition of RTE-foods in the cafeteria of Universities.

Different vegetation types, cater to the needs of butterflies at different stages of their life cycle. Some caterpillars are specific in their diet and egg-laying, such as the caterpillar of the Monarch butterfly, which mainly consumes leaves of milkweed and hence prefers laying eggs on this plant (Faldyn et al., 2018). This entomological research was undertaken at protected areas of Pakistan that include Dhirkot Nature Reserve, Pir Chanasi National Park, Banjosa Game Reserve, Pir Lasura National Park and Tolipir National Park. Forty-four different species of butterflies were recorded from the study area. The highest diversity of butterflies was observed from PCNP (34) and least from PLNP (15).

A general investigation of sub-tropical forests, from Pir Chinasi National Park, Tolipir National Park, Dhirkot Nature Reserve and Banjosa Game Reserve was carried out during different months from February 2008 to May 2010. The relative abundance of species was calculated using line transects of 50m. A total of five different species (Abies pindrow. Cedrus deodara, Pinus wallichiana, Pinus roxburgii and Picea smithiana) from the Pinaceae family were recorded. The main reported use of Cedrus deodara and Pinus wallichiana by the local people was for furniture and construction purposes. Pinus wallichiana was observed as the dominant species from all the selected sites.

Rice is one of the most important crops in Pakistan, grown all over the world. Rice production has decreased due to susceptibility to a number of biological and abiotic factors. One of the oldest diseases is bacterial leaf blight of rice. The causative agent of the disease is Xanthomonas oryzae pv. oryzae. In this study, seedlings of four commercially grown rice varieties were sown by following the randomized complete block design (RCBD). Four treatments were used to manage the disease and to promote the plant growth. Correlation and regression analysis was used to study the relation of BLB disease and environmental factors. It was observed that plant height increased by the application of NPK followed by Farm yard manure, boron and leaf manure. Panicle length and weight was maximum in boron treated plants while minimum in FYM. Minimum disease severity was recorded in NPK treatment followed by boron FYM and leaf manure. All the environmental variables showed significantly negative relationship with the development BLB disease. These results would be beneficial for the farming community to devise management options against BLB disease.

Hepatitis is an inflammatory disease of the liver and is considered one of the leading causes of death worldwide. Due to its scavenging activity, Punica granatum may be used for the treatment and prevention of liver diseases. The current study investigated the protective mechanism underlying the effects of pomegranate against a rat model of carbon tetrachloride–induced liver injury. Intraperitoneal injection of CCl4 resulted in liver inflammation, oxidative stress, and accumulation of lipid in hepatocytes. CCl4 induced a downregulation of superoxide dismutase (SOD), glutathione (GSH), and melonaldehyde (MDA). Pomegranate protection was assessed in terms of biochemical parameters, histopathology, and immunohistochemistry. Promegranate administration decreased inflammation, elevated serum enzymes and ROS production, and countered the debilitating effects caused by CCl4. In addition, CCl4-induced histological changes were absent in the crude pomegranate extract group, which also enhanced the scavenging activity of reactive oxygen species by enhancing the antioxidant defense mechanism as confirmed by detecting MDA, SOD, and GSH expressions. The migration of CD68+ macrophages was halted at the injured area of the central vein and the number of macrophages was reduced to the normal control by the crude extract compared to the positive control silymarin group. Likewise, protective effects of ethylacetate and the aqueous fraction of the crude extract were also observed. However, the butanol and n-hexane fractions displayed increased levels of ALT, AST, and ALP as compared to silymarin. About 25% damage to hepatocytes was observed in the butanol and n-hexane group by histopathological examination, which is a little better compared to the CCl4-treated group. The crude extract and its ethyl acetate and aqueous fractions may be accountable for the hepatoprotective potential of Punica granatum, which was further confirmed by in vivo experiments. Together, these findings confirm that pomegranate exerts hepatoprotective activity against CCl4-induced oxidative stress and liver damage.

The aim of present studyis to evaluate and assess the impact of built-up areas on development of the urban heat island (UHI).The study mainly focused on Lahore,which is one of the mega cities of Pakistan. In terms of population size,Lahore is the second largest city of Pakistan with 11.13 million inhabitants. The geospatial techniques (Remote Sensing and Geographical Information System) along with statistical applications were applied to find out the Land Cover Land Uses changes and consequent development of builtup areas overthe period of 2000 and 2015. To study the UHI, the meteorological data of each 30 minutes for 36 days starting from 30thJune 2015 to 4thAugust 2015 were collected through direct on site observation by using digital weather station. The results of UHI were cross checked by obtaining land surface temperature by using thermal infrared (TIR) band 6 of the Landsat-7 TM. The results show that the LCLU and built environment have direct impact on development of UHI. The areas where there was more vegetation cover had less temperature while in urban areas, the temperature was measured higher. Over the period of 36 days, the average UHI remained 5.5°C and the highest intensity of UHI was observed as 8.3°C thus augmented research rationale. The study suggests establishment of a thick network of automatic weather stations in Lahore to gauge the urban heat island intensity and to plant indigenous trees on vacant swaths and develop urban forest to mitigate city’s rising temperature.

Present study examines the trends of extreme daily temperature and rainfall indices in some selected meteorological stations/districts of the Punjab. Due to paucity of data only six weather stations wereselected from the whole Punjab, having data of 33 years for temperature and precipitation on daily basis. A set of 14 indices (recommended by climate ET) were used to calculate the trends over a period of 32 years (1985–2017) by using RClimDex (1.0) software package. These results showed that the number of tropical nights (TR20) and warm nights (TN90p) has been increasing in selected weather stations/districts and number for cool nights (TN10p) has been falling. Other temperature related indices trends such as, summer days, warms days, warm spell duration indicator (WSDI) and cool spell duration (CSDI) shows a mix pattern. The precipitation indices like SDII, RX1day, R10mm and PRCPTOT showed an increasing trend in some selected stations. Most of the trends were not significant at level of 0.05 % while maximum day temperature increase has been observed at five out of six selected stations. Similarly, an average increase in precipitation in the vicinity of 3 mm per decade has been noted. The annual total rainfall and number of heavy rainfall days has also increased by 18 mm and 8.4 mm respectively during each decade. The analysis identified and highlighted a slight change which was not temporally and spatially rational. However, there is need to more and adequate yearly data of different weather stations across the Punjab to identify the ongoing apparent and impeccable changes in climate of the Punjab province.

This paper proposes the multipurpose and wirelessly controlled UGV which can move across the surface, detect objects and classify them. It can also monitor and inspect object under interest if detects any undesirable condition then inform corresponding authority for further immediate actions. The Mini Rover-Unmanned Ground Vehicle (UGV) is any piece of mechanized equipment that moves across the surface of the ground and serves as a means for carrying or transporting something, but explicitly does not carry a human being. It will be able to go to places that human cannot reach for the sack of exploration and observation. The UGV operates without an onboard human presence. UGVs are used for the purpose of search and rescue, security and surveillance, terrain and forest monitoring because it is inconvenient, inefficient, dangerous, and sometimes impossible to have a human operator present in such environments. Major problems faced by UGV in natural terrain environment are reliable sensing, route finding, and object detection and identification. We combine a set of sensors and image processing techniques to counter these problems by getting a more extensive perception of the environment.

Autophagy plays an intricate role in paradigmatic human pathologies such as cancer, and neurodegenerative, cardiovascular, and autoimmune disorders. Autophagy regulation is performed by a set of autophagy-related (ATG) genes, first recognized in yeast genome and subsequently identified in other species, including humans. Several other genes have been identified to be involved in the process of autophagy either directly or indirectly. Studying the codon usage bias (CUB) of genes is crucial for understanding their genome biology and molecular evolution. Here, we examined the usage pattern of nucleotide and synonymous codons and the influence of evolutionary forces in genes involved in human autophagy. The coding sequences (CDS) of the protein coding human autophagy genes were retrieved from the NCBI nucleotide database and analyzed using various web tools and software to understand their nucleotide composition and codon usage pattern. The effective number of codons (ENC) in all genes involved in human autophagy ranges between 33.26 and 54.6 with a mean value of 45.05, indicating an overall low CUB. The nucleotide composition analysis of the autophagy genes revealed that the genes were marginally rich in GC content that significantly influenced the codon usage pattern. The relative synonymous codon usage (RSCU) revealed 3 over-represented and 10 under-represented codons. Both natural selection and mutational pressure were the key forces influencing the codon usage pattern of the genes involved in human autophagy.

Tobacco cutworm, Spodoptera litura Feb. (Lepidoptera; Noctuidae) is a notorious cosmopolitan pest of numerous crops. Frequent evolution of insecticide resistance and polyphagous nature favors the survival of this voracious pest. Nanotechnology offers an alternative technique to overcome the limitations of existing pest management strategies. In the present study, the silver nanoparticles were synthesized from Ocimum basilicum leaf extract and UV-spectra at 464.17 nm confirmed their synthesis while crystalline nature of nanoparticles was evaluated by X-rays diffraction (XRD) pattern and scanning electron microscopy (SEM) revealed their octagonal to spherical shape. Insecticidal potential of O. basilicum synthesized silver nanoparticles (ObAgNPs) was evaluated in comparison with some synthetic insecticides owning different mode of actions, including Coragen®, Proclaim®, Tracer® and Talstar® against S. litura. Probit analysis of 2nd, 3rd, 4th and 5th instars of S. litura showed that lethal concentrations (LCs) of tested nanoparticles and pesticides were positively correlated with older instars. All values of LC50, LC90 and LC95 were statistically different from each other with maximum on the 4th instar and minimum on 2nd instar of S. litura. Tukey’s HSD test revealed that ObAgNPs caused maximum mortality (21.67–96.67%) in 2nd instar larvae at the rate of 100–1500 mg/L followed by Coragen® (18.33–91.67%), Proclaim® (13.33–78.33%) and Talstar® (13.33–68.33%), while Tracer indicated the lowest larval mortality (11.67–66.67%) at the rate of 60–120 mg/L and a similar trend was assessed for all the successive instars of S. litura. Higher activity of carboxyl esterase and glutathione-s-transferases confirmed the development of insecticide resistance against the synthetic chemicals. Conclusively, ObAgNPs were found to be eco-friendly but the most effective biogenic compounds for the suppression of S. litura population as compared to the selected synthetic chemicals which may be hazardous for the environment as well as human health. This study will assist the pesticide industries to re-standardize the dose rates against Spodoptera litura.

Bots are created to use the resources maliciously on World Wide Web. The misuse of the resources could be prevented by employing CAPTCHAs. Several types of CAPTCHAs are being used against the bots (robot) attacks but text-based CAPTCHA type is the most popular being very secured and easy to use. Latin language based text CAPTCHAs can be found ubiquitously on Internet but English text based CAPTCHAs are already decoded by many researchers. Thus, a novel Sindhi language based text CAPTCHA was proposed for regional websites where Arabic style script was utilized. This scheme offered two fold benefits: first, the proposed scheme could easily be understood by averagely literate person; second, this scheme paved a way for Arabic style OCR developers to understand Sindhi language specific features and facilitate Sindhi text recognition in future. A survey was also conducted to analyze the usability and strength of proposed CAPTCHA.

[This corrects the article DOI: 10.1371/journal.pone.0244059.].

Crop leaf disease management and control pose significant impact on enhancement in yield and quality to fulfill consumer needs. For smart agriculture, an intelligent leaf disease identification system is inevitable for efficient crop health monitoring. In this view, a novel approach is proposed for crop disease identification using feature fusion and PCA-LDA classification (FF-PCA-LDA). Handcrafted hybrid and deep features are extracted from RGB images. TL-ResNet50 is used to extract the deep features. Fused feature vector is obtained by combining handcrafted hybrid and deep features. After fusing the image features, PCA is employed to select most discriminant features for LDA model development. Potato crop leaf disease identification is used as a case study for the validation of the approach. The developed system is experimentally validated on a potato crop leaf benchmark dataset. It offers high accuracy of 98.20% on an unseen dataset which was not used during the model training process. Performance comparison of the proposed technique with other approaches shows its superiority. Owing to the better discrimination and learning ability, the proposed approach overcomes the leaf segmentation step. The developed approach may be used as an automated tool for crop monitoring, management control, and can be extended for other crop types.

Background The radial forearm free flap (RFFF) has remained a leading choice of many plastic surgeons as a fasciocutaneous flap due to its versatility, pedicle length, and simple elevation technique. However, donor site morbidity has led many reconstructive surgeons to limit their use of the RFFF and to use other flaps instead. We propose that using a narrow RFFF (nRFFF) decreases the aesthetic and functional morbidity of the donor site.

Background: The Pakistani Salt Range has a rich floral diversity including Withania coagulans from the Solanaceae family. Methods: The crude methanolic extracts of the root, leaf, leaf stalk, and fruit of this plant were screened for their cytotoxic activity against human (HeLa, MCF-7, RD) and rat (RG2 and INS-1) cancer cell lines at 20 μg/mL and compared to methotrexate. The IC50 values indicated that leaf stalk and fruit extracts exert an 80% or higher cytotoxic activity against all cell lines at 24 hours. Results: The leaf stalk extract showed the highest cytotoxic efficacy against all tested cell lines, with IC50 values ranging from 0.96 ± 0.01 μg/mL to 4.73 ± 0.05 μg/mL followed by the fruit extract with IC50 values of 0.69 ± 0.01–6.69 ± 0.06 μg/mL after 48–72 hours incubation. The leaf stalk and seed extracts were analyzed for polyphenols and flavonoids using RP-HPLC. The total flavonoid content (TFC) was calculated for all tested samples, and the highest TFC was recorded for the root extract (394.34 ± 1.26 μg/g). The total phenolic content (TPC) was found in the seed extract (307.86 ± 9.42 μg/g) of W. coagulans. The highest contents of myricetin (358.46 ± 2.91 μg/g) were noted in the leaf extract, and highest quercetin was recorded in the seed extract (21.43 ± 0.13 μg/g). The highest gallic acid concentration (83.62 ± 0.71 μg/g) was recorded in leaf stalk extract and p-hydroxybenzoic acid in the seed extract (157.46 ± 1.43 μg/g). Conclusion: The present study gives a scientific insight and comparative analysis of various plant parts in this medicinally important plant species from the Salt Range of Pakistan against both human and rat cancer cells. Keywords: Anticancer, Presto Blue cell metabolic assay, Total phenolic contents, Total flavonoid contents

This paper researches the issue of the finite-time combination-combination (C-C) synchronization (FTCCS) of fractional order (FO) chaotic systems under multiple stochastic disturbances (SD) utilizing the nonsingular terminal sliding mode control (NTSMC) technique. The systems we considered have different characteristics of the structures and the parameters are unknown. The stochastic disturbances are considered parameter uncertainties, nonlinear uncertainties and external disturbances. The bounds of the uncertainties and disturbances are unknown. Firstly, we are going to put forward a new FO sliding surface in terms of fractional calculus. Secondly, some suitable adaptive control laws (ACL) are found to assess the unknown parameters and examine the upper bound of stochastic disturbances. Finally, combining the finite-time Lyapunov stability theory and the sliding mode control (SMC) technique, we propose a fractional-order adaptive combination controller that can achieve the finite-time synchronization of drive-response (D-R) systems. In this paper, some of the synchronization methods, such as chaos control, complete synchronization, projection synchronization, anti-synchronization, and so forth, have become special cases of combination-combination synchronization. Examples are presented to verify the usefulness and validity of the proposed scheme via MATLAB.

License plate localization is the process of finding the license plate area and drawing a bounding box around it, while recognition is the process of identifying the text within the bounding box. The current state-of-the-art license plate localization and recognition approaches require license plates of standard size, style, fonts, and colors. Unfortunately, in Pakistan, license plates are non-standard and vary in terms of the characteristics mentioned above. This paper presents a deep-learning-based approach to localize and recognize Pakistani license plates with non-uniform and non-standardized sizes, fonts, and styles. We developed a new Pakistani license plate dataset (PLPD) to train and evaluate the proposed model. We conducted extensive experiments to compare the accuracy of the proposed approach with existing techniques. The results show that the proposed method outperformed the other methods to localize and recognize non-standard license plates.

In the last couple of years, energy management in the building environment has been a topic of interest to the research community. A number of renowned methods exist in the literature for energy management in buildings, but the trade-off between occupants comfort level and energy consumption is still a major challenge and needs more attention. In this paper, we propose a power control model for comfort and energy saving, using a fuzzy controller and genetic programming (GP). Our focus is to increase the occupants’ comfort index and to minimize the energy consumption simultaneously. First, we implemented a Genetic Algorithm (GA) to optimize the environmental parameters. Second, we control the environment using fuzzy logic and third, we predict the consumed power using GP. The environmental and comfort parameters considered are temperature, illumination and air quality. At the end of the work we compare the power consumption results with and without prediction. The results confirmed the effectiveness of the proposed technique in getting the solution for the above mentioned problem.

This article studies the propagation of rogue waves with a nonautonomous NLSE in the presence of external potential. This model is considered to be an important model for many physical phenomena in quantum mechanics and optical fiber. The obtained waves are of first and second order and are investigated using similarity transformation. The nonlinear dynamic behavior of these waves is also demonstrated with different parameter values for the magnetic and gravity fields. The results show the influence of these fields over density, width, and peak heights. Moreover, the modulation instability is also discussed.

Numerous cropping systems of the world are experiencing the emergence of new weed species in response to conservation agriculture. Conyza stricta Willd. is being a newly emerging weed of barley-based cropping systems in response to conservational tillage practices. Seed germination ecology of four populations (irrigated, rainfed, abandoned and ruderal habitats) was studied in laboratory and greenhouse experiments. The presence/absence of seed dormancy was inferred first, which indicated seeds were non-dormant. Seed germination was then recorded under various photoperiods, constant and alternating day/night temperatures, and pH, salinity and osmotic potential levels. Seedling emergence was observed from various seed burial depths. Seeds of all populations proved photoblastic and required 12-hour light/dark period for germination. Seeds of all populations germinated under 5-30°C constant temperature; however, peak germination was recorded under 17.22-18.11°C. Nonetheless, the highest germination was noted under 20/15°C alternating day/night temperature. Ruderal and irrigated populations better tolerated salinity and germinated under 0-500 mM salinity. Similarly, rainfed population proved more tolerant to osmotic potential than other populations. Seeds of all populations required neutral pH for the highest germination, whereas decline was noted in germination under basic and alkaline pH. Seedling emergence was retarded for seeds buried >2 cm depth and no emergence was recorded from >4 cm depth. These results add valuable information towards our understanding of seed germination ecology of C. stricta. Seed germination ability of different populations under diverse environmental conditions suspects that the species can present severe challenges in future if not managed. Deep seed burial along with effective management of the emerging seedlings seems a pragmatic option to manage the species in cultivated fields. However, immediate management strategies are needed for rest of the habitats.

The incidence, distribution, and variation of simple sequence repeats (SSRs) in viruses is instrumental in understanding the functional and evolutionary aspects of repeat sequences. Full-length genome sequences retrieved from NCBI were used for extraction and analysis of repeat sequences using IMEx software. We have also developed two MATLAB-based tools for extraction of gene locations from GenBank in tabular format and simulation of this data with SSR incidence data. Present study encompassing 147 Mycobacteriophage genomes revealed 25,284 SSRs and 1,127 compound SSRs (cSSRs) through IMEx. Mono- to hexa-nucleotide motifs were present. The SSR count per genome ranged from 78 (M100) to 342 (M58) while cSSRs incidence ranged from 1 (M138) to 17 (M28, M73). Though cSSRs were present in all the genomes, their frequency and SSR to cSSR conversion percentage varied from 1.08 (M138 with 93 SSRs) to 8.33 (M116 with 96 SSRs). In terms of localization, the SSRs were predominantly localized to coding regions (∼78%). Interestingly, genomes of around 50 kb contained a similar number of SSRs/cSSRs to that in a 110 kb genome, suggesting functional relevance for SSRs which was substantiated by variation in motif constitution between species with different host range. The three species with broad host range (M97, M100, M116) have around 90% of their mono-nucleotide repeat motifs composed of G or C and only M16 has both A and T mononucleotide motifs. Around 20% of the di-nucleotide repeat motifs in the genomes exhibiting a broad host range were CT/TC, which were either absent or represented to a much lesser extent in the other genomes.

Objective: The aim of the study is to find out amount of physical stress among cardiovascular disease (CVD) patients and its relation with hypertension. Background: Physical stress is defined as a pressure – force and strain a state of physical mental tension. Stress is among the mental factors that has for some time been recorded among the potential. Furthermore, essential hazard variables of hypertension and coronary illness. Methodology: A cross-sectional study was conducted in the patients of department of Cardiology at tertiary hospitals, Karachi, from January 2014 to December 2014. Sadaf stress scale (SSS) 2.0 was used to find out the physical stress. Results: It showed physical stress among CVD patients about n=39 (43.3%) have moderate physical stress. which was decreased over time after 5 year of illness as compared to the patient who have disease for less than 5 years. While systolic blood pressure among subjects with severe physical stress showed an average systolic B.P. of 147mmhg, moderate have 146mmhg and patients with mild physical stress have 135mmhg. Conclusion: This report concluded moderate physical stress among CVD patients which was decrease over time due different coping mechanism and blood pressures are directly related to severity of physical stress mainly systolic which lead to hypertension.