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Little is known regarding effects of azo-dyes on soil organic matter cycling in soil. Therefore, this lab study was carried out in Government College University Faisalabad to understand effects of varying concentrations (100, 200, 400 mg kg-1 ) of reactive black (RB5), direct red (DR) and, acid yellow (AY) on soil organic matter cycling in a sandy loam, a clay loam, and a loam. Soils were mixed with the aforementioned dyes and incubated in lab for 636 hrs. Results revealed that DR induced change of -52 to +53%, -8 to -58%, and -50 to +8% on soil respiration rate in sandy loam, loam and clay loam soils respectively in first 160 h of incubation. RB5 induced a change of -52 to +49%, -38 to +9%, and -67 to -15% whereas, the AY induced a change of -54 to +36%, -34 to +24%, and -75 to -6% in respiration rate in sandy loam, loam and clay loam soils respectively during the same incubation time. The microbial biomass C (MBC) did not show any significant change in response to any azo dye in loam soil. Metabolic quotient indicated that the clay loam soil experienced the highest toxicity in response to DR and RB5 among the three soils. Overall, our study shows that not all the dyes are toxic to SOM cycling and that is dependent on the type of the azo dye as well as the intrinsic characteristics of the soils. [ABSTRACT FROM AUTHOR]

The current study was carried out in order to assess the effects of micronutrients (B, Fe, Zn) on the yield and quality of Kinnow (Citrus reticulata Blanco). Citrus is an important fruit crop of Pakistan and micronutrients are not only important for yield and quality of citrus but also for the human health. This experiment consisted of different soil treatments and foliar applications of B, Zn and Fe either alone or in combinations. The results revealed that the highest concentrations of these three micronutrients in soil were found where 20 g B, 40 g Zn and 100 g Fe were applied per plant, respectively through soil application. The highest concentrations of these micronutrients in the leaves of Kinnow were found in the individual treatments of foliar spray of 0.03 % B, 0.1 % Zn and 0.25 % Fe, respectively, followed by the combined application of B, Zn and Fe with concentration of 0.03%, 0.1% and 0.25%. Soil that had combined treatment, B: 10 g plant-1, Zn: 20 g plant-1, Fe: 50 g plant-1 gave the highest yield of fruit and juice content. Fruit drop was the highest in control and the lowest for 20 g B soil application. Total sugars, reducing sugars and TSS were the highest for 40 g Zn as soil application, followed by the combined treatment of B:10 g plant-1, Zn:20 g plant-1, Fe:50 g plant-1 . The non-reducing sugars were the highest in the case of combined soil application of B, Zn and Fe. It is concluded that the micronutrients application is a suitable approach for increasing the quality and yield of Kinnow [ABSTRACT FROM AUTHOR]

OBJECTIVE: To determine the quantitative comparison of handgrip strength between cardiac patients and age matched healthy controls using a handheld dynamometer. METHODS: This quantitative comparison cross-sectional study was th conducted at University of Lahore Teaching Hospital, Lahore from 17, th October 2017 to 5 February 2018. Twenty cardiac and twenty age matched healthy participants were selected using consecutive (non-probability) sampling technique. After approval from ethical committee, data was collected using questionnaire. Measurements were taken of grip strength of both hands by using Jammer Dynamometer. This method was repeated three times in order to obtain mean value of both hands. RESULTS: In this study 40 subjects were studied with mean age of the participants as 62.08±7.63years. Among them 23(57.5%) were male and 17(42.5%) were female. Mean age of males were 65±7.37years whereas mean age of females were 64.11±7.75years. Out of twenty cardiac patients, 12(60%) male and 5 (25%) female were suffering from myocardial infarction, 3(15%) female had angina. Twenty participants of age-matched healthy individual group included 11 (55%) males and 9 (45%) females. In quantitative comparison of the dominant handgrip strength of cardiac patients (54.28 ± 27.75) and age matched healthy control (74.78±30.33) there was noteworthy difference in mean values of both groups with significant p-value of 0.032 whereas in the strength of non-dominant hand grip in cardiac patients (54.11±26.46) and age matched healthy control (71.03±29.25), no significant difference was recorded. CONCLUSION: Grip strength of dominant hand is less in cardiac patients as compared to healthy normal individual with significant relationship whereas there is no significant difference among non-dominant hand strength in both groups. [ABSTRACT FROM AUTHOR]

OBJECTIVE: To determine the quantitative comparison of handgrip strength between cardiac patients and age matched healthy controls using a handheld dynamometer. METHODS: This quantitative comparison cross-sectional study was th conducted at University of Lahore Teaching Hospital, Lahore from 17th, th October 2017 to 5th February 2018. Twenty cardiac and twenty age matched healthy participants were selected using consecutive (non-probability) sampling technique. After approval from ethical committee, data was collected using questionnaire. Measurements were taken of grip strength of both hands by using Jammer Dynamometer. This method was repeated three times in order to obtain mean value of both hands. RESULTS: In this study 40 subjects were studied with mean age of the participants as 62.08±7.63years. Among them 23(57.5%) were male and 17(42.5%) were female. Mean age of males were 65±7.37years whereas mean age of females were 64.11±7.75years. Out of twenty cardiac patients, 12(60%) male and 5 (25%) female were suffering from myocardial infarction, 3(15%) female had angina. Twenty participants of age-matched healthy individual group included 11 (55%) males and 9 (45%) females. In quantitative comparison of the dominant handgrip strength of cardiac patients (54.28 ± 27.75) and age matched healthy control (74.78±30.33) there was noteworthy difference in mean values of both groups with significant p-value of 0.032 whereas in the strength of non-dominant hand grip in cardiac patients (54.11±26.46) and age matched healthy control (71.03±29.25), no significant difference was recorded. CONCLUSION: Grip strength of dominant hand is less in cardiac patients as compared to healthy normal individual with significant relationship whereas there is no significant difference among non-dominant hand strength in both groups. [ABSTRACT FROM AUTHOR]

The pomegranate (Punica granatum L.) is popular for its high medicinal value. It is a common table fruit and whole fruit contains important vitamins, minerals and antioxidants. Four pomegranate varieties (Pearl, Golden, Sultan, and Qandhari) were analyzed in the Biochemistry laboratory of Post Harvest Research Centre, Ayub Agricultural Research Institute (AARI), Faisalabad Pakistan during the year 2021-2022. The results showed that juice carried a remarkably higher value of TSS (total soluble solids) ranging from 12.4% (Pearl) to 17.2 % (Sultan), total invert sugars were minimum (11.8%) in Golden and maximum (14.3%) in Sultan. The value of vitamin-C varies from 10.6 mg/100 mL (Qandhari) to 11.5 mg/100 mL (Pearl) and acidity ranges from 0.8% (Sultan) to 1.9% (Pearl). Sultan showed a higher value for total phenols and antioxidants (1111µg GAE L-1 and 43.5% DPPH inhibition respectively) and lowest in Pearl (1022µg GAE L-1 and 27.7% respectively). Peel powder of different varieties carry a different percentage of crude fat and crude fiber but Sultan is statistically at par with Qandhari but significantly higher than pearl. Ash/mineral matter was significantly different in different varieties. Sultan was better than other varieties having ash contents of 3.67%. The lowest value was observed in Golden (2.7%). Keeping in view the current results Sultan was better than Pearl and Golden and comparable to Qandhari. [ABSTRACT FROM AUTHOR]

The Biochemistry Section at the Ayub Agricultural Research Institute (AARI) in Faisalabad served as the research hub for our study throughout 2020-21. We delved into the antioxidants and biochemical parameters found in an array of fruits including peach (Prunus persica), grapes (Vitis vinifera), grapefruit (Citrus paradisi), lychee (Litchi chinensis), fig (Ficus carica), plum (Prunus domestica), sweet lime (Citrus limetta), Kuranda (Carissa carandas), kiwi (Actinidia deliciosa), and pear (Pyrus communis). These fruits offer vital nutrition like Vitamin C, ranging from 2.49 in fig to 48.7 in sweet lime, mineral matter is minimum (0.34%) in pear and maximum 6.19% in Lychee, crude fiber was highest (7.26%) in kuranda and lowest (0.82%) in Grapefruit, crude fat was less than 1 in all the fruits except kuranda having crude fat 1.66%. crude protein was also less than one in most of the fruits under study except Fig (2.05%), Plum (3.33%) and Kuranda (1.16%). Total antioxidants were higher in Peach (94.1%) followed by Plum (88.5%), Sweet lime (84.6%) and Fig (83.9%) while lowest value was observed in Kuranda (10.4%). Their adequate consumption not only fortifies the immune system but also serves as a shield against afflictions. Phenols packed abundantly within fruits, stand out as some of the most nutrient-rich components. Total phenols were ranging from 13.8 µg GAE/mL (Grapefruit) to 1182.5 µg GAE/mL (Kuranda). Total sugar lies between 6% (Plum) to 14.3% (Luchee). This paper delves deep into an exhaustive analysis of bioactive compounds, exploring their antioxidant capacities within the most widely cultivated fruits. Our exploration identifies that all the fruits are useful due to one or more nutritious elements. Our findings conclusively advocate the regular consumption of fruits, emphasizing their pivotal role in fostering nutrition and safeguarding against diseases. [ABSTRACT FROM AUTHOR]

With the global spread of COVID-19, the governments advised the public for adopting safety precautions to limit its spread. The virus spreads from people, contaminated places, and nozzle droplets that necessitate strict precautionary measures. Consequently, different safety precautions have been implemented to fight COVID-19 such as wearing a facemask, restriction of social gatherings, keeping 6 feet distance, etc. Despite the warnings, highlighted need for such measures, and the increasing severity of the pandemic situation, the expected number of people adopting these precautions is low. This study aims at assessing and understanding the public perception of COVID-19 safety precautions, especially the use of facemask. A unified framework of sentiment lexicon with the proposed ensemble EB-DT is devised to analyze sentiments regarding safety precautions. Extensive experiments are performed with a large dataset collected from Twitter. In addition, the factors leading to a negative perception of safety precautions are analyzed by performing topic analysis using the Latent Dirichlet allocation algorithm. The experimental results reveal that 12% of the tweets correspond to negative sentiments towards facemask precaution mainly by its discomfort. Analysis of change in peoples' sentiment over time indicates a gradual increase in the positive sentiments regarding COVID-19 restrictions. [ABSTRACT FROM AUTHOR]

Currently, the high complexity of video contents has posed the following major challenges for fast retrieval: (1) efficient similarity measurements, and (2) efficient indexing on the compact representations. A video-retrieval strategy based on fuzzy c-means (FCM) is presented for querying by example. Initially, the query video is segmented and represented by a set of shots, each shot can be represented by a key frame, and then we used video processing techniques to find visual cues to represent the key frame. Next, because the FCM algorithm is sensitive to the initializations, here we initialized the cluster center by the shots of query video so that users could achieve appropriate convergence. After an FCM cluster was initialized by the query video, each shot of query video was considered a benchmark point in the aforesaid cluster, and each shot in the database possessed a class label. The similarity between the shots in the database with the same class label and benchmark point can be transformed into the distance between them. Finally, the similarity between the query video and the video in database was transformed into the number of similar shots. Our experimental results demonstrated the performance of this proposed approach. [ABSTRACT FROM AUTHOR]

The experiment was conducted at Biochemistry Section, Ayub Agricultural Research Institute, Faisalabad Pakistan, during the year 2017-18 to assess the total phenols and antioxidants potential of mango, grapes, banana, guava, mulberry, strawberry, loquat, melon, apricot and phalsa. Fruits samples were obtained from the market of Faisalabad Pakistan, washed, dry at room temperature, extracted their juice/pulp. Thejuice was stored at 4 °C for further analysis. Juice samples were processed for Vitamin-C, pH, TSS, total phenolics and total antioxidant capacity. The results showed that among all the ten fruits vitamin C was higher in mango (24.33 mg/100 mL) followed by phalsa (19.74 mg/100 mL) and Grapes (11.25 mg/100 mL), whereas lower value was observed in melon (3.3 mg/100 mL) and loquat (3.4 mg/100 mL). Vitamin C for other fruits lies between these. Highly acidic pH of fresh juices of all the fruits was observed except in melon (5.82) and guava (5.38) which is less acidic. Percentage of TSS was higher in phalsa, mulberry and mangoes (13.8, 13.5 and 13.9% respectively) and lesser in melon (5.6%). Antioxidant capacity (% DPPH reduction) was found higher in grapes (91.9%) and mango (91.2%) which was statistically at par with melon (90.9%), while lesser value was observed in mulberry (51.6%). Total phenolics were significantly higher in grapes (1266.4 pg GAE/mL), whereas minimum phenolic contents were found in melon (4.1 pg GAE/mL). Therefore, it was concluded that grapes are more nutritious and healthy fruit than other. [ABSTRACT FROM AUTHOR]

• Explore qualitative aspects of citations to measure the influence of a research article. • Apply a feature representation technique in combination with machine learning models to find the sentiment of citation. • Determine the sentiment of citation instances into positive, negative, or neutral. • Analyze the efficacy of SMOTE in balancing the citation sentiment dataset. Ascertaining the impact of research is significant for the research community and academia of all disciplines. The only prevalent measure associated with the quantification of research quality is the citation-count. Although a number of citations play a significant role in academic research, sometimes citations can be biased or made to discuss only the weaknesses and shortcomings of the research. By considering the sentiment of citations and recognizing patterns in text can aid in understanding the opinion of the peer research community and will also help in quantifying the quality of research articles. Efficient feature representation combined with machine learning classifiers has yielded significant improvement in text classification. However, the effectiveness of such combinations has not been analyzed for citation sentiment analysis. This study aims to investigate pattern recognition using machine learning models in combination with frequency-based and prediction-based feature representation techniques with and without using Synthetic Minority Oversampling Technique (SMOTE) on publicly available citation sentiment dataset. Sentiment of citation instances are classified into positive, negative or neutral. Results indicate that the Extra tree classifier in combination with Term Frequency-Inverse Document Frequency achieved 98.26% accuracy on the SMOTE-balanced dataset. [ABSTRACT FROM AUTHOR]

A field experiment was conducted to assess the quality of carrot variety T-29 as affected by the application of potassium fertilizer. Potassium was applied @ 0, 40, 60, 80, 100 and 120 kg/ha and carrot was sown during the month of November of every year. The experiment was continued for consecutive three years i.e. 2016-17, 2017-18 and 2018-19 at research area of Biochemistry Section, Ayub Agricultural Research Institute, Pakistan. Yield data were collected and quality parameters pulp, juice, TSS, vitamin C, dry matter, total sugars and reducing sugars were determined. Results revealed that the application of K enhanced the yield and quality parameters. Root yield in various treatments ranged from 20.6 to 30.8 in 2017, 18.0 to 25.8 in 2018 and 17.5 to 27.8 t/ha in 2019, minimum in control and maximum at treatment where K was applied @ 120 kg/ha. Quality parameters like pulp, juice, mineral matter and vitamin-C did not affect significantly by the application of K while the total sugars were increased from 4.0 to 5.6, 4.7 to 5.5 and 5.5 to 6.8% (Minimum in control and maximum with 120 kg/ha K application) during the years 2016-17, 2017-18 and 2018-19, respectively. Maximum antioxidant potential i.e. 75.2, 80.13 and 78.6 was found with potassium application of 120 kg/ha during all years. Pro vitamin A contents (3782 and 3706 μg/100g) were analyzed during 2018 and 2019, respectively where 100 kg/ha potassium was applied. In short, potassium application could be effective for carrot optimum yield and quality enhancement. [ABSTRACT FROM AUTHOR]

The significance of root exudates has long been under estimated, presumably of being concealed in nature. Plant growth promoting rhizobacteria (PGPR) and compost inhabiting bacteria (CIB) interact with plant to regulate root exudation. Present study was conducted at Biochemistry Section, Ayub Agricultural Research Institute, Faisalabad, Pakistan during the year 2018 to check antifungal effect of PGPR and CIB tested against fungal pathogen, (Fusarium oxysporum) with maize crop. Root exudates were collected and analyzed by high performance laquid chromatography (HPLC) to get an insight of their chemical composition. Our results indicated that conidial germination of pathogen was significantly decreased while bacterial population enhanced by exudates of those plant roots which were treated with bacterial consortium. Analysis of root exudates revealed that composition of root exudates of co-inoculated plants, differ not only from the exudates of pathogen free plants but also from the un-inoculated controls referring to only pathogen inoculated plants. Salicylic acid (upto 83%), chlorogenic acid (upto 46%) and caffeic acid (upto 61%), along with higher quantities of malliec acid (upto 24%) were found in exudation of bacterial treated plants. The increase in concentration of specific secondary metabolites might have a role in inducing systemic resistance in the maize against seedling blight (Fusarium oxysporum). In conclusion, this study illustrates the disease resistance mechanism on the basis of plant-microbe communication and helps to devise suitable strategies against fusarium-mediated blight of maize plants. [ABSTRACT FROM AUTHOR]

Regular inspection of railway track health is crucial for maintaining safe and reliable train operations. Factors, such as cracks, ballast issues, rail discontinuity, loose nuts and bolts, burnt wheels, superelevation, and misalignment developed on the rails due to non-maintenance, pre-emptive investigations and delayed detection, pose a grave danger and threats to the safe operation of rail transport. The traditional procedure of manually inspecting the rail track using a railway cart is both inefficient and prone to human error and biases. In a country like Pakistan where train accidents have taken many lives, it is not unusual to automate such approaches to avoid such accidents and save countless lives. This study aims at enhancing the traditional railway cart system to address these issues by introducing an automatic railway track fault detection system using acoustic analysis. In this regard, this study makes two important contributions: data collection on Pakistan railway tracks using acoustic signals and the application of various classification techniques to the collected data. Initially, three types of tracks are considered, including normal track, wheel burnt and superelevation, due to their common occurrence. Several well-known machine learning algorithms are applied such as support vector machines, logistic regression, random forest and decision tree classifier, in addition to deep learning models like multilayer perceptron and convolutional neural networks. Results suggest that acoustic data can help determine the track faults successfully. Results indicate that the best results are obtained by RF and DT with an accuracy of 97%. [ABSTRACT FROM AUTHOR]