Land cover changes and carbon dynamics in Central India's dry tropical forests: A 25-year assessment and nature-based eco-restoration approaches.

Anthropogenic land use and land cover changes are major drivers of environmental degradation and declining soil health across heterogeneous landscapes in Central India. To examines the land cover changes and spatio-temporal variations in forest carbon stock and soil organic carbon (SOC) over the past 25 years in central India. Geospatial techniques, coupled with ground measurements were employed to detect changes in land cover, carbon stocks in vegetation, and soil carbon in various vegetation types. The results indicate that forested areas have decreased, while agriculture and habitation have expanded between 1997 and 2022. Vegetation C stocks varied significantly (P < 0.05) from 39.42 to 139.95 Mg ha-1 and the SOC varied from 7.02 to 17.98 Mg ha-1 under different soil profiles across vegetation types, which decreased with soil depth, while the pH and bulk density increased. The maximum bulk density in the soil was found at a depth of 40-60 cm (lower profile) in Bamboo Brake, while the minimum was observed under Dense Mixed Forest at a depth of 0-20 cm (top profile). The topsoil profile contributed 33.6%-39%, the middle profile (20-40 cm) was 33.6%-34.4%, and the lower profile was 26.5%-30.8% of soil organic carbon. The study site has experienced rapid carbon losses due to changes in land cover, such as illegal expansion of agriculture, encroachments into forest fringes, and activities like selective logging and overgrazing, which have degraded dense forests. The ecological engineering of degraded ecosystems poses a great challenge and application of complex biological, mechanical and engineering measures is highly cumbersome, expensive, uneconomical and practically not feasible for upscaling. Nevertheless, proposed nature-based solutions mimic natural reparation and processes provide sustainable interventions for the reclamation of ruined landscapes besides improving ecological integrity and rendering many co-benefits to ecosystems and human societies.

Integrons and multidrug resistance across phylogenetic groups of clinical isolates of Escherichia coli.

Objective: This study was aimed to investigate the multidrug resistance patterns in clinical isolates of Escherichia coli and their correlation with integrons and phylogenetic groupings. Methods: A total of 37 clinical E. coli isolates were evaluated for drug resistance patterns by disk diffusion method. Phylogenetic groupings and the presence of integrons among E. coli were determined by multiplex PCR assays. Results: Multidrug resistance was identified in 84% of the clinical isolates of E. coli with higher resistance found against cephalosporins (94.6%) and fluoroquinolones (83.8%), while lower resistance was observed against polymyxins (24.3%) and carbapenems (29.7%). Metallo-ß-lactamases were found in all carbapenem resistant isolates. The phylogenetic group B2 was the most dominant (40.5%), followed by groups A (35.1%), D (13.5%) and B1 (10.8%). Integrons were detected in 25 (67.6%) isolates and intI1, intI2, and intI3 genes were found in 62.2%, 18.9% and 10.8% of isolates respectively. Conclusion: Our results show that phylogenetic classification of E. coli is not relevant with antimicrobial resistance. However, there was strong association between the integron classes and resistance against ß-lactam and fluoroquinolones antimicrobials. Additionally, this study highlighted that the presence of integrons plays a crucial role in the development of multidrug resistance in clinical isolates of E. coli. Most significantly, this is the first report of detection of three classes of integron among clinical isolates of E. coli in Pakistan.

The NWRD Dataset: An Open-Source Annotated Segmentation Dataset of Diseased Wheat Crop.

Wheat stripe rust disease (WRD) is extremely detrimental to wheat crop health, and it severely affects the crop yield, increasing the risk of food insecurity. Manual inspection by trained personnel is carried out to inspect the disease spread and extent of damage to wheat fields. However, this is quite inefficient, time-consuming, and laborious, owing to the large area of wheat plantations. Artificial intelligence (AI) and deep learning (DL) offer efficient and accurate solutions to such real-world problems. By analyzing large amounts of data, AI algorithms can identify patterns that are difficult for humans to detect, enabling early disease detection and prevention. However, deep learning models are data-driven, and scarcity of data related to specific crop diseases is one major hindrance in developing models. To overcome this limitation, in this work, we introduce an annotated real-world semantic segmentation dataset named the NUST Wheat Rust Disease (NWRD) dataset. Multileaf images from wheat fields under various illumination conditions with complex backgrounds were collected, preprocessed, and manually annotated to construct a segmentation dataset specific to wheat stripe rust disease. Classification of WRD into different types and categories is a task that has been solved in the literature; however, semantic segmentation of wheat crops to identify the specific areas of plants and leaves affected by the disease remains a challenge. For this reason, in this work, we target semantic segmentation of WRD to estimate the extent of disease spread in wheat fields. Sections of fields where the disease is prevalent need to be segmented to ensure that the sick plants are quarantined and remedial actions are taken. This will consequently limit the use of harmful fungicides only on the targeted disease area instead of the majority of wheat fields, promoting environmentally friendly and sustainable farming solutions. Owing to the complexity of the proposed NWRD segmentation dataset, in our experiments, promising results were obtained using the UNet semantic segmentation model and the proposed adaptive patching with feedback (APF) technique, which produced a precision of 0.506, recall of 0.624, and F1 score of 0.557 for the rust class.

Hybrid FSK-FDM Scheme for Data Rate Enhancement in Dual-Function Radar and Communication.

In this paper, we present a hybrid frequency shift keying and frequency division multiplexing (i.e., FSK-FDM) approach for information embedding in dual-function radar and communication (DFRC) design to achieve an improved communication data rate. Since most of the existing works focus on merely two-bit transmission in each pulse repetition interval (PRI) using different amplitude modulation (AM)- and phased modulation (PM)-based techniques, this paper proposes a new technique that doubles the data rate by using a hybrid FSK-FDM technique. Note that the AM-based techniques are used when the communication receiver resides in the side lobe region of the radar. In contrast, the PM-based techniques perform better if the communication receiver is in the main lobe region. However, the proposed design facilitates the delivery of information bits to the communication receivers with an improved bit rate (BR) and bit error rate (BER) regardless of their locations in the radar's main lobe or side lobe regions. That is, the proposed scheme enables information encoding according to the transmitted waveforms and frequencies using FSK modulation. Next, the modulated symbols are added together to achieve a double data rate using the FDM technique. Finally, each transmitted composite symbol contains multiple FSK-modulated symbols, resulting in an increased data rate for the communication receiver. Numerous simulation results are presented to validate the effectiveness of the proposed technique.

Nickel toxicity pretreatment attenuates salt stress by activating antioxidative system and ion homeostasis in tomato (Solanum lycopersicon L.): an interplay from mild to severe stress.

Plants antioxidative system is the first line of defense against oxidative stress caused secondarily by toxic ions under salinity. Plants with pre-activated antioxidative system can better adapt to salinity and can result in higher growth and yield. The current experiment was conducted to assess the adaptation of two tomato genotypes (Riogrande and Green Gold) with pre-activated antioxidative enzymes against salt stress. Tomato seedlings were exposed to mild stress (Ni: 0, 15 and 30 mg L-1) for three weeks to activate the antioxidative enzymes. The seedlings with pre-activated antioxidative enzymes were then grown under severe stress in hydroponics (0, 75 and 150 mM NaCl) and soil (control, 7.5 and 15 dS m-1) to check the adaptation, growth and yield. The results showed that Ni toxicity significantly enhanced activities of antioxidant enzymes (SOD, CAT, APX and POX) in both the genotypes and reduced growth with higher values in genotype Riogrande than Green Gold. The seedlings with pre-activated antioxidant enzymes showed better growth, low Na+ and high K+ uptake and maintained higher antioxidative enzymes activity than non-treated seedlings after four weeks of salt stress treatment in hydroponics. Similarly, the results in soil salinity treatment of the Ni pretreated seedlings showed higher yield characteristics (fruit yield per plant, average fruit weight and fruit diameter) than non-treated seedlings. However, Ni pretreatment had nonsignificant effect on tomato fruit quality characteristics like fruit dry matter percentage, total soluble solids, fruit juice pH and titratable acidity. The genotype Riogrande showed better growth, yield and fruit quality than Green Gold due to higher activity of antioxidant enzymes and better ion homeostasis as a result of Ni pretreatment. The results suggest that pre-activation antioxidant enzymes by Ni treatment proved to be an effective strategy to attenuate salt stress for better growth and yield of tomato plants.

Barriers and challenges faced by orthodontists in providing orthodontic care and implementing new innovative technologies in the field of orthodontics among children and adults: a qualitative study.

Orthodontic treatment requires the cooperation of patients as well as orthodontists. Therefore, the aim of the study was to investigate and address the challenges and barriers orthodontists have in achieving the desired orthodontic results, as well as make recommendations for ways to address the stated problems and introduce new innovative technologies to the area of orthodontics. This qualitative study wasbased on the grounded theory. Twelve orthodontists participated in face-to-face interviews, which were primarily comprised of open-ended questions. Data analysis was carried out manually using the "by hand" method. Orthodontists between the age group of 29-42 were interviewed. The answers varied depending on the years of experience of the interviewees. Teenagers and boys were found to be most non-compliant with the treatment. The average treatment span ranged between 6 months for mild cases up to 3 years for severe orthodontic cases occurring most commonly in government hospitals. Patient compliance plays a major role in orthodontics. Poor oral hygiene maintenance, brackets breakage by patients, and missed appointments were the major concerns mentioned by participants and hindered getting the desired results. Patients' main worries were related to the cost of therapy, premolar extractions, the length of treatment, and the possibility of relapse. Patient counseling and reinforcement at the start of the treatment can help to overcome the challenges and barriers in orthodontics since patient motivation is a very important factor in obtaining the desired results. It is recommended to conduct more training sessions for the orthodontists in order to introduce them to new technological paradigms.

Comparison of residual silicone oil index after removal of silicone oil with fluid-air versus oil-fluid exchange.

Objectives: To compare the effectiveness of fluid-air exchange with silicone oil-fluid exchange in reducing the residual silicone oil (SO) droplets after the removal of SO. Methods: This was a prospective, quasi-experimental study conducted from October 2021 to February 2022 at Eye Unit-III, COAVS, Mayo Hospital, Lahore. Sixty-one patients with siliconized eyes underwent removal of SO with two different techniques and were divided into fluid-air exchange and oil-fluid exchange groups. To quantify the residual silicone droplets objectively, B-scan echographic images were analyzed within seven days of surgery. Silicone oil index (SOI) which is the amount of residual SO droplets/vitreal area in the images was calculated with the help of imagej software. Results: The residual SOI of the fluid-air exchange group (0.99 ± 1.76%) was significantly lower than the oil-fluid exchange group (3.25 ± 3.85%). The SOI is positively correlated with the duration of tamponade, preoperative intraocular- pressure and axial length. Persistent IOP elevation post-operatively was seen in 16.67% individuals in the fluid-air exchange group and 54.8% individuals in the oil-fluid exchange group. Conclusion: Fluid-air exchange group was found to be superior in reducing residual SO droplets than the oil-fluid exchange group.

Fast volumetric imaging with line-scan confocal microscopy by electrically tunable lens at resonant frequency.

In microscopic imaging of biological tissues, particularly real-time visualization of neuronal activities, rapid acquisition of volumetric images poses a prominent challenge. Typically, two-dimensional (2D) microscopy can be devised into an imaging system with 3D capability using any varifocal lens. Despite the conceptual simplicity, such an upgrade yet requires additional, complicated device components and usually suffers from a reduced acquisition rate, which is critical to properly document rapid neurophysiological dynamics. In this study, we implemented an electrically tunable lens (ETL) in the line-scan confocal microscopy (LSCM), enabling the volumetric acquisition at the rate of 20 frames per second with a maximum volume of interest of 315 × 315 × 80 µm3. The axial extent of point-spread-function (PSF) was 17.6 ± 1.6 µm and 90.4 ± 2.1 µm with the ETL operating in either stationary or resonant mode, respectively, revealing significant depth axial penetration by the resonant mode ETL microscopy. We further demonstrated the utilities of the ETL system by volume imaging of both cleared mouse brain ex vivo samples and in vivo brains. The current study showed a successful application of resonant ETL for constructing a high-performance 3D axially scanning LSCM (asLSCM) system. Such advances in rapid volumetric imaging would significantly enhance our understanding of various dynamic biological processes.

MiRNA fine tuning for crop improvement: using advance computational models and biotechnological tools.

MiRNAs modulate target genes expression at post-transcriptional levels, by reducing spatial abundance of mRNAs. MiRNAs regulats plant metabolism, and emerged as regulators of plant stress responses. Which make miRNAs promising candidates for fine tuning to affectively alter crop stress tolerance and other important traits. With recent advancements in the computational biology and biotechnology miRNAs structure and target prediction is possible resulting in pin point editing; miRNA modulation can be done by up or down regulating miRNAs using recently available biotechnological tools (CRISPR Cas9, TALENS and RNAi). In this review we have focused on miRNA biogenesis, miRNA roles in plant development, plant stress responses and roles in signaling pathways. Additionally we have discussed latest computational prediction models for miRNA to target gene interaction and biotechnological systems used recently for miRNA modulation. We have also highlighted setbacks and limitations in the way of miRNA modulation; providing entirely a new direction for improvement in plant genomics primarily focusing miRNAs.

Examining the Effects of Normal Ageing on Cortical Connectivity of Older Adults.

With the recent advancement in computer technology, we can extract the picture of the brain as a network. The aim of this study is to constructs large scale individual anatomical brain networks using regional gray matter cortical thickness from individual subject's magnetic resonance imaging (MRI) data, as well as to investigate changes with normal aging in global network organization. The dataset includes 183 healthy subjects sMRI data with an age range from 50 to 80 plus. For all brain networks, we calculated the global network measures and nodal network measures by using network analysis toolkit GRETNA. From global network measurements we calculated small-world measurements and network efficiency measurements, from nodal measurements we calculated node clustering coefficient (CC) and node efficiency at a wide-range of threshold values. All small world measurements showed more clustering at all the given threshold values than random networks and a alike least path length, indicative of that they were "small world". To analyze the effect normal ageing on networks organization, the networks of subjects were categorized into three age groups (50s, 60s, and 70 over). The global and nodal network measurements of each group were statistically analyzed to investigate the significant difference in network organization with in age groups. Results shows that the age has no significance effect in global measurements of brain network. However, by analysis the nodal measures of brain network between age group, network nodes from brain frontal lobe and temporal lobe showed age related significant difference. The results obtained from the proposed study suggest that this network method can deliver a concise network-level picture of brain organization and be used from the outlook of composite networks to investigate inter-individual variability in brain morphology.

Perceptions of oncology as a career choice among the early career doctors in Pakistan.

BACKGROUND: Lack of oncologists is a growing global concern. With the rise in cancer burden across the world, the supply-demand mismatch of the oncology workforce is projected to increase. Furthermore, oncology is a low-ranked field of choice among medical students, and without understanding the perceptions and concerns of early-career doctors regarding oncology, any investments made in cancer care will be futile. This study aims to determine the opinions of young doctors and the factors most affecting their preferences in order to devise focused strategies to attract more doctors into oncology. METHODS: A cross-sectional study was conducted on 300 early-career doctors across various public and private hospitals in Pakistan, from March to November 2019. A close-ended, self-administered questionnaire was used to assess their opinions in terms of the workplace environment, scope, and the emotional and financial aspects of oncology. Data was analyzed using SPSS version 23 and the influence (positive or negative) of the perceptions on the choice of oncology as a career was determined by binary logistic regression analysis. RESULTS: Almost three-quarters of the participants did not want a career in oncology. The top positive perceptions about oncology in descending order were: progressive field, gender-neutral, stable working hours, financially healthy, and work-family balance. Top negative perceptions were: lack of oncologic facilities in hospitals, radiation exposure, need for private practice, poor patient prognosis, high patient load, and depressing environment. Participants who attended private medical school (p < 0.10), planned to live abroad (p < 0.10), had an oncologist (p < 0.05), cancer survivor or death due to cancer in the family (p < 0.05), were more likely to adopt oncology as a career. Those who believed that poor patient prognosis can have an impact on career choice were less likely to prefer oncology (p < 0.05). CONCLUSION: Despite the rising cancer burden, early career doctors are reluctant to join oncology. Curricular, infrastructural and policy changes are needed at the level of medical school, oncology training and practice to recruit more young doctors and minimize the existing paucity of the oncologic workforce.

Assessment of cadmium and lead tolerance potential of quinoa (Chenopodium quinoa Willd) and its implications for phytoremediation and human health.

Soil contamination with Cd and Pb is a worldwide problem which not only degrades the environment but also poses a serious threat for human and animal health. Phytoremediation of these contaminated soils using halophytic plants like quinoa presents an opportunity to clean the soils and use them for crop production. The current experiment was performed to evaluate the Cd and Pb tolerance potential of quinoa and subsequently its implications for human health. Three weeks old quinoa seedlings were exposed to Cd (30, 60 and 90 mg kg-1) and Pb (50, 100 and 150 mg kg-1) levels along with a control. The results revealed that plant height decreased at highest levels of soil Cd and Pb. Shoot, root and seed dry weight decreased with increasing levels of soil Cd and Pb. Tissue Cd and Pb concentrations increased with increasing levels of Cd and Pb in soil, the highest Cd was found in roots while the lowest in seeds. The highest Pb concentration was found in shoots at low Pb level, while in roots at high level of Pb. Increasing levels of Cd and Pb stimulated the activities of measured antioxidant enzymes and decreased membrane stability index. The health risk assessments of Cd and Pb revealed that hazard quotient was < 1 for both the metals. However, the results of total hazard quotient showed that value was < 1 for Pb and 1.19 for Cd showing potential carcinogenicity. This study demonstrates that quinoa has good phytoremediation potential for Cd and Pb however, the risk of Cd toxicity is challenging for human health.

Level of biofilm production by Staphylococcus aureus isolates is critical for resistance against most but not all antimicrobial drugs.

Background and Objective: Staphylococcal biofilms cause a wide range of acute and chronic infections, both in hospital and community settings across the world. This study explores biofilm forming propensity among Staphylococcus aureus clinical isolates from Faisalabad, Pakistan and their association with antimicrobial drug resistance. Methods: The study was conducted during July to December 2020. The biofilm forming ability of S. aureus isolates was assessed by crystal violet staining in 96 well plates. Antimicrobial susceptibility was determined by disk diffusion method against ten antimicrobials representing whole spectrum of antimicrobial drugs. Results: All the isolates (n=22) produced biofilm; 14 (63.6%) were strong, and 8 (36.4%) moderate biofilm producers. Comparative data were obtained for moderate and strong biofilm producers. Increased biofilm production did not affect azithromycin, clindamycin and mupirocin. However, stronger biofilm production significantly increased resistant isolates in case of augmentin (23.2%), cefoxitin (17.9%), levofloxacin (26.8%), tetracycline (23.2%), vancomycin (14.3%) and trimethoprim (21.4%). Conclusions: Our findings indicate that the ability to produce large amount of biofilm is an important factor, and S. aureus isolates with this ability, do not require acquisition of drug resistance genes from other bacteria. Our study also provides a guideline for selection of antimicrobials which are not adversely affected by level of biofilm production by various strains of S. aureus.

A 24-generation-old founder mutation impairs splicing of RBBP8 in Pakistani families affected with Jawad syndrome.

Jawad syndrome is a multiple congenital anomaly and intellectual disability syndrome with mutation in RBBP8 reported only in two families. Here, we report on two new families from Pakistan and identified a previously reported variant in RBBP8, NM_002894.3:c.1808-1809delTA. We could show that this mutation impairs splicing resulting in two different abnormal transcripts. Finally, we could verify a shared haplotype among all four families and estimate the founder event to have occurred some 24 generations ago.

Phytomelatonin: An overview of the importance and mediating functions of melatonin against environmental stresses.

Recently, melatonin has gained significant importance in plant research. The presence of melatonin in the plant kingdom has been known since 1995. It is a molecule that is conserved in a wide array of evolutionary distant organisms. Its functions and characteristics have been found to be similar in both plants and animals. The review focuses on the role of melatonin pertaining to physiological functions in higher plants. Melatonin regulates physiological functions regarding auxin activity, root, shoot, and explant growth, activates germination of seeds, promotes rhizogenesis (growth of adventitious and lateral roots), and holds up impelled leaf senescence. Melatonin is a natural bio-stimulant that creates resistance in field crops against various abiotic stress, including heat, chemical pollutants, cold, drought, salinity, and harmful ultra-violet radiation. The full potential of melatonin in regulating physiological functions in higher plants still needs to be explored by further research.

Improved lifetime and stability of copper species in hierarchical, copper-incorporated CuSAPO-34 verified by catalytic model reactions.

The first successful synthesis of hierarchical CuSAPO-34 (3.9 wt% Cu) is reported using the polymer Pluronic F127 as a mesoporous structure directing agent (SDA). X-Ray absorption spectroscopy (XAS) revealed single site Cu2+ with 4 nearest oxygen neighbours at 1.96 Å. A catalytic model reaction, the selective reduction of NO with different sized hydrocarbons as reductants, explained that Cu2+ is accessible and reactive in both micro- and mesopores of the hierarchical CuSAPO-34. The presence of mesopores resulted in superior lifetime of the hierarchical CuSAPO-34 in the catalytic model reaction, selective oxidation of propene.

Does biochar accelerate the mitigation of greenhouse gaseous emissions from agricultural soil? - A global meta-analysis.

Greenhouse gaseous (GHGs) emissions from cropland soils are one of the major contributors to global warming. However, the extent and pattern of these climatic breakdowns are usally determined by the management practices in-place. The use of biochar on cropland soils holds a great promise for increasing the overall crop productivity. Nevertheless, biochar application to agricultural soils has grown in popularity as a strategy to off-set the negative feedback associated with agriculture GHGs emissions, i.e., CO2 (carbon dioxide), CH4 (methane), and N2O (nitrous oxide). Despite increasing efforts to uncover the potential of biochar to mitigate the farmland GHGs effects, there has been little synthesis of how different types of biochar affect GHGs fluxes from cropland soils under varied experimental conditions. Here, we presented a meta-analysis of the interactions between biochar and GHGs emissions across global cropland soils, with field experiments showing the strongest GHG mitigation potential, i.e. CO2 (RR = -0.108) and CH4 (RR = -0.399). The biochar pyrolysis temperature, feedstock, C: N ratio, and pH were also found to be important factors influencing GHGs emissions. A prominent reduction in N2O (RR = -0.13) and CH4 (RR = -1.035) emissions was observed in neutral soils (pH = 6.6-7.3), whereas acidic soils (pH ≤ 6.5) accounted for the strongest mitigation effect on CO2 compared to N2O and CH4 emissions. We also found that a biochar application rate of 30 t ha-1 was best for mitigating GHGs emissions while achieving optimal crop yield. According to our meta-analysis, maize crop receiving biochar amendment showed a significant mitigation potential for CO2, N2O, and CH4 emissions. On the other hand, the use of biochar had shown significant impact on the global warming potential (GWP) of total GHGs emissions. The current data synthesis takes the lead in analyzing emissions status and mitigation potential for three of the most common GHGs from cropland soils and demonstrates that biochar application can significantly reduce the emissions budget from agriculture.

Epidemiological trends of foodborne Campylobacter outbreaks in the United States of America, 1998-2016.

Campylobacter is a major cause of foodborne diarrheal infections in the United States of America (USA). This study aimed to elucidate the patterns of Campylobacter foodborne outbreaks temporally and spatially concerning food vehicles. We collected the data of foodborne outbreaks from 1998 to 2016 reported to the Centers for Disease Control and Prevention. The incidence rate of outbreaks for each food source was calculated and analyzed for each variable including season, food location, and census region. Overall, 465 single-state outbreaks and 8003 cases were reported during 1998-2016. Outbreaks were frequently attributed to dairy products (32%), chicken (17%) and vegetables (6%). Binomial regression analysis showed that compared to chicken items, the highest rate ratio of outbreaks was associated with dairy products (1.86) followed by vegetables (1.35) and meat products (0.76). More outbreaks were reported in the summer (35%) followed by the spring (26%) and fall (22%) season. We found that the highest number of outbreaks occurred in the West 159 (34%) and Midwest 137 (29%) census regions. The study highlights the role of dairy, chicken, and vegetables as food vehicles in Campylobacter outbreaks. Findings from this study can help in devising strategies to mitigate the increasing occurrence of Campylobacter foodborne outbreaks.

First report of Alternaria alternata causing Alternaria leaf spot of Fig in Pakistan.

Fig (Ficus carica) is a species of flowering plants within the mulberry family. During June 2020, leaf spots were observed on several fig plants (31°26'15.0"N 73°04'25.6"E) at the University of Agriculture, Faisalabad, Pakistan. Early symptoms were small, oval to circular, light brown, sunken spots that were uniformly distributed on the leaves. Spots gradually enlarged and coalesced into circular to irregular dark brown to black spots that could be up to 3cm diam. with no or small sized fruit. Disease incidence was approximately 25%. To identify the causal agent of the disease, 15 symptomatic leaves were collected. Small pieces from all diseased samples were removed from the margin between healthy and diseased tissues were surface disinfested in 70% ethanol for 2 min, rinsed three times with sterile distilled water, plated on Potato dextrose agar and incubated at 25 ± 2°C with a 12-h photoperiod. Fungal isolation on PDA medium frequency was 95% from diseases leaves. Morphological observations were made on 7- day- old single-spore cultures. The colonies initially appeared light grayish which turned sooty black in color. All fungal isolates were characterized by small, short-beaked, multicellular conidia. The conidia were ellipsoidal or ovoid and measured 9 to 25 µm × 5 to 10 µm (n = 40) with longitudinal and transverse septa. The morphological characters matched those of Alternaria alternata (Simmons et al. 2007). Genomic DNA of a representative isolate (FG01-FG03) was extracted using DNAzol reagent (Thermo Fisher Scientific MA, USA) and PCR amplification of the internal transcribed spacer (ITS) rDNA region, was performed with primers ITS1/ITS4 (White et al. 1990), partial RNA polymerase II largest subunit (RPB2) with RPB2-5F/RPB2-7cR (Liu et al. 1999) and glyceraldehyde 3-phosphate dehydrogenase (GAPDH) gene regions was performed with gpd1/gpd2 (Berbee et al. 1999). The obtained sequences were deposited in GenBank with accession numbers MW692903.1 to MW692905.1 for ITS-rDNA gene, MZ066731.1 to MZ066733.1 for RPB2 and MZ066728.1 to MZ066730.1 for GAPDH. BLASTn analysis showed 100% identity with the submitted sequences of A. alternata for ITS rDNA, RPB2, and GAPDH. To confirm pathogenicity, 2-month-old 15 healthy potted F. carica plants were sprayed at true leaf stage with conidial suspension by using an atomizer in a greenhouse. Each representative A. alternata isolate (FG01-FG03) was inoculated on every three plants with conidial suspensions (106 conidia/ml; obtained from 1-week-old cultures) amended with 0.1% (vol/vol) of Tween 20 until runoff (1.5 to 2 ml per plant) whereas, three control plants were sprayed with sterile distilled water amended with 0.1% Tween 20. All plants were incubated at 25 ± 2°C in a greenhouse, and the experiment was conducted twice. After 10 days of inoculation, each isolate induced leaf spots similar to typical spots observed in the field, whereas the control plants remained symptomless. The fungus was re-isolated from symptomatic tissues and reisolation frequency was 100%. Re-isolated fungal cultures were again morphologically and molecularly identical to A. alternata, thus fulfilling Koch's postulates. Previously, A. alternata has been reported cause fruit disease of fig in Pakistan and California, USA (Alam et al. 2021; Latinovic et al. 2014). To our knowledge, this is the first report of A. alternata causing leaf spot on common fig in Pakistan. In Pakistan, fig is widely grown for drying, and this disease may represent a threat to fig cultivation.

Development of a Novel Methodology for Remaining Useful Life Prediction of Industrial Slurry Pumps in the Absence of Run to Failure Data.

Smart remaining useful life (RUL) prognosis methods for condition-based maintenance (CBM) of engineering equipment are getting high popularity nowadays. Current RUL prediction models in the literature are developed with an ideal database, i.e., a combination of a huge "run to failure" and "run to prior failure" data. However, in real-world, run to failure data for rotary machines is difficult to exist since periodic maintenance is continuously practiced to the running machines in industry, to save any production downtime. In such a situation, the maintenance staff only have run to prior failure data of an in operation machine for implementing CBM. In this study, a unique strategy for the RUL prediction of two identical and in-process slurry pumps, having only real-time run to prior failure data, is proposed. The obtained vibration signals from slurry pumps were utilized for generating degradation trends while a hybrid nonlinear autoregressive (NAR)-LSTM-BiLSTM model was developed for RUL prediction. The core of the developed strategy was the usage of the NAR prediction results as the "path to be followed" for the designed LSTM-BiLSTM model. The proposed methodology was also applied on publically available NASA's C-MAPSS dataset for validating its applicability, and in return, satisfactory results were achieved.