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Abstract River systems originating from the Upper Indus Basin (UIB) are dominated by runoff from snow and glacier melt and summer monsoonal rainfall. These water resources are highly stressed as huge populations of people living in this region depend on them, including for agriculture, domestic use, and energy production. Projections suggest that the UIB region will be affected by considerable (yet poorly quantified) changes to the seasonality and composition of runoff in the future, which are likely to have considerable impacts on these supplies. Given how directly and indirectly communities and ecosystems are dependent on these resources and the growing pressure on them due to ever‐increasing demands, the impacts of climate change pose considerable adaptation challenges. The strong linkages between hydroclimate, cryosphere, water resources, and human activities within the UIB suggest that a multi‐ and inter‐disciplinary research approach integrating the social and natural/environmental sciences is critical for successful adaptation to ongoing and future hydrological and climate change. Here we use a horizon scanning technique to identify the Top 100 questions related to the most pressing knowledge gaps and research priorities in social and natural sciences on climate change and water in the UIB. These questions are on the margins of current thinking and investigation and are clustered into 14 themes, covering three overarching topics of “governance, policy, and sustainable solutions”, “socioeconomic processes and livelihoods”, and “integrated Earth System processes”. Raising awareness of these cutting‐edge knowledge gaps and opportunities will hopefully encourage researchers, funding bodies, practitioners, and policy makers to address them.

OBJECTIVE: The aim of the study was to determine the bacterial-adherence to the experimental pellicle pretreated with commercially available oral-rinse/photosensitizer (mimicking use of oral-rinse/photosensitizer before meals). MATERIALS AND METHODS: An artificial mouth (NAM) system was used for the development of single-species biofilm (Actinomyces viscosus, Streptococcus mitis and Streptococcus sanguinis respectively). Two commercially available oral-rinses containing active ingredients [Essential oils (EO) and Chlorhexidine gluconate (CHX) were used. Curcumin photosensitizer (PS) was used as a photosensitizer against the microbes. For the adherence study, the experimental pellicle on the beads (in the capillary tubes of the NAM system) was pretreated with the oral-rinse and photosensitizer before the inoculation of bacteria; this would resemble the use of rinse/photosensitizer before meal. The bacterial population of the biofilm was determined using serial dilution assay and expressed as colony forming unit per ml. Deionized distilled water was used in place of oral-rinse/photosensitizer and served as a negative-control. For the qualitative study, bacterial population viewing was carried out using Scanning Electron Microscope (SEM). RESULTS: It was observed that on treatment with the oral-rinses the bacterial population of S.mitis, S.sanguinis and A.viscosus (adherence) was significantly reduced where the reduction was less for EO-based oral-rinse compared with that of CHX and curcumin PS in the following sequence EO

OBJECTIVE: The aim of the study was to evaluate the tensile BS of FPs luted with conventional and self-adhesive resin modified GIC cement on disinfection of post-space radicular dentin with various photo-activated photosensitizer (chitosan, TB and Clp6). MATERIALS AND METHODS: Sixty-six orthodontically extracted mandibular pre-molars were selected on specific exclusion/inclusion criteria, trailed by thorough debridement of plaque/calculus and disinfected by immersion in Chloramine T trihydrate solution for 48 hrs. The selected teeth were sectioned from the cement-enamel junction removing the crown. The radicular region of the samples was entrenched perpendicularly in heat cure resin modified acrylic. The pulpal tissue was detached using K-files trailed by canal shaping with ProTaper Next rotary NiTi (Dentsply Sirona, Gloucestershire, UK) files under continuous irrigation with NaOCl. The canals were dried using paper points trailed by obturation by Pro Taper Next Obturators gutta-percha points (Dentsply, UK) coated with ADSEAL (Meta Biomed, Chungcheongbuk-do, South Korea). After incubation for seven days in an environment mimicking oral cavity, post space was created using peso reamers. The space was disinfected by G1: chitosan 3 mg/mL; G2: 13-15 mg/mL TB and G3: Clp6. After photo-irridation the FPs were luted with conventional (n=11) and resin modified self-adhesive cement (n=11) for each group respectively. The specimens were incubated for 48 hrs prior to tensile BS testing. The type of bond fracture/failure was evaluated under 30x magnification. The tensile BS was statistically analyzed using ANOVA trailed by Tukey's test to respective groups. RESULTS: FPs luted using self-adhesive resin modified cement with prior to disinfection by TBs displayed highest tensile BS 291.47 N ± 5.36. On the contrary, post-space disinfected by Clp6 displayed statistically significant (p = 0.05) lowest bond strength (276.62 N ± 4.31). Intra-group analysis displayed statistically significant difference in bond strength of the luting dental materials (p = 0.05). CONCLUSIONS: The self-adhesive resin modified cement revealed utmost bond strength on pre-treatment of post-space with respective photo-activated photosensitizer (chitosan, TB & Clp6) in contrast to conventional GIC. [ABSTRACT FROM AUTHOR]

Many diseases such as human dental caries result in the destruction of tooth structure; dental caries is an infectious disease leading to the destruction of tooth structure due to the acids produced on the fermentation of dietary carbohydrates by acidogenic bacteria. Bacteria colonise non-shedding oral surfaces, and produce lactic, acetic, and formic acids. Preserving tooth structure using fluoride in dental products may have its adverse effects on human health. The use of fluoride-containing dental products without supervision in children when the teeth are developing can lead to fluorosis. Therefore, the main aim of the present review was to identify natural oral healthcare products having minimum or no adverse effects in maintaining the integrity of tooth enamel. The active compounds observed in the natural plant products till date are polyphenolic compounds which contain antibacterial effects, and a potential to shift demineralisation to remineralisation. But their mechanism of action remain unclear. Therefore, further studies are needed to determine the effectiveness of these natural products and enhance their effect. [ABSTRACT FROM AUTHOR]

Morphology plays a crucial role in defining the optical, electronic, and mechanical properties of halide perovskite microcrystals. Therefore, developing strategies that offer precise control over crystal morphology during the growth process is highly desirable. This work presents a simple scheme to simultaneously grow distinct geometries of cesium lead bromide (CsPbBr3) microcrystals, including microrods (MR), microplates (MP), and microspheres (MS), in a single chemical vapor deposition (CVD) experiment. By strategically adjusting precursor evaporation temperatures, flux density, and the substrate temperature, we surpass previous techniques by achieving simultaneous yet selective growth of multiple CsPbBr3 geometries at distinct positions on the same substrate. This fine growth control is attributed to the synergistic variation in fluid flow dynamics, precursor substrate distance, and temperature across the substrate, offering regions suitable for the growth of different morphologies. Pertinently, perovskite MR are grown at the top, while MP and MS are observed at the center and bottom regions of the substrate, respectively. Structural analysis reveals high crystallinity and an orthorhombic phase of the as-grown perovskite microcrystals, while persistent photonic lasing manifests their nonlinear optical characteristics, underpinning their potential application for next-generation photonic and optoelectronic devices.

Abstract Carbonate rocks present a complicated pore system owing to the existence of intra-particle and interparticle porosities. Therefore, characterization of carbonate rocks using petrophysical data is a challenging task. Conventional neutron, sonic, and neutron-density porosities are proven to be less accurate as compared to the NMR porosity. This study aims to predict the NMR porosity by implementing three different machine learning (ML) algorithms using conventional well logs including neutron-porosity, sonic, resistivity, gamma ray, and photoelectric factor. Data, comprising 3500 data points, was acquired from a vast carbonate petroleum reservoir in the Middle East. The input parameters were selected based on their relative importance with respect to output parameter. Three ML techniques such as adaptive neuro-fuzzy inference system (ANFIS), artificial neural network (ANN), and functional network (FN) were implemented for the development of prediction models. The model’s accuracy was evaluated by correlation coefficient (R), root mean square error (RMSE), and average absolute percentage error (AAPE). The results demonstrated that all three prediction models are reliable and consistent exhibiting low errors and high ‘R’ values for both training and testing prediction when related to actual dataset. However, the performance of ANN model was better as compared to other two studied ML techniques based on minimum AAPE and RMSE errors (5.12 and 0.39) and highest R (0.95) for testing and validation outcome. The AAPE and RMSE for the testing and validation results were found to be 5.38 and 0.41 for ANFIS and 6.06 and 0.48 for FN model, respectively. The ANFIS and FN models exhibited ‘R’ 0.937 and 0.942, for testing and validation dataset, respectively. Based on testing and validation results, ANFIS and FN models have been ranked second and third after ANN. Further, optimized ANN and FN models were used to extract explicit correlations to compute the NMR porosity. Hence, this study reveals the successful applications of ML techniques for the accurate prediction of NMR porosity.

Drilling through shale formations can be expensive and time-consuming due to the instability of the wellbore. Further, there is a need to develop inhibitors that are environmentally friendly. Our study discovered a cost-effective solution to this problem using Gum Arabic (ArG). We evaluated the inhibition potential of an ArG clay swelling inhibitor and fluid loss controller in water-based mud (WBM) by conducting a linear swelling test, capillary suction timer test, and zeta potential, fluid loss, and rheology tests. Our results displayed a significant reduction in linear swelling of bentonite clay (Na-Ben) by up to 36.1% at a concentration of 1.0 wt. % ArG. The capillary suction timer (CST) showed that capillary suction time also increased with the increase in the concentration of ArG, which indicates the fluid-loss-controlling potential of ArG. Adding ArG to the drilling mud prominently decreased fluid loss by up to 50%. Further, ArG reduced the shear stresses of the base mud, showing its inhibition and friction-reducing effect. These findings suggest that ArG is a strong candidate for an alternate green swelling inhibitor and fluid loss controller in WBM. Introducing this new green additive could significantly reduce non-productive time and costs associated with wellbore instability while drilling. Further, a dynamic linear swelling model, based on machine learning (ML), was created to forecast the linear swelling capacity of clay samples treated with ArG. The ML model proposed demonstrates exceptional accuracy (R2 score = 0.998 on testing) in predicting the swelling properties of ArG in drilling mud.

In developing countries like Pakistan, the preservation of the environment, as well as people’s economies, agriculture, and way of life, are believed to be hampered by climate change. Understanding how people perceive climate change and its signs is essential for creating a variety of adaptation solutions. In this study, we aim to bridge the gap in current research within this area, which predominantly relies on satellite data, by integrating qualitative assessments of people’s perceptions of climate change, thereby providing valuable ground-based observations of climate variability and its impacts on local communities. Field-based data were collected at different altitudes (upstream (US), midstream (MS), and downstream (DS)) of the Upper Indus Basin using both quantitative and qualitative assessments in 2017. The result shows that these altitudes are highly variable in many contexts: socioeconomic indicators of education, agriculture, income, women empowerment, health, access to basic resources, and livelihood diversifications are highly variable in the Indus Basin. The inhabitants of the Indus Basin perceive the climate changing around them and report impacts of this change as increase in overall temperatures (US 96.9%, MS 97%, DS 93.6%) and erratic rainfall patterns (US 44.1%, MS 73.3%, DS 51.0%) resulting in increased water availability for crops (US 38.6%, MS 39.7%, DS 54.8%) but also increasing number of dry days (US 56.7%, MS 85.5%, DS 67.1%). Communities at these altitudes said that agriculture was their primary source of income, making them particularly vulnerable to the effects of climate change and the dangers that go along with it. The insights are useful for determining what information and actions are required to support local climate-related hazard management in subtropical climate regions. Moreover, it is vital to launch a campaign to raise awareness of potential hazards, as well as to provide training and an early warning system.

Honey is a natural flower extract rich in healthy components including fructose, glucose, and various oligosaccharides. In addition, it comprises of proteins, enzymes, trace elements, vitamins, and polyphenols. Honey has a long history for its uses in medicinal purposes. However, its benefits on oral health have been overlooked till date. The main aim of this review is to address the benefits of honey in oral cavity, which have been identified in previous studies to have anti-cariogenic and anti-plaque; and also, for the treatment of cancer-induced mucositis and xerostomia. [ABSTRACT FROM AUTHOR]

In this study, graphene oxide (GO) was prepared with modified Hummer’s method while reduce graphene oxide (rGO) was prepared in the presence of hydrazine hydrate and then coated on polyester cotton (PC) blend camouflage pattern print fabric using the pad-dry-cure method. The as-synthesized GO and rGO were characterized by dynamic light scattering (DLS) analysis, X-ray diffraction (xRD), and UV-visible spectrophotometry. The surface morphology and the thermal camouflage property of the coated fabric were investigated by scanning electron microscopy (SEM) and infrared thermal imaging test, respectively. The average particle size of GO and rGO were 99.8 nm and 0.4 nm, respectively. The fabrics treated with GO and rGO apparently reduced the emitting temperature of the human body and made it similar to the surrounding environment. The increase in the concentration of coating materials (GO and rGO) resulted in the enhancement of camouflage property. Interestingly, the camouflage property of the coated fabric was very good even after several washing cycles. Based on these scientific outcomes, the coating of PC fabric with GO and rGO is a novel and successful approach in the development of thermal camouflage technical textiles which can be potentially applied on pilot-scale experiments to establish its industrial-scale feasibility.

The change in the global energy production mix towards variable renewable energy sources requires efficient utilization of regulated rivers to optimise hydropower operations meet the needs of a changing energy market. However, the flexible operation of hydropower plants causes non-natural, sub-daily fluctuating flows in the receiving water bodies, often referred to as ‘hydropeaking’. Drastic changes in sub-daily flow regimes undermine attempts to improve river system health. Environmental decision makers, including permitting authorities and river basin managers facing the intense and increasing pressure on river environments, should consider ecosystem services and biodiversity issues more thoroughly. The need for research innovations in hydropeaking operation design to fulfil both the water and energy security responsibilities of hydropower is highlighted. Our paper outlines optimized hydropeaking design as a future research direction to help researchers, managers, and decision-makers prioritize actions that could enable better integration of river science and energy system planning. The goal of this is to find a balanced hydropower operation strategy.

Development of layered nanostructures with distinct morphology has become an avenue of recent research to engineer targeted properties, especially for electrochemical devices. However, their remarkable characteristics are yet to be exploited for biological applications. In this work, we followed a facile and single-step method and prepared the solution grown zinc vanadium oxide multilayered nanosheets (ZnV2O4 MLNs). Field emission scanning electron microscopy shows the presence of nanosheets about 15–20 nm in height, integrated, and overlapped with one another, conferring a layered morphology. The layers are a structural mixture of triangular and hexagonal shapes. The phase pure and highly crystalline ZnV2O4 MLNs are investigated as an efficient receptor material for the electrocatalytic binding of glutathione, an important biomolecule involved in many cellular processes. This work is the first report where ZnV2O4 MLNs are employed to bind biomolecules. These nanostructured interfaces are expected to increase the effective surface area for detection, improve the planer surface of the sensor, and provide more binding sides for greater sensitivity. The developed sensor enables the sensitive detection of glutathione with outstanding detection limit down to 9 nM and ensures the 100% selectivity at a specific potential when compared to its functional and structural analogues. The study demonstrates the novel multilayer morphology-based interfaces can be a favourable platform to develop immune probes and further establishes their great potential to detect clinical biomolecules and disease biomarkers.

ObjectiveEpilepsy affects ~50 million people worldwide causing significant medical, financial, and sociologic concerns for affected patients and their families. To date, treatment of epilepsy is primarily symptomatic management because few effective preventative or disease-modifying interventions exist. However, recent research has identified neurobiological mechanisms of epileptogenesis, providing new pharmacologic targets to investigate. The current scientific evidence remains scattered across multiple studies using different model and experimental designs. The review compiles different models of anti-epileptogenic investigation and highlights specific compounds with potential epileptogenesis-modifying experimental drugs. It provides a platform for standardization of future epilepsy research to allow a more robust compound analysis of compounds with potential for epilepsy prevention.MethodsPubMed, Ovid MEDLINE, and Web of Science were searched from 2007 to 2021. Studies with murine models of epileptogenesis and explicitly detailed experimental procedures were included in the scoping review. In total, 51 articles were selected from 14,983 and then grouped by five core variables: (1) seizure frequency, (2) seizure severity, (3) spontaneous recurrent seizures (SRS), (4) seizure duration, and (5) mossy fiber sprouting (MFS). The variables were differentiated based on experimental models including methods of seizure induction, treatment schedule and timeline of data collection. Data was categorized by the five core variables and analyzed by converting original treatment values to units of percent of its respective control.ResultsDiscrepancies in current epileptogenesis models significantly complicate inter-study comparison of potential anti-epileptogenic interventions. With our analysis, many compounds showed a potential to reduce epileptogenic characteristics defined by the five core variables. WIN55,212-2, aspirin, rapamycin, 1400W, and LEV + BQ788 were identified compounds with the potential of effective anti-epileptic properties.SignificanceOur review highlights the need for consistent methodology in epilepsy research and provides a novel approach for future research. Inconsistent experimental designs hinder study comparison, slowing the progression of treatments for epilepsy. If the research community can optimize and standardize parameters such as methods of seizure induction, administration schedule, sampling time, and aniMal models, more robust meta-analysis and collaborative research would follow. Additionally, some compounds such as rapamycin, WIN 55,212-2, aspirin, 1400W, and LEV + BQ788 showed anti-epileptogenic modulation across multiple variables. We believe they warrant further study both individually and synergistically.

Knitted fleece fabrics with superior comfort characteristics are chiefly focused in winter wear. Thermal characteristics are an area of interest in selecting fleece clothing. However, environmental hazards also need to be focused. Fleece clothing is worn in cold areas having higher ultraviolet rays exposures. Hence the clothing should have the capability of combating environmental challenges. The study focuses on engineering variable fleece structures with different materials. Cotton, nylon, and polypropylene fleece patterns have been knitted using fleece 1:1, 3:1, and 2:2 patterns. The designs vary by tuck and miss stitch configurations in the fleece course. Comfort characteristics were determined through air permeability, moisture management, and thermal resistance tests. Performance criteria were evaluated in terms of pilling resistance and ultraviolet protection factor (UPF) investigation. Structures and materials owing better comfort characteristics with satisfactory UPF have been predicted as safe clothing in UV affected zones, that is, fleece 3:1 possessed the optimum comfort characteristics and UPF simultaneously; however, the mechanical performance was better for 2:1 and 1:1 fleece fabric due to less amount of miss stitch floating yarns.

The Zinc doped cobalt chromium ferrites with the general formula Co1-xZn xCr0.5Fe1.5O4 are used to deposit the thin films on silicon Si (100) substrate using pulsed laser deposition technique keeping the substrate temperature constant at 450°C. The pressure inside the chamber was 10-4Torr. After deposition these thin films have been post annealed at 800C0 to achieve the crystallinity. The structural properties, surface analysis, magnetic and optical properties have been analyzed by X-ray Diffractrometer, Atomic Force Microscopy, Spectroscopy Ellipsometry and Vibrating Sample Magnetometer respectively. XRD analysis revealed that lattice parameters decreases from 8.796 A0 to 8.705 A0 and crystallite size increases from 19 nm to 68nm with increasing the zinc contents. AFM analysis showed that average roughness increases with enhancement of zinc which may be due to increasing grain size and thickness. The ellipsometric analysis revealed that the band gap energy increases from 1.91 eV to 3.0 eV. [ABSTRACT FROM AUTHOR]

Acinetobacter baumannii, a pathogenic bacterium acquired in hospitals, causes diverse infections in humans. Previous studies have reported resistance among A. baumannii strains, potentially selecting multi-drug-resistant variants. In Pakistan, research has primarily focused on carbapenem-resistant A. baumannii (CRAB) strains, overlooking the investigation of efflux pumps (EPs) and biocide resistance. This study aims to assess A. baumannii strains from five hospitals in Pakistan, focusing on antibiotic and biocide susceptibility, the impact of EP inhibitors on antimicrobial susceptibility, and the distribution of ARGs and STs. A total of 130 non-repeated Acinetobacter baumannii isolates were collected from five tertiary care hospitals in Pakistan and identified using API 20NE and multiplex PCR. Antimicrobial susceptibility testing utilized disc diffusion and broth microdilution assays, while biocide susceptibility was assessed with various agents. The impact of an efflux pump inhibitor (NMP) on antibiotic susceptibility was evaluated. PCR screening for ARGs and EPGs was followed by DNA sequencing validation. MLST was performed using the Pasteur scheme. Most isolates demonstrated resistance to tested antibiotics, with varying levels of susceptibility to biocides. All isolates exhibited the intrinsic class D β-lactamase blaOXA-51, while acquired blaOXA-23 was present in all CRAB isolates. Among EPs, adeJ, abeD, amvA, and aceI were prevalent in almost all isolates, with adeB found in 93% of isolates and adeG, adeT1, adeT2, and qacEΔ1 displaying lower prevalence ranging from 65% to 79%. The most common STs were ST589 and ST2, accounting for 28.46% and 25.38% of isolates, respectively, followed by ST642 at 12.6%. These findings indicate that A. baumannii strains in Pakistan are resistant to antibiotics (excluding colistin and tigecycline) and may be developing biocide resistance, which could contribute to the selection and dissemination of multi-drug-resistant strains.

Enzyme-induced calcium carbonate precipitation (EICP) techniques are used in several disciplines and for a wide range of applications. In the oil and gas industry, EICP is a relatively new technique and is actively used for enhanced oil recovery applications, removal of undesired chemicals and generating desired chemicals in situ, and plugging of fractures, lost circulation, and sand consolidation. Many oil- and gas-bearing formations encounter the problem of the flow of sand grains into the wellbore along with the reservoir fluids. This study offers a detailed review of sand consolidation using EICP to solve and prevent sand production issues in oil and gas wells. Interest in bio-cementation techniques has gained a sharp increase recently due to their sustainable and environmentally friendly nature. An overview of the factors affecting the EICP technique is discussed with an emphasis on the in situ reactions, leading to sand consolidation. Furthermore, this study provides a guideline to assess sand consolidation performance and the applicability of EICP to mitigate sand production issues in oil and gas wells.

Uveal melanoma is one of the most common primary intraocular malignancies that accounts for about 85% of all ocular melanomas. The pathophysiology of uveal melanoma is distinct from cutaneous melanoma and has separate tumor profiles. The management of uveal melanoma is largely dependent on the presence of metastases, which confers a poor prognosis with a one-year survival reaching only 15%. Although a better understanding of tumor biology has led to the development of novel pharmacologic agents, there is increasing demand for minimally invasive management of hepatic uveal melanoma metastases. Multiple studies have already summarized the systemic therapeutic options available for metastatic uveal melanoma. This review covers the current research for the most prevalent locoregional treatment options for metastatic uveal melanoma including percutaneous hepatic perfusion, immunoembolization, chemoembolization, thermal ablation, and radioembolization.

Based on the perceptions of the local farmers, this study aims to assess the effects of socioeconomic factors and climatic change on the groundwater livelihood system, with a particular focus on in situ Persian wheels/dug wells. Farmers’ perceptions of climate change and how it is affecting their way of life in the Soan River Basin have also been evaluated to determine the most appropriate adaptive interventions. Information and literature about dug wells was unavailable, which stressed the need to carry out this survey. A structured close-ended questionnaire was designed and administered with as much quantitative data as possible. Random sampling opted for a 5 km buffer zone across the Soan River and its tributaries. Union councils having more than 50% of their area lying in the buffer zone were surveyed, and data was collected. Fifty UCs fell within this criterion, and six dug wells from each Union Council were surveyed. The results of our survey collecting local farmer’s perceptions determined that about 70% of respondents agreed about climate change in the Soan Basin of Pakistan, and 62% of farmers reported that climate change severely impacted their livelihood by affecting agricultural productivity and water availability. Ninety-two percent reported summer becoming hot, 72% highlighted that winters are becoming less cold, and 96% reported that average annual rainfall has decreased compared to 10 years before. About 72% of respondents indicated that available water in their dug wells had decreased, and 80% of respondents explained that their crop yield had decreased compared to 10 years before. Sixty percent preferred drip and 35% sprinkler irrigation as efficient water management practices to cope with water shortages. Ninety-five percent of farmers were ready to use solar pumps for irrigation to tame high pumping costs. The study recommends integrating solar pumping with drip and sprinkler irrigation systems to enhance farmers’ cropped area and productivity. These vulnerable farmers can enhance their resilience and profitability by adopting high-value agriculture (tunnel farming, off-season vegetables, etc.) instead of conventional crops.

We describe the seroprevalence of severe fever with thrombocytopenia syndrome virus (SFTSV) and the association of antibody occurrence with location, sex, and age among the human population in Pakistan. Our results indicate substantial activity of SFTSV and SFTSV-related viruses in this country.

We detected Crimean-Congo hemorrhagic fever virus infections in 4 provinces of Pakistan during 2017–2018. Overall, seroprevalence was 2.7% in humans and 36.2% in domestic livestock. Antibody prevalence in humans was highest in rural areas, where increased contact with animals is likely.

The rocks may be classified as Archie rocks or Non-Archie rocks, depending on the link between pore structure and resistivity of the rock. For carbonate rocks, keeping this factor in view, the applicability of Archie's law tends to be unreasonable and employing Archie's equation will ultimately lead to inaccurate estimates of the water saturation. Numerous investigators have reported models that forms a link between laboratory results and field well logs to determine water saturation in intricate pore systems. In case of complex systems, Archie's law fails to correctly define the resistivity-index curves. In addition, it is imperative to carry out investigations at lower saturation values in order to elaborate the non-Archie characteristics. This brings the dual and triple porosity conductivity models into the equation. As these models are essential in defining the considerable changes of the resistivity-index curves, both qualitatively and quantitatively. The linkage between the two models is depicted electrically in series or in parallel. Moreover, it is possible to have a combination of the two configurations. As a result, the experimental results can be modeled accurately using least parameters.This work presents two models to determine water saturation in carbonate rocks, containing dual and triple porosity systems. This study also investigates the impact of different influential parameters such as saturation exponents, conductivity ratios, and pore volume fraction of each network systems, on the new models. Finally, the effect of each parameter is individually studied and the sensitivity analysis on the RI curves is produced. A new approach to apply these models is also explained which requires the use of NMR log, mercury injection capillary pressure (MICP) measurement, and simple plotting techniques to determine the water saturation. The proposed new models help petrophysicists to estimate water saturation in Non-Archie rocks, containing double and triple porosity network systems. Keywords: Dual porosity, Triple porosity, Carbonate rocks, Water saturation models

Abstract An accurate prediction of well flowing bottom-hole pressure (FBHP) is highly needed in petroleum engineering applications such as for the field production optimization, cost per barrel of oil reduction, and quantification of workover remedial operations. A good number of empirical correlations and mechanistic models exist in the literature and are frequently used in oil industry to estimate FBHP. But majority of the empirical models were developed under a laboratory scale and are therefore inaccurate when scaled up for the field applications. The objective of this study is to present a new computational intelligence-based model to predict FBHP for a naturally flowing vertical well with multiphase flow. The present study shows that the accuracy of FBHP estimation using PSO-ANN is better than the conventional ANN model. A small average absolute percentage error of less than 2.1% is observed with the proposed model, while comparing the previous empirical correlations and mechanistic models on the same data gives more than 15% error. The new model is trained on a surface production data, which makes the prediction of FBHP in a real time. A group trend analysis tests were also carried out to assure that the proposed model is accurately capturing the underline physics behind the problem.

Abstract To obtain the high-quality crude oil from the surface processing plants, oil and gas separation plants parameters need to be optimized, by minimizing the intermediate components, flash from the crude oil during primary and secondary separation processes. The aim of this paper is to present an accurate methodology for predicting optimized separation parameters in the multistage crude oil production unit. The new proposed methodology determines the optimum pressures of separators in different stages of separation and consequently optimizes the operating conditions. A dynamic simulator is used to generate the data set for a designed production facility. Then, an optimization algorithm is used to build an optimum artificial neural network model to predict the optimum operating conditions that will maximize the liquid recovery. The ultimate objective of this work is to have an advisory system for optimizing liquid recovery from the production facilities.

The emergence of carbapenem-resistant Acinetobacter calcoaceticus-baumannii complex (CRACB) in clinical environments is a significant global concern. These critical pathogens have shown resistance to a broad spectrum of antibacterial drugs, including carbapenems, mostly due to the acquisition of various β-lactamase genes. Clinical samples (n = 1985) were collected aseptically from multiple sources and grown on blood and MacConkey agar. Isolates and antimicrobial susceptibility were confirmed with the VITEK-2 system. The modified Hodge test confirmed the CRACB phenotype, and specific PCR primers were used for the molecular identification of blaOXA and blaNDM genes. Of the 1985 samples, 1250 (62.9%) were culture-positive and 200 (43.9%) were CRACB isolates. Of these isolates, 35.4% were recovered from pus samples and 23.5% from tracheal secretions obtained from patients in intensive care units (49.3%) and medical wards (20.2%). An antibiogram indicated that 100% of the CRACB isolates were resistant to β-lactam antibiotics and β-lactam inhibitors, 86.5% to ciprofloxacin, and 83.5% to amikacin, while the most effective antibiotics were tigecycline and colistin. The CRACB isolates displayed resistance to eight different AWaRe classes of antibiotics. All isolates exhibited the blaOXA-51 gene, while blaOXA-23 was present in 94.5%, blaVIM in 37%, and blaNDM in 14% of the isolates. The blaOXA-51, blaOXA-23, and blaOXA-24 genes co-existed in 13 (6.5%) isolates. CRACB isolates with co-existing blaOXA-23, blaOXA-24, blaNDM, blaOXA-51 and blaVIM genes were highly prevalent in clinical samples from Pakistan. CRACB strains were highly critical pathogens and presented resistance to virtually all antibacterial drugs, except tigecycline and colistin.

A significant challenge for organisations is the timely identification of the abnormalities or deviations in their process executions. Abnormalities are generally due to missing vital aspects of a process or possession of unwanted behaviour in the process execution. Conformance analysis techniques examine the synchronisation between the recorded logs and the learned process models, but the exploitation of event logs for abnormality detection is a relatively under-explored area in process mining. In this paper, we proposed a novel technique for the identification of abnormalities in business process execution through the extension of available conformance analysis techniques. Non-traditional conformance analysis techniques are used to find correlations and discrepancies between simulated and observed behaviour in process logs. Initially, the raw event log is filtered into two variants, successful and failed, based upon the outcome of the instances. Successfully executed instances refer to an ideal conduct of process and are utilised to discover an optimal process model. Later, the process model is used as a behavioural benchmark to classify the abnormality in the failed instances. Abnormal behaviour is compiled grounded on three dimensions of conformance, control flow-based alignment, trace-level alignment and event-level alignment. For early predictions, we introduced the notion of conformance lifeline presenting the impact of varying fitness scores during process execution. We applied the proposed methodology to a real-world event log and presented several process-specific improvement measures in the discussion section.

The porosity of the petroleum reservoirs is considered one of the most important parameters in reserve estimation because it determines the effective volume of the hydrocarbon that is stored in the reservoir. Based on the reserve estimation, the development plan can be set and managed. Porosity can be determined in the laboratory which is the most expensive methods. Porosity also can be determined from the logs such as density, neutron, sonic, and NMR logs. There are a lot of uncertainties in the porosity estimation from wireline logs because it depends on many statistical analysis and also is affected by the logging environment and logging tools. The prediction of the porosity from different porosity logs using artificial intelligence (AI) methods validated with the laboratory measured values is the best method to determine an accurate value of the rock porosity.The objective of this research is to evaluate AI tools such as artificial neural network (ANN), Support vector machine (SVM) and Adaptive neuro fuzzy inference system (ANFIS) to predict the reservoir porosity based on wireline log data. More than 1700 field measurements of porosity with logs data were used for training and testing the AI techniques.The results obtained showed that ANN and ANFIS can be used to estimate the reservoir porosity based on log data with a high correlation coefficient (R) and low average absolute percentage error (AAPE). The main inputs required for porosity estimation are bulk density, neutron porosity, and sonic compressional time. The developed mathematical equation based on the weights and bias of the ANN model can be used to predict the reservoir porosity based on log data with a correlation coefficient of 0.98 and an AAPE less than 8%. The advantage of this work is that we extracted the mathematical model from the ANN that can be used directly to determine the porosity without the need for training and testing the data. The porosity estimation from the neutron-density crossplots, which is the current technique used by the industry, yielded 14.7% error. Keywords: Porosity, Artificial intelligence, Neural network, Carbonate reservoir, Logging

During the fracture stimulation of oil and gas wells, fracturing fluids are used to create fractures and transport the proppant into the fractured reservoirs. The fracturing fluid viscosity is responsible for proppant suspension, the viscosity can be increased through the incorporation of guar polymer and cross-linkers. After the fracturing operation, the fluid viscosity is decreased by breakers for efficient oil and gas recovery. Different types of enzyme breakers have been engineered and employed to reduce the fracturing fluid′s viscosity, but thermal stability remains the major constraint for the use of enzymes. The latest enzyme engineering approaches such as direct evolution and rational design, have great potential to increase the enzyme breakers’ thermostability against high temperatures of reservoirs. In this review article, we have reviewed recently advanced enzyme molecular engineering technologies and how these strategies could be used to enhance the thermostability of enzyme breakers in the upstream oil and gas industry.

Objectives: This study was performed to determine the presence of West Nile virus (WNV) in mosquito specimens and human blood donors in Pakistan. Methods: A total of 4150 mosquito specimens were collected using CO2-baited traps from five selected districts of Punjab Province, Pakistan. The mosquitoes were taxonomically identified using standard morphological keys, resulting in 166 pools. In addition, 1070 serum samples were collected from human blood donors. RNA was extracted from mosquito and human samples and screened for WNV using a reverse transcriptase PCR (RT-PCR). Results: None of the mosquito pools tested positive for WNV, whereas three samples from asymptomatic humans tested positive. To determine the WNV strains, partial sequences were compared against a global representation of 23 WNV sequences. The study strains were determined to come from WNV lineage 1. Conclusions: This study is novel in reporting the circulation of lineage 1 WNV in Pakistan. Given its ability to transmit from human to human via blood transfusion, this highlights the urgent need for nationwide surveillance to assess the distribution and impact of WNV in Pakistan. Determining the source of human infection will require more extensive mosquito sampling. Keywords: West Nile virus, Mosquitoes, Human, Pakistan

The process of well cleanup involves the removal of an impermeable layer of filter cake from the face of the formation. The inefficient removal of the filter cake imposes difficulty on fracturing operations. Filter cake’s impermeable features increase the required pressure to fracture the formation. In this study, a novel method is introduced to reduce the required breakdown pressure to fracture the formation containing the water-based drilling fluid filter cake. The breakdown pressure was tested for five samples of similar properties using different solutions. A simulated borehole was drilled in the core samples. An impermeable filter cake using barite-weighted drilling fluid was built on the face of the drilled hole of each sample. The breakdown pressure for the virgin sample without damage (filter cake) was 6.9 MPa. The breakdown pressure increased to 26.7 MPa after the formation of an impermeable filter cake. Partial removal of filter cake by chelating agent reduced the breakdown pressure to 17.9 MPa. Complete dissolution of the filter cake with chelating agents resulted in the breakdown pressure approximately equivalent to the virgin rock breakdown pressure, i.e., 6.8 MPa. The combined thermochemical and chelating agent solution removed the filter cake and reduced the breakdown pressure to 3.8 MPa. Post-treatment analysis was carried out using nuclear magnetic resonance (NMR) and scratch test. NMR showed the pore size redistributions with good communication between different pores after the thermochemical removal of filter cake. At the same time, there was no communication between the different pores due to permeability impairment after filter cake formation. The diffusion coupling through NMR scans confirmed the higher interconnectivity between different pores systems after the combined thermochemical and chelating agent treatment. Compressive strength was measured from the scratch test, confirming that filter cake formation caused added strength to the rock that impacts the rock breakdown pressure. The average compressive strength of the original specimen was 44.5 MPa that increased to 73.5 MPa after the formation of filter cake. When the filter cake was partially removed, the strength was reduced to 61.7 MPa. Complete removal with chelating agents removed the extra strength that was added due to the filter cake presence. Thermochemical and chelating agents resulted in a significantly lower compressive strength of 25.3 MPa. A numerical model was created to observe the reduction in breakdown pressure due to the thermochemical treatment of the filter cake. The result presented in this study showed the engineering applications of thermochemical treatment for filter cake removal.

Current oil prices and global financial situations underline the need for the best engineering practices to recover remaining oil from unconventional hydrocarbon reservoirs. These hydrocarbon reservoirs are mostly situated in deep and overpressured formations, with high rock strength and integrity. Breakdown pressure of the rock is a function of their tensile strength and in situ stresses acting on them. Fracturing stimulation techniques become challenging when treating these types of rocks, and many cases approached to the operational limits. This leaves a small operational window to initiate and place hydraulic fractures. In this study, a new methodology to reduce the breakdown pressure of the high stressed rock is presented. The new method enables the fracturing of high stressed rocks more economically and efficiently. Fracturing experiments were carried out on different blocks, and the breakdown pressure was measured by creating a simulated borehole at the center of the block. Thermochemical fluids were injected to create the microfractures. These microfractures improved the permeability and porosity and reduced the elastic strength of the subjected samples prior to the main hydraulic fracturing job. The posttreatment experimental analysis confirmed the presence of microfractures which were originated due to the pressure pulse generated from the thermochemical reaction. The results of this study showed that the newly formulated method of thermochemical fracturing reduced the breakdown pressure by 38% in slim borehole blocks and 60% in large borehole blocks. Results also showed that the breakdown time to initiate the fractures was reduced to 19% in slim borehole blocks and 17% in large borehole blocks. The reduction in breakdown pressure and breakdown time happened due to the creation of microfractures by the pressure rise phenomenon in a new thermochemical fracturing approach.

Real-world business processes are dynamic, with event logs that are generally unstructured and contain heterogeneous business classes. Process mining techniques derive useful knowledge from such logs but translating them into simplified and logical segments is crucial. Complexity is increased when dealing with business processes with a large number of events with no outcome labels. Techniques such as trace clustering and event clustering, tend to simplify the complex business logs but the resulting clusters are generally not understandable to the business users as the business aspects of the process are not considered while clustering the process log. In this paper, we provided a multi-stage hierarchical framework for business-logic driven clustering of highly variable process logs with extensively large number of events. Firstly, we introduced a term contrail processes for describing the characteristics of such complex real-world business processes and their logs presenting contrail-like models. Secondly, we proposed an algorithm Novel Hierarchical Clustering (NoHiC) to discover business-logic driven clusters from these contrail processes. For clustering, the raw event log is initially decomposed into high-level business classes, and later feature engineering is performed exclusively based on the business-context features, to support the discovery of meaningful business clusters. We used a hybrid approach which combines rule-based mining technique with a novel form of agglomerative hierarchical clustering for the experiments. A case-study of a CRM process of the UK’s renowned telecommunication firm is presented and the quality of the proposed framework is verified through several measures, such as cluster segregation, classification accuracy, and fitness of the log. We compared NoHiC technique with two trace clustering techniques using two real world process logs. The discovered clusters through NoHiC are found to have improved fitness as compared to the other techniques, and they also hold valuable information about the business context of the process log.

Co and Cr Co-doped Titanium Dioxide, Ti0.9Cr.1-xCoxO2 (x=0.0, 0.02, 0.04, 0.06, 0.08 and .10), Dilute magnetic semiconductors (DMSs) were synthesized by solid state reaction method at annealing temperature of 1050°C for six hours. XRD patterns confirmed the single phase rutile. The rutile structure was also confirmed by Raman spectroscopy technique. Grain sizes were measured by Scanning Electron Microscope (SEM). The samples were examined for its magnetic property using Vibrating Sample Magnetometer (VSM) at room temperature which indicated Paramagnetic behavior. Electrical resistivity as a function of temperature was measured using four probe technique. Band gap energy was calculated by UV Visible spectroscopy. Both electrical resistivity measurements and band gap measurements confirmed the semiconducting nature of Ti0.9Cr.1-xCoxO2 series. [ABSTRACT FROM AUTHOR]