Search Results (385)

Bioethanol manifests an extraordinary potential to overcome the severe energy crises and reliance on fossil fuels, yet it supports the sustainable and cost-effective production of fuels for automobile engines and contributes to the reduction of greenhouse gas (GHG) emissions and other global climate-related challenges. The present study examines the potential of Mixed Lignocellulosic Biomass (MLB) as a sustainable feedstock for the consistent year-round production of bioethanol. The primary MLB sources considered in this research to underscore the significance of this heterogeneous strategy include sweet sorghum bagasse (SSB), sugarcane bagasse (SCB), and date palm trunk (DPT). Each of the three feedstocks, i.e., SSB, SCB, and DPT, were individually subjected to alkaline pretreatment, a step aimed at breaking down structural barriers and facilitating greater release of fermentable sugars during fermentation. Likewise, the alkaline-pretreated biomasses were subjected to simultaneous saccharification and fermentation (SSF) for 96 h, both individually as well as in various combined proportions. Individually, pretreated sweet sorghum bagasse (SSB) fibers produced the highest ethanol concentration, of 30.79 ± 0.44 g/L; an ethanol yield of 0.40 ± 0.62 g/g; an ethanol productivity of 0.42 ± 0.87 g/L/h; and a theoretical ethanol yield of 79.81% at 72 h. In contrast, the combination of MLB (50% of pretreated SSB and 50% of DPT fibers) produced a significantly higher ethanol concentration of 31.47 ± 0.57 g/L and an ethanol productivity of 0.653 ± 0.24 g/L/h in much less time, i.e., 48 h of SSF fermentation. The empirical data confirms that MLB offers a sustainable paradigm for ethanol biosynthesis by curtailing fermentation time and optimizing economic and operational efficacy. Full article

The aim of this manuscript is to introduce the fractional integral inequalities of H-H types via multiplicative (Antagana-Baleanu) A-B fractional operators. We also provide the fractional version of the H-H type of the product and quotient of multiplicative superquadratic and multiplicative subquadratic functions via the same operators. Superquadratic functions, have stronger convexity-like behavior. They provide sharper bounds and more refined inequalities, which are valuable in optimization, information theory, and related fields. The use of multiplicative fractional operators establishes a nonlinear fractional structure, enhancing the analytical tools available for studying dynamic and nonlinear systems. The authenticity of the obtained results are verified by graphical and numerical illustrations by taking into account some examples. Additionally, the study explores applications involving special means, special functions and moments of random variables resulting in new fractional recurrence relations within the multiplicative calculus framework. These contributions not only generalize existing inequalities but also pave the way for future research in both theoretical mathematics and real-world modeling scenarios. Full article

In Pakistan and most other developing nations, the residential building sector is one of the highest energy-consuming domains. The residential sector has the highest share of 50% of final electricity use of the country. Though Energy Conservation Building Codes (ECBC-2023) provide structured energy guidelines, no work has been performed to quantify the actual energy-saving potential of code-compliant retrofits in residential buildings. This study investigates the performance of ECBC-compliant retrofitting strategies for residential buildings under Pakistan’s diverse climatic conditions. The Passive House Planning Package (PHPP), a validated simulation tool, was used to assess energy performance improvements through building envelope interventions such as thermal insulation, solar shading, window glazing, and optimal orientation. Field data were collected from three representative cities, Multan (hot desert), Taxila (humid subtropical), and Quetta (cold semi-arid), to simulate both conventional and energy-efficient building scenarios. The results showed substantial seasonal energy savings in all three climates. During the heating period, energy savings were 48%, 50%, and 60% for Taxila, Multan, and Quetta, respectively. Similarly, energy savings during the cooling season were 44%, 33%, and 16%. Life cycle economic analysis revealed that these retrofits yielded Net Present Values (NPVs) of USD 752 (Taxila), USD 1226 (Multan), and USD 1670 (Quetta) over a 30-year period, with discounted payback periods ranging from 6 to 10 years. Furthermore, a life cycle assessment demonstrated that retrofitted buildings yielded up to 26% reduction in overall carbon emissions, combining both embodied and operational sources. The findings highlight that ECBC-2023 is not only a technically viable solution for energy savings but also financially attractive in residential retrofitting. By incorporating localized climate responsiveness into ECBC-compliant building design, the study provides a practical roadmap for achieving Pakistan’s energy efficiency goals. Additionally, the outcomes serve as a basis for informing policy initiatives, supporting building code adaptation, and raising public awareness of sustainable housing practices. Full article

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) raced around the world across different populations; there needs to be a consolidated effort to understand the divergence of the epidemiology of SARS-CoV-2. Population-based epidemiological characteristics studies measure the extent of SARS-CoV-2 infection in a country. The current research study was designed to report epidemiological data from Pakistan. For this purpose, 246 SARS-CoV-2-infected patients were included in the study. For SARS-CoV-2 confirmation, viral samples were collected from all the study participants; SARS-CoV-2 infection was confirmed by viral nucleic acid detection using a nucleic acid detection kit. After SARS-CoV-2 confirmation, all the study participants were interviewed for epidemiological data through a detailed questionnaire. The study results showed that the disease ratio was higher between 30 and 59 years (51.21%) of age. The male ratio (55.28%) was higher compared to the female ratio (44.71%). The patients’ illiteracy and low socioeconomic status were 32.52% and 59.75%, respectively. The majority of the patients (97.56%) had cough, smell or taste disturbance (79.67%), or fever (76.42%), and 70.73% had fatigue. For comorbidities, a higher ratio was observed for diabetes (38.61%), hypertension (36.17%), and respiratory disease (16.26%). The vaccination status analysis revealed that 51.21% of patients had not received routine immunizations, and 65.5% were un-vaccinated against SARS-CoV-2. Notably, not a single patient was vaccinated for influenza vaccine. The current research study concluded that SARS-CoV-2 was more prevalent in individuals who were middle aged, male, and had low socio-economic status. The most common symptoms were cough, smell or taste disturbance, and fever. The patients’ vaccination status highlights a critical gap in preventive healthcare and shows the need to strengthen vaccination awareness and accessibility in the population to reduce vulnerability to future outbreaks. Future research should focus on investigating the impact of COVID-19 outcomes on comorbidities such as diabetes and hypertension. Full article

Background/Objectives: Metabolic syndrome (MetS) is a multifactorial condition characterized by abdominal obesity, dyslipidemia, insulin resistance, hypertension, and chronic inflammation. As its global prevalence rises, there is increasing interest in natural, multi-targeted approaches to manage MetS. Curcuma longa Linn. (turmeric), especially its active compound curcumin, has shown therapeutic promise in preclinical studies. This systematic review and meta-analysis evaluated the effects of Curcuma longa and its derivatives on MetS-related outcomes in rodent models. Methods: A comprehensive search was conducted across six databases (PubMed, Scopus, AMED, LILACS, MDPI, and Google Scholar), yielding 47 eligible in vivo studies. Data were extracted on key metabolic, inflammatory, and oxidative stress markers and analyzed using random-effects models. Results were presented as mean differences (MD) with 95% confidence intervals (CI). Results: Meta-analysis showed that curcumin significantly reduced body weight (rats: MD = −42.10; mice: MD = −2.91), blood glucose (rats: MD = −55.59; mice: MD = −28.69), triglycerides (rats: MD = −70.17; mice: MD = −24.57), total cholesterol (rats: MD = −35.77; mice: MD = −52.61), and LDL cholesterol (rats: MD = −69.34; mice: MD = −42.93). HDL cholesterol increased significantly in rats but not in mice. Inflammatory cytokines were markedly reduced, while oxidative stress improved via decreased malondialdehyde (MDA) and elevated superoxide dismutase (SOD) and catalase (CAT) levels. Heterogeneity was moderate to high, primarily due to variations in curcumin dosage (ranging from 10 to 500 mg/kg) and treatment duration (2 to 16 weeks) across studies. Conclusions: This preclinical evidence supports Curcuma longa as a promising functional food component for preventing and managing MetS. Its multi-faceted effects warrant further clinical studies to validate its translational potential. Full article

Extrapulmonary tuberculosis (EPTB) remains diagnostically challenging due to its paucibacillary nature and variable presentation. Xpert and culture are limited in EPTB diagnosis due to sampling challenges, low sensitivity, and long turnaround times. This study evaluated the performance of the MPT64 antigen detection test for diagnosing EPTB, particularly tuberculous lymphadenitis (TBLN) and tuberculous pleuritis (TBP), in a high-TB, low-HIV setting. Conducted at Gulab-Devi Hospital, Lahore, Pakistan, this study evaluated the MPT64 test’s performance against conventional diagnostic methods, including culture, histopathology, and the Xpert MTB/RIF assay. Lymph node biopsies were collected, and cell blocks were made from aspirated pleural fluid from patients clinically presumed to have EPTB. Of 338 patients, 318 (94%) were diagnosed with EPTB. For TBLN, MPT64 demonstrated higher sensitivity (84%) than Xpert (48%); for TBP, the sensitivity was 51% versus 7%, respectively. Among histopathology-confirmed TBLN cases, MPT64 outperformed both culture and Xpert (85% vs. 58% and 47%). Due to the low number of non-TB cases, specificity could not be reliably assessed. The MPT64 test shows promise as a rapid, sensitive diagnostic tool for EPTB, particularly TBLN, in routine settings. While sensitivity is notably superior to Xpert, further studies are needed to evaluate its specificity and broader diagnostic utility. Full article

Reservoir-induced landslides threaten infrastructures and downstream communities, making continuous deformation monitoring vital. Time-series InSAR, notably the SBAS algorithm, provides high-precision surface-displacement mapping but suffers from voids due to layover/shadow effects and temporal decorrelation. Existing deep-learning approaches often operate on fixed-size patches or ignore irregular spatio-temporal dependencies, limiting their ability to recover missing pixels. With this objective, a hybrid spatio-temporal Graph Attention (ST-GAT) framework was developed and trained on SBAS-InSAR values using 24 influential features. A unified spatio-temporal graph is constructed, where each node represents a pixel at a specific acquisition time. The nodes are connected via inverse distance spatial edges to their K-nearest neighbors, and they have bidirectional temporal edges to themselves in adjacent acquisitions. The two spatial GAT layers capture terrain-driven influences, while the two temporal GAT layers model annual deformation trends. A compact MLP with per-map bias converts the fused node embeddings into normalized LOS estimates. The SBAS-InSAR results reveal LOS deformation, with 48% of missing pixels and 20% located near the Dasu dam. ST D-GAT reconstructed fully continuous spatio-temporal displacement fields, filling voids at critical sites. The model was validated and achieved an overall R² (0.907), ρ (0.947), per-map R² ≥ 0.807 with RMSE ≤ 9.99, and a ROC-AUC of 0.91. It also outperformed the six compared baseline models (IDW, KNN, RF, XGBoost, MLP, simple-NN) in both RMSE and R². By combining observed LOS values with 24 covariates in the proposed model, it delivers physically consistent gap-filling and enables continuous, high-resolution landslide monitoring in radar-challenged mountainous terrain. Full article

Extremophilic microorganisms offer an untapped potential for producing unique bioactive metabolites with therapeutic applications. In the current study, bacterial isolates were obtained from samples collected from Chamalang cave located in Kohlu District, Balochistan, Pakistan. The cave-derived isolate C1 (Rhodococcus jialingiae) exhibits prominent antibacterial activity against multidrug-resistant pathogens (MDR), including Escherichia coli, Staphylococcus aureus, and Micrococcus luteus. It also demonstrates substantial antioxidant activity, with 71% and 58.39% DPPH radical scavenging. Optimization of physicochemical conditions, such as media, pH, temperature, and nitrogen and carbon sources and concentrations substantially enhanced both biomass and metabolite yields. Optimal conditions comprise specialized media, a pH of 7, a temperature of 30 °C, peptone (1.0 g/L) as the nitrogen source, and glucose (0.5 g/L) as the carbon source. HPLC and QTOF-MS analyses uncovered numerous metabolites, including a phenolic compound, 2-[(E)-3-hydroxy-3-(4-methoxyphenyl) prop-2-enoyl]-4-methoxyphenolate, Streptolactam C, Puromycin, and a putative aromatic polyketide highlighting the C1 isolate chemical. Remarkably, one compound (C₁₄H₃₆N₇) demonstrated a special molecular profile, signifying structural novelty and warranting further characterization by techniques such as ¹H and ¹³C NMR. These findings highlight the biotechnological capacity of the C1 isolate as a source of novel antimicrobials and antioxidants, linking environmental adaptation to metabolic potential and supporting natural product discovery pipelines against antibiotic resistance. Full article

The determination of the live body weight of camels (required for their successful breeding) is a rather difficult task due to the problems with handling and restraining these animals. Therefore, the main aim of this study was to predict the ABW of eight indigenous camel (Camelus dromedarius) breeds of Pakistan (Bravhi, Kachi, Kharani, Kohi, Lassi, Makrani, Pishin, and Rodbari). Selected productive (hair production, milk yield per lactation, and lactation length) and reproductive (age of puberty, age at first breeding, gestation period, dry period, and calving interval) traits served as the predictors. Six data mining methods [classification and regression trees (CARTs), chi-square automatic interaction detector (CHAID), exhaustive CHAID (EXCHAID), multivariate adaptive regression splines (MARSs), MLP, and RBF] were applied for ABW prediction. Additionally, hierarchical cluster analysis with Euclidean distance was performed for the phenotypic characterization of the camel breeds. The highest Pearson correlation coefficient between the observed and predicted values (0.84, p < 0.05) was obtained for MLP, which was also characterized by the lowest root-mean-square error (RMSE) (20.86 kg), standard deviation ratio (SD_ratio) (0.54), mean absolute percentage error (MAPE) (2.44%), and mean absolute deviation (MAD) (16.45 kg). The most influential predictor for all the models was the camel breed. The applied methods allowed for the moderately accurate prediction of ABW (average R² equal to 65.0%) and the identification of the most important productive and reproductive traits affecting its value. However, one important limitation of the present study is its relatively small dataset, especially for training the ANN (MLP and RBF). Hence, the obtained preliminary results should be validated on larger datasets in the future. Full article

Research on energy demand is advancing, with the addition of nanomaterials in anaerobic digestion increasing stability, accelerating hydrolysis, and reducing microbial inhibition. However, further research is needed to determine the mechanisms, ideal dosages, and long-term impacts. This work used continuous stir tank reactors (CSTRs) to experimentally examine the biocompatibility of iron oxide nanoparticles (Fe₃O₄-NPs) at a concentration of 75 mg/L at various organic loading rates (OLRs) of 0.3, 0.8, and 1.3 gVS/L.d (CSTRs). The efficiency of the reactors was observed by considering various parameters, such as pH, soluble chemical oxygen demand (sCOD), TVFA formation and degradation, total solids (TS), and volatile solids (VS) removal, as well as methane (CH₄) generation. Hence, it was found that the reactor with added NPs (R1) yielded an optimum 725.9 mL/gVS of CH₄ and this was achieved at the lowest OLR of 0.3 gVS/Ld. However, another reactor (R2, without NPs), exhibited more stabilized results, ranging from 372.8 to 424.4 mL/gVS at 0.3 to 1.3 gVS/Ld of OLR, respectively. Therefore, in R1, the maximum removal of sCOD, TVFAs, and VS was achieved at 90%, 74%, and 93%, respectively, as compared to R2. Full article

Humic acid (HA), a major component of soil organic matter, is a naturally occurring macromolecule formed through the decomposition of plant and microbial residues. Its molecular structure comprises functional groups such as carboxyl, phenolic, hydroxyl, and carbonyl functional groups, which enable HA to interact with soil particles, nutrients, and biological systems. These interactions significantly contribute to soil fertility and overall plant productivity. Functionally, HA enhances soil health by increasing cation exchange capacity, improving water retention, and promoting the formation and stabilization of soil aggregates. In addition to its role in soil conditioning, HA is essential in mitigating plant stress. It achieves this by modulating antioxidant enzyme activity, stabilizing cellular membranes, and alleviating the adverse effects of abiotic stressors such as salinity, drought, and heavy metal toxicity. This review highlights the structural characteristics of HA, its structure-based functions, and the mechanisms involved in plant stress alleviation. Additionally, we explore how HA can be modified through physical, chemical, and biological approaches to enhance its agronomic performance. These modifications are designed to improve HA agronomic efficiency by increasing nutrient bioavailability, reducing environmental losses through minimized leaching and volatilization, and supporting sustainable agricultural practices. Overall, this review underscores the multifaceted roles of HA in promoting plant resilience to environmental stress, highlighting its potential as a key agent in the development of sustainable and eco-friendly crop production systems. Full article

This study examines culture-led urban regeneration as a strategy for revitalizing Meezan Chowk, a historically significant yet deteriorating public space in Quetta, Pakistan. Once a central site of social and commercial exchange, the area suffered from infrastructural decline, overcrowding, and the erosion of its architectural identity. The research proposes a design intervention to restore the site’s heritage value while enhancing its functional and social relevance. A qualitative approach is adopted, incorporating surveys, focus group discussions, and site observations to assess user needs and spatial dynamics. A SWOT analysis serves as the analytical framework to identify the site’s internal strengths and weaknesses, as well as external opportunities and threats. By utilizing the Geographic Information Systems (GIS) and OpenStreetMap data, further information can enhance understanding of the site’s urban morphology. The proposed design integrates vernacular elements, such as arched facades, shaded corridors, and communal courtyards, with contemporary features, including cafes, local artisan shops, and accessible public amenities. Full article

Metabolic syndrome (MetS) is a complex condition defined by central obesity, insulin resistance, dyslipidemia, and systemic inflammation. Kefir, a fermented beverage rich in probiotics and beneficial compounds, has emerged as a functional food that may offer metabolic advantages. Nevertheless, preclinical results have been variable. This systematic review and meta-analysis aimed to assess the influence of kefir and its derived compositions on parameters associated with MetS, inflammation, and oxidative stress in rodent studies. A comprehensive literature search was conducted in PubMed, Scopus, AMED, and LILACS through June 2024. Eligible studies involving kefir interventions in rodent MetS models were included. Data extraction followed PRISMA guidelines, with the risk of bias assessed using the CAMARADES and SYRCLE tools. Meta-analyses were performed with a random effects model. Thirty-eight studies involving 1462 rodents (mice and rats) were analyzed. Kefir significantly reduced body weight gain in both mice (MD = –3.33; 95% CI: –4.89 to –1.77) and rats (MD = –41.53; 95% CI: –54.33 to –28.72). In mice, triglycerides and LDL-C levels decreased significantly; in rats, kefir lowered total cholesterol and triglycerides. Insulin levels were reduced (MD = –0.69; 95% CI: –1.16 to –0.22), suggesting improved insulin sensitivity. Several studies also reported reductions in TNF-α, IL-1β, and IL-6. Despite promising results, the high heterogeneity and methodological variability emphasize the need for standardized preclinical protocols and clinical validation. These findings support the role of kefir as a functional food for metabolic health promotion. Full article

The Mega-Sub Controlled Structure System (MSCSS) represents an innovative category of seismic-resistant super high-rise building structural systems, and exploring its damage mechanisms and identification methods is crucial. Nonetheless, the prevailing methodologies for establishing criteria for structural damage are deficient in providing a lucid and comprehensible representation of the actual damage sustained by edifices during seismic events. To address these challenges, the present study develops a finite element model of the MSCSS, conducts nonlinear time-history analyses to assess the MSCSS’s response to prolonged seismic motion records, and evaluates its damage progression. Moreover, considering the genuine damage conditions experienced by the MSCSS, damage working scenarios under seismic forces were formulated to delineate the damage patterns. A convolutional neural network recognition framework based on stacking ensemble learning is proposed for extracting damage features from the temporal response of structural systems and achieving damage classification. This framework accounts for the temporal and spatial interrelations among sensors distributed at disparate locations within the structure and addresses the issue of data imbalance arising from a limited quantity of damaged samples. The research results indicate that the proposed method achieves an accuracy of over 98% in dealing with damage in imbalanced datasets, while also demonstrating remarkable robustness. Full article

Microorganisms play an essential role in the biogeochemical processes of macroalgal cultivation ecosystems by participating in a complex network of interactions, significantly influencing the growth and development of macroalgae. This study used bibliometric analysis and VOSviewer based on Web of Science data to provide an overview by tracing the developmental footprint of the technology. Countries, institutions, authors, keywords, and key phrases were tracked and mapped accordingly. From 1 January 2003 to 31 December 2023, 619 documents by 2516 authors from 716 institutions in 51 countries were analyzed. Keyword co-occurrence network analysis revealed five main areas of research on microbes in macroalgal cultivation ecosystems: (1) identification of microbial species and functional genes, (2) biogeochemical cycling of carbon in microbial communities, (3) microbial influences on macroalgae growth and development, (4) bioactivities, and (5) studies based on database. Thematic evolution and map research emphasized the centrality of microbial diversity research in this direction. Over time, the research hotspots and the core scientific questions of the microorganisms in the macroalgal cultivation ecosystems have evolved from single-organism interactions to the complex dynamics of microbial communities. The application of high-throughput techniques had become a hotspot, and the adoption of systems biology approaches had further facilitated the integrated analysis of microbial community composition and function. Our results provide valuable guidance and information for future researches on algal–bacterial interactions and microbe-driven carbon cycling in coastal ecosystems. Full article