Potential Trends Research Articles

A key factor in monitoring cannabis consumption trends through wastewater analysis: Partitioning of THC[sbnd]COOH between the liquid and solid phase of influent wastewater

Current wastewater-based epidemiology (WBE) studies are predominantly focused on the analysis of urinary biomarkers present in the liquid phase of influent wastewater (IWW). This approach systematically underestimates less polar metabolites, such as cannabis biomarkers. These biomarkers can potentially sorb to and desorb from suspended particulate matter (SPM) present in IWW. This study investigates the bidirectional partitioning of THCCOOH between the liquid phase and SPM of IWW by performing multiple sorption experiments using THCCOOH-D9 as a surrogate due to the unavailability of blank SPM and blank IWW. In addition, this study involves the analysis of IWW collected from eight wastewater treatment plants (WWTP) (n = 56) across four European countries, where raw IWW, the liquid phase and SPM were separately analysed to identify potential trends in the fraction of THCCOOH in the SPM between and withing the examined locations. Based on the performed sorption experiments, bidirectional partitioning of THCCOOH between the liquid phase and SPM was noted, showing partition between both phases when only one of the two phases was spiked. It was illustrated that the concentration of SPM had a notable influence on the THCCOOH partitioning between both phases. In addition to the inter location variability (average THCCOOH present in the SPM ranged 31–59 %), a substantial intra location variation was also observed, e.g., in one location ranged 17–58 %. While the determination of a correction factor for the amount of THCCOOH present in SPM would be ideal, this is challenging, since the amount of SPM is not fixed in all IWW samples. Although SPM has influence on the THCCOOH partition, no correlation (p value Spearman correlation = 0.3160) was observed between the SPM concentration and the fraction of THCCOOH in the solid phase. Moreover, the collection of homogenized samples is difficult, and the time required to reach an equilibration in partitioning of THCCOOH between both IWW phases remains unclear. Due to i) the large inter-and intra-location variation of THCCOOH present in the SPM, ii) the variability in SPM concentration in IWW samples, and iii) the time required to reach a partitioning equilibration, an analytical procedure based on liquid-liquid extraction (LLE) that considers both the liquid phase and SPM of IWW is recommended to reduce the overall uncertainty for THCCOOH measurement in IWW. It was illustrated that this extraction method is capable to recover the total concentration of THCCOOH in both phases.

Half a century of spread: how trends can inform the phenology of Undaria pinnatifida in California.

The potential for non-native species to outcompete native species, change ecosystem dynamics and decrease biodiversity necessitates an understanding of their ecological role. Non-native seaweed species (NNSS) can be particularly impactful due to their cryptic life cycles, high fecundity, and tolerance to stressors which could allow rapid spread across coastlines. This literature review summarizes a few well known NNSS in California with a focus on using global literature on Undaria pinnatifida to inform potential trends of habitat use, dispersal, and phenology in this region. Globally, we found that Undaria is widely documented in bays and harbors but there are documented cases of it establishing populations in coastal habitats in exposed rocky reef ecosystems, including California. Using data on thermal tolerance for U. pinnatifida in its native range I found the sea surface temperatures (SST) throughout the west coast of the United States during 2019 are within the thermal tolerance of Undaria with the best SST for gametophytes occurring most frequently in southern California. Using data from the literature, I estimated the potential for Undaria to disperse from known populations in San Diego, CA. These data suggest that Undaria has the potential to disperse into open coastal habitats in this region. This study provides a case for further using pre-existing literature from other regions to guide research conducted in regions of interest that can inform management decisions.

Detection of gamma-ray burst Amati relation based on Hubble data set and Pantheon+ samples

Using gamma-ray bursts as standard candles for cosmological parameter constraints rely on their empirical luminosity relations and low-redshift calibration. In this paper, we examine the Amati relation and its potential corrections based on the A118 sample of higher-quality gamma-ray bursts, using both Hubble data set and Pantheon+ samples as calibration samples in the redshift range of z<1.965\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$z<1.965$$\\end{document}. In calibrating gamma-ray bursts using these two datasets, we employ Gaussian processes to obtain corresponding Hubble diagrams to avoid the dependence on cosmological models in the calibration process. We first divided the low-redshift sample of GRBs into two bins and examined the Amati relation and its potential modifications. We found that under both calibrations, the Amati relation did not show evidence of redshift evolution (68%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\%$$\\end{document} confidence level). For the other two Amati relations that include redshift evolution terms, the central values of the redshift evolution coefficients deviated from 0, but due to the limitations of the sample size and the increase in the number of parameters, most of the redshift evolution coefficients were not able to be excluded from 0 at the 1σ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\sigma $$\\end{document} level. Therefore, to assess their situation across the entire redshift range, we employed MCMC to globally fit three types of Amati relations. By computing AIC and BIC, we found that for the GRB A118 sample, the standard Amati relation remains the most fitting empirical luminosity formula, and no potential redshift evolution trend was observed for two different low-redshift calibrating sources.

Incidence of Clinically Diagnosed Psoriatic Arthritis in Sweden.

Prior incidence estimates of psoriatic arthritis (PsA) vary considerably. We aimed to assess the annual incidence of clinically diagnosed PsA among adults in Sweden in 2014-2016, overall and stratified by age/sex/education/geography, and to investigate potential time trends in incidence in 2006-2018. Use of disease-modifying antirheumatic drugs (DMARDs) during the 2 years after diagnosis was also examined. Patients (aged ≥ 18 years) with incident clinically diagnosed PsA in Sweden were identified from the National Patient Register (NPR) and/or the Swedish Rheumatology Quality Register (SRQ). Population statistics, stratification variables, and DMARD information were retrieved from other nationwide registers. Incidence was estimated according to a base case (BC) definition (ie, ≥ 1 main International Classification of Diseases, 10th revision, diagnosis of PsA [L40.5/M07.0-M07.3] from rheumatology/internal medicine in NPR, or a PsA diagnosis in SRQ during the relevant year, and no prior such diagnoses) and 4 different sensitivity analysis case definitions. The mean annual incidence of clinically diagnosed PsA among adults in Sweden in 2014-2016 was estimated at 21.77 per 100,000 person-years (PYs) at risk, according to the BC definition; 17.41 per 100,000 PYs at risk after accounting for diagnostic misclassification; and 15.78 to 28.83 per 100,000 PYs at risk across all sensitivity analyses. Incidence was slightly higher in female individuals, was lower in those with higher education (aged > 12 years), and peaked during the ages of 50 to 59 years. No apparent increasing or decreasing time trend was observed in 2006-2018. Within 2 years of diagnosis, 71.03% of patients had received DMARD therapy (22.37% biologic or targeted synthetic DMARDs). From 2014 to 2016, the annual incidence of clinically diagnosed PsA in the adult Swedish population was approximately 20 per 100,000 PYs at risk. Two years after diagnosis, almost three-quarters of patients had received DMARD therapy.

Future changes in agrometeorological extremes in the southern Mediterranean region: When and where will they affect croplands and wheatlands?

Climate change and extremes are increasingly threatening food security, especially in the Global South. Here, we examine how croplands and wheatlands of the southern Mediterranean region could be affected by projected changes in agrometeorological extremes over the 21st century. We use 17 bias-corrected climate models from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) to identify potential trends and assess the time of emergence of significant changes in agrometeorological extremes under the Shared Socioeconomic Pathway (SSP3–7.0). We note that simulated historical trends in agrometeorological extremes closely match observed trends, here derived from ERA5land, over croplands. Our analysis of CMIP6 projected scenarios reveals a consistent rise in heat intensity, drought intensity, and the frequency of compound dry and hot (D5/H95) days. While a reduction in frost intensity, combined with fewer wet and cold (W95/C5) and dry and cold (D5/C5) events offer some mitigation potential, concerns about water scarcity due to heightened heat and drought stresses may overshadow these benefits. These changes in agrometeorological extremes are projected to emerge in the near- and mid-term future (by 2030 and 2050). We also note that the projected decreases in cold extremes affect smaller agricultural regions than the increases in extreme heat. We find higher likelihoods of negative agrometeorological impacts over croplands and wheatlands throughout the 21st century, which could significantly challenge crop yields and agricultural sustainability. Without proactive adaptation and mitigation strategies, food security could come increasingly under threat in a changing climate in the southern Mediterranean region.

Sodium-glucose cotransporter 2 inhibitors and the risk of Parkinson disease in real-world patients with type 2 diabetes.

Diabetes increases the risk of Parkinson disease (PD). Sodium-glucose cotransporter 2 (SGLT2) inhibitors, a new glucose-lowering therapeutic class, have shown neuroprotective effects in mechanistic studies. However, the association between SGLT2 inhibitors and PD risk in real-world populations with type 2 diabetes (T2D) remains unclear. The aim was to assess the association between SGLT2 inhibitors and the risk of PD in older populations with T2D. This retrospective cohort analysis used Medicare claims data from 2016 to 2020 to identify fee-for-service beneficiaries ≥65 years diagnosed with T2D and without pre-existing PD. The initiation of an SGLT2 inhibitor was compared with that of a dipeptidyl peptidase-4 (DPP4) inhibitor. The outcome was the first incident PD ever since the date initiating either an SGLT2 inhibitor or a DPP4 inhibitor. We employed a 1:1 propensity score matching to balance the baseline covariates between treatment groups, including sociodemographics, comorbidities and co-medications. We applied Cox regression models to assess the effect of SGLT2 inhibitors versus DPP4 inhibitors on incident PD. Of 89 330 eligible Medicare beneficiaries (mean age: 75 ± 7 years, 52% women), 0.6% (n = 537) had incident PD over the follow-up. After 1:1 propensity matching, the PD incidence was 2.5 and 3.5 events per 1000 person-years in the SGLT2 inhibitor group and DPP4 inhibitor group, respectively. The SGLT2 inhibitor group was associated with a significantly lower risk of incident PD than the DPP4 inhibitor group (hazard ratio: 0.70 [95% confidence interval: 0.55-0.89]). There is a potential trend that the risk reduction in incident PD was profound in non-Hispanic Black individuals and insulin users. Compared to DPP4 inhibitors, SGLT2 inhibitors were associated with a significantly lower risk of incident PD in older populations with T2D.

Point and interval forecasting approach for short-term urban subway passenger flow based on residual term decomposition and fuzzy information granulation

Accurate forecasting information of short-term subway passenger flow is an important scientific reference for daily operations and urban management. The rapid time-varying nature of subway passenger flow caused by various factors that affect travel behavior poses a huge challenge to accurate forecasting. The complexity and uncertainty of data mainly focus on residual terms that deeply reflect the fluctuations. Reasonably mining the residual terms has become the key to achieving accurate forecasting. Therefore, this paper proposes a sophisticated decomposition strategy to extract and analyze the useful information hidden in the residual terms. Firstly, the potential trend, seasonal and residual terms from the original data are extracted by seasonal-trend decomposition procedure based on loess. Secondly, the residual term is decomposed into a series of subcomponents with different frequency features by symplectic geometric mode decomposition. Thirdly, these subcomponents are classified into three clusters based on fuzzy C-means clustering (FCM), and then the corresponding forecasting models are matched to the three obtained clusters and trend and seasonal terms. Finally, based on a decomposition-ensemble framework and information granulation for high-frequency components, we have established point and interval forecasting approach, respectively. Three experiments on real data sets in Beijing, Guangzhou and Shenzhen are conducted to verify the performance of the proposed approach, and the experimental results show that our approach is superior to all benchmark models and contributes to improving operational management and service quality.

Geographical Distribution of Osteopathic Neurosurgery Residents.

The neurosurgery residency match has grown increasingly competitive, especially for osteopathic (DO) medical students, amidst the transition to a single accreditation system in 2020. This shift required former American Osteopathic Association (AOA) programs to apply for Accreditation Council for Graduate Medical Education (ACGME) accreditation, leading to a notable reduction in programs with a history of accepting DO applicants. This study aims to explore both potential geographical trends in residency match among recent DO neurosurgical residents and in the number of DO neurosurgical residents pre- and post-ACGME merger. Neurosurgery residency programs during the 2023-2024 academic year were identified, and each program's residents, resident degrees, and resident post-graduate years were collected from residency programs' websites. Descriptive statistics were used to analyze the ratios of DO and allopathic (MD) residents, while regression analyses were used to determine the trends in DO residents between 2017 and 2024. DO residents were also collated by state to observe their geographical distribution. A comprehensive cross-sectional analysis of 115 neurosurgery residency programs across the United States from 2016 to 2024 reveals a significant decrease in DO residents, from 14 in 2016 to four in 2024, with an average of six DO residents per year post-merger. A geographical heatmap analysis pinpointed New Jersey, Michigan, and California as states with the highest proportions and numbers of DO neurosurgery residents. These findings show the geographical distribution of DO neurosurgery residents in the US. Recognizing and understanding these geographical trends could be essential in the strategic application planning for DO candidates and the need for residency programs to reassess selection criteria to be more inclusive of DO applicants.

Evidences and perspectives on the association between gut microbiota and sepsis: A bibliometric analysis from 2003 to 2023

BackgroundIn the last two decades, the role of the gut microbiome in the development, maintenance, and outcome of sepsis has received increased attention; however, few descriptive studies exist on its research focus, priorities, and future prospects. This study aimed to identify the current state, evolution, and emerging trends in the field of gut microbiota and sepsis using bibliometric analysis. MethodsAll publications on sepsis and gut microbiota were retrieved from the Web of Science Core Collection and included in this study. VOSviewer, CiteSpace, and the Web of Science online analysis platform were used to visualize trends based on publication country, institution, author, journal, and keywords. ResultsA total of 1,882 articles on sepsis-related gut microbiota were screened, mainly from 95 countries or regions and 2,581 institutions. The United States and China contributed the most to this research field, with 521 (27.683 %) and 376 (19.979 %) articles, respectively. Scientists from the University of California were the most prolific, publishing 63 (3.348 %) articles. Cani PD published papers with the highest H-index, establishing himself as a leader in the field. The most publications were published in the journals “Nutrients” and “PLOS One.” The journals with the most co-citations were “PLOS One,” “Nature,” and “Gut.” The most used keywords were prebiotics, gut microbiota, and sepsis. The keyword burst research analysis revealed that research on treatment strategies based on the intestinal microbiota, intestine-liver axis, and regulatory mechanisms of bacterial metabolites are currently hot directions. ConclusionThis study presents a global overview of the current state and potential trends in the field of sepsis-related gut microbiota. This study identified hot research sub-directions and new trends through comparison and analysis, which will aid in the development of this field.

Blockchain Technology Application and Potential in the Global Securities Trading Market

With the rapid development of financial technology, blockchain technology is gradually permeating the global securities trading market. This paper delves into the current status of blockchain technology applications in this field, covering key aspects such as trade settlement and clearing, securities issuance and trading, identity verification, and compliance management. Through detailed case studies, it powerfully demonstrates its significant reduction in settlement cycles and intermediate links, thereby improving trade efficiency; its substantial reduction in operational costs and additional expenditures due to human errors, thereby lowering costs; and its effective resistance to cyber-attacks through data encryption and tamper-proof characteristics, thereby enhancing security. At the same time, it explores the positive role of blockchain technology in improving market trust by offering transparent transaction records and reducing information asymmetry. The paper further analyzes the challenges faced by blockchain technology in the global securities trading market, including issues with technology maturity such as performance scaling and interoperability, regulatory and compliance issues such as incomplete legal frameworks and policy uncertainties, industry acceptance issues such as conservative attitudes from traditional institutions and insufficient technology popularization education, and security risks such as emerging vulnerabilities and private key management risks. On this basis, it provides a forward-looking outlook on the potential and development trends of blockchain technology in the global securities trading market in the future, including integration trends with other emerging technologies, its role in promoting cross-border transactions and financial market integration, the possibility of innovative financial products and services, and the resulting changes in market patterns. In summary, this paper provides a comprehensive and systematic study of the current status, advantages, challenges, and future development of blockchain technology in the global securities trading market, offering valuable references and insights for further development in this field.

A systematic review of the application of machine learning techniques to ultrasound tongue imaging analysis.

B-mode ultrasound has emerged as a prevalent tool for observing tongue motion in speech production, gaining traction in speech therapy applications. However, the effective analysis of ultrasound tongue image frame sequences (UTIFs) encounters many challenges, such as the presence of high levels of speckle noise and obscured views. Recently, the application of machine learning, especially deep learning techniques, to UTIF interpretation has shown promise in overcoming these hurdles. This paper presents a thorough examination of the existing literature, focusing on UTIF analysis. The scope of our work encompasses four key areas: a foundational introduction to deep learning principles, an exploration of motion tracking methodologies, a discussion of feature extraction techniques, and an examination of cross-modality mapping. The paper concludes with a detailed discussion of insights gleaned from the comprehensive literature review, outlining potential trends and challenges that lie ahead in the field.

Causality between Celiac disease and kidney disease: A Mendelian Randomization Study.

Celiac disease, characterized as an autoimmune disorder, possesses the capacity to affect multiple organs and systems. Earlier research has indicated an increased risk of kidney diseases associated with celiac disease. However, the potential causal relationship between genetic susceptibility to celiac disease and the risk of kidney diseases remains uncertain. We conducted Mendelian randomization analysis using nonoverlapping European population data, examining the link between celiac disease and 10 kidney traits in whole-genome association studies. We employed the inverse variance-weighted method to enhance statistical robustness, and results' reliability was reinforced through rigorous sensitivity analysis. Mendelian randomization analysis revealed a genetic susceptibility of celiac disease to an increased risk of immunoglobulin A nephropathy (OR = 1.44; 95% confidence interval [CI] = 1.17-1.78; P = 5.7 × 10-4), chronic glomerulonephritis (OR = 1.15; 95% CI = 1.08-1.22; P = 2.58 × 10-5), and a decline in estimated glomerular filtration rate (beta = -0.001; P = 2.99 × 10-4). Additionally, a potential positive trend in the causal relationship between celiac disease and membranous nephropathy (OR = 1.37; 95% CI = 1.08-1.74; P = 0.01) was observed. Sensitivity analysis indicated the absence of pleiotropy. This study contributes novel evidence establishing a causal link between celiac disease and kidney traits, indicating a potential association between celiac disease and an elevated risk of kidney diseases. The findings provide fresh perspectives for advancing mechanistic and clinical research into kidney diseases associated with celiac disease.

Genome-Wide Survey of the Potential Function of CrLBDs in Catharanthus roseus MIA Biosynthesis.

Catharanthus roseus (C. roseus) can produce over 150 types of monoterpenoid indole alkaloids (MIAs), including vinblastine and vincristine, which are currently the primary sources of these alkaloids. Exploring the complex regulatory mechanisms of C. roseus is significant for resolving MIA biosynthesis. The Lateral Organ Boundaries Domain (LBD) is a plant-specific transcription factor family that plays crucial roles in the physiological processes of plant growth, stress tolerance, and specialized metabolism. However, the LBD gene family has not been extensively characterized in C. roseus, and whether its members are involved in MIA biosynthesis is still being determined. A total of 34 C. roseus LBD (CrLBD) genes were identified. RNA-Seq data were investigated to examine the expression patterns of CrLBD genes in various tissues and methyl jasmonate (MeJA) treatments. The results revealed that the Class Ia member CrLBD4 is positively correlated with iridoid biosynthetic genes (p < 0.05, r ≥ 0.8); the Class IIb member CrLBD11 is negatively correlated with iridoid biosynthetic genes (p < 0.05, r ≤ -0.8). Further validation in leaves at different growth stages of C. roseus showed that CrLBD4 and CrLBD11 exhibited different potential expression trends with iridoid biosynthetic genes and the accumulation of vindoline and catharanthine. Yeast one-hybrid (Y1H) and subcellular localization assays demonstrated that CrLBD4 and CrLBD11 could bind to the "aattatTCCGGccgc" cis-element and localize to the nucleus. These findings suggest that CrLBD4 and CrLBD11 may be potential candidates for regulating MIA biosynthesis in C. roseus. In this study, we systematically analyzed the CrLBD gene family and provided insights into the roles of certain CrLBDs in the MIA biosynthesis of C. roseus.

Assessing Climate Change Projections through High-Resolution Modelling: A Comparative Study of Three European Cities

Climate change is expected to influence urban living conditions, challenging cities to adopt mitigation and adaptation measures. This paper assesses climate change projections for different urban areas in Europe –Eindhoven (The Netherlands), Genova (Italy) and Tampere (Finland)—and discusses how nature-based solutions (NBS) can help climate change adaptation in these cities. The Weather Research and Forecasting Model was used to simulate the climate of the recent past and the medium-term future, considering the RCP4.5 scenario, using nesting capabilities and high spatial resolution (1 km2). Climate indices focusing on temperature-related metrics are calculated for each city: Daily Temperature Range, Summer Days, Tropical Nights, Icing Days, and Frost Days. Despite the uncertainties of this modelling study, it was possible to identify some potential trends for the future. The strongest temperature increase was found during winter, whereas warming is less distinct in summer, except for Tampere, which could experience warmer summers and colder winters. The warming in Genova is predicted mainly outside of the main urban areas. Results indicate that on average the temperature in Eindhoven will increase more than in Genova, while in Tampere a small reduction in annual average temperature was estimated. NBS could help mitigate the increase in Summer Days and Tropical Nights projected for Genova and Eindhoven in the warmer months, and the increase in the number of Frost Days and Icing Days in Eindhoven (in winter) and Tampere (in autumn). To avoid undesirable impacts of NBS, proper planning concerning the location and type of NBS, vegetation characteristics and seasonality, is needed.

The influence of ecolabels in the consumption of green products: a study on Durban consumers

The purpose of the study is to ascertain the influence of ecolabels in the consumption of certified green products. It explores ecolabels in Durban, hoping to gain valuable insights into ecolabels’ role in influencing the consumption of certified green products. The study employed a quantitative and a non-probability sampling method to understand the influence of ecolabels among green consumers in Durban. To ensure that the data represents the diversity of Durban consumers, a random sampling method was adopted. The data was collected using questionnaires and analysed using the IBM SPSS Version 25. The study employed a sample of 384 customers from retail malls within selected Durban suburbs. The findings revealed that consumers generally have a positive perception of ecolabels and are likely to recommend certified green products. However, the data also revealed that there is scepticism around certified green products as they are considered expensive and can perhaps be attributed to the high cost of certification, credibility issues and the cost associated with the ecolabelling. There is a potential trend towards wider acceptance, with more respondents trusting the authenticity of ecolabels than not. The study also found that older respondents and those with higher income tend to have a more positive perception of ecolabels, potentially due to higher disposable income and greater familiarity with the concept. This suggests that addressing concerns about cost and credibility could further increase positive consumer perception of ecolabels. Businesses can use these findings to develop strategies to address consumer concerns about the cost and credibility of certified green products. They can also target marketing efforts towards older demographics and higher-income consumers who are more receptive to ecolabels. Policymakers can use the findings to evaluate the effectiveness of existing ecolabeling programs and also develop strategies to increase consumer awareness and trust in ecolabels, especially younger audiences.

Gabapentinoids for chemotherapy-induced peripheral neuropathy: systematic review and meta-analysis

IntroductionChemotherapy-induced peripheral neuropathy (CIPN) affects patients’ quality of life and treatment effectiveness. Gabapentinoids, like gabapentin and pregabalin, are often used for CIPN treatment, but their efficacy and safety remain uncertain....

High Performance Solar-Driven Power-Water Cogeneration for Practical Application: From Micro/Nano Materials to Beyond.

Solar-driven water-electricity cogeneration is a promising strategy for tackling water scarcity and power shortages. However, comprehensive reviews on performance, scalability, commercialization, and power density are lacking. This Perspective presents an overview of recent developments and insights into the challenges and future outlooks for practical applications in this area. We summarize recent advances in high-efficiency water production, focusing on rapid evaporation and condensation. Then we categorize power-water cogeneration systems by power generation mechanisms like steam, evaporation, salinity gradient, photovoltaics, and temperature gradient, providing a comprehensive summary of the performance and applicability of these systems in different scenarios. Finally, we highlight challenges in current systems, considering nanoscale mechanisms and large-scale manufacturing, while also exploring potential trends for future practical applications.

Rainwater Quality Disparities Across Malaysian Peninsula Sites

This research describes the physicochemical quality of harvested rainwater at four distinct locations in Peninsula Malaysia. The evaluation of rainwater quality across different geographic areas aims to provide valuable insights into potential variations and trends in rainwater quality to reduce water demand globally. This analysis is conducted to determine seven properties, namely ammoniacal nitrogen, biochemical oxygen demand (BOD5), chemical oxygen demand (COD), dissolved oxygen (DO), pH, total dissolved solids (TDS), and turbidity. The results demonstrate that the quality of harvested rainwater meets the raw water quality standards set by the World Health Organization (WHO) and the National Water Quality Standards for Malaysia (NWQSM), indicating good quality rainwater in Malaysia. However, the COD for rainwater in all locations exceeded the limit, with a range of 14.1 to 29.7 mg/L, while the maximum limit for COD set by WHO is 10 mg/L, and according to NWQSM standards, it is 10–100 mg/L. The average pH of the collected rainwater is acidic ranged from 4.7 to 5.56. BOD5 for the collected rainwater is excellent; however, L2 has a slightly higher BOD5 at 6.5 mg/L, whereas the recommended limit by WHO is 6 mg/L, and the NWQSM standard suggests a range of 1–12 mg/L, with a standard limit of 5–7 mg/L. Nevertheless, DO levels ranged from 7.71 to 7.76 mg/L, indicating an ambient gas concentration in the rainwater. The collected rainwater can be used for portable purposes, gardening, smart farming, and toilet flushing.

Influence of Breast Cancer Awareness Month on Public Interest of Breast Cancer in High-Income Countries Between 2012 and 2022: Google Trends Analysis.

Breast cancer is the most common cancer among women worldwide. High-income countries have a greater incidence and mortality rate of breast cancer than low-income countries. As a result, raising awareness about breast cancer is crucial in increasing the chances of early detection and treatment. Social media has evolved into an essential tool for Breast Cancer Awareness Month campaigns, allowing people to share their breast cancer stories and experiences while also providing a venue for education and support. The aim of this study was to assess the level of public interest in searches linked to breast cancer among a sample of high-income nations with a sizable internet user base from 2012 to 2022. We also sought to compare the proportional search volume for breast cancer during Breast Cancer Awareness Month with that during other months of the year. Google Trends was used to retrieve data on internet user search behaviors in the context of breast cancer from 2012 to 2022. Seven countries were evaluated in this study: Australia, Canada, Ireland, New Zealand, the United Kingdom, Saudi Arabia, and the United States, in addition to global data. Breast cancer relative search volume trends were analyzed annually, monthly, and weekly from 2012 to 2022. The annual percent change (APC) was calculated for each country and worldwide. Monthly and weekly data were used to identify potential trends. A fluctuating pattern in APC rates was observed, with a notable increase in 2018 and a significant decrease in 2020, particularly in Saudi Arabia. Monthly analysis revealed a consistent peak in search volume during October (Breast Cancer Awareness Month) each year. Weekly trends over a 20-year period indicated significant decreases in Australia, Canada, New Zealand, and the United States, while increases were noted in Ireland. Heatmap analysis further highlighted a consistent elevation in median search volume during October across all countries. These findings underscore the impact of Breast Cancer Awareness Month and suggest potential influences of governmental COVID-19 pandemic control measures in 2020 on internet search behavior.

Peri-urban dynamics: assessing expansion patterns and influencing factors

BackgroundPeri-urbanization, the expansion of large metropolitan centers into adjacent peri-urban regions, is a growing concern due to land scarcity and escalating housing costs. These zones, a blend of rural and urban features, blur the line between urban and rural areas, creating new landscapes. This study examines historical, present, and potential growth trends in the peri-urban area surrounding Durgapur Municipal Corporation (DMC). Analytical techniques and spatial metrics are used to track development intensity changes over time, including built-up density, Shannon’s entropy, Landscape expansion index, Average Weighted Mean Expansion Index, Annual Built-Up Expansion Rate, Built-Up Expansion Intensity Index, and Built-Up Expansion Difference Index. Landscape indices like Patch Density, Edge Density, Landscape Shape Index, Largest Patch Index, Ratio of Open Space, and Area Weighted Mean Patch Fractal are used to understand fragmentation, connectivity, and spatial relationships. The Logistic Regression Model (LRM) is used to identify influencing factors and CA-Markov modeling for future built-up areas.ResultsBetween 1991 and 2001, built-up area in the region increased significantly, primarily due to urban development near industrial zones, roadways, and mining areas. The growth was primarily concentrated in the western sector and near National Highway-2 (NH-2). Urban sprawl was a continuous trend, with the highest built-up density in the South-South-East (SSE) direction from 1991 to 2011. Additionally, a key determinant of built-up development was the distance to the city core. By 2031, the built-up area is expected to concentrate in the western and southeast regions, reaching 177.90 km2.ConclusionsThis expansion is attributed to urban development near industrial zones, roadways, mining areas, and other infrastructure. The study identifies distance to the city center as a significant influencing factor for built-up development. The results emphasize the need for inclusive urban planning methods prioritizing sustainable development principles and prudent resource management for future growth and efficient management in the DMC’s peri-urban area.