Browse Articles
Discover research articles across all indexed journals
The overlooked impacts of freshwater scarcity on oceans as evidenced by the Mediterranean Sea
Dynamic behavior of solitons in nonlinear Schrödinger equations
Carbon pricing drives critical transition to green growth
Efficacy and safety of selective laser trabeculoplasty for uveitic glaucoma
Reframing the filter bubble through diverse scale effects in online music consumption
Enhancing urban air quality prediction using time-based-spatial forecasting framework
Abstract Air quality forecasting plays a pivotal role in environmental management, public health and urban planning. This research presents a comprehensive approach for forecasting the Air Quality Index (AQI). The proposed Time-Based-Spatial (TBS) forecasting framework is integrated with spatial and temporal information using machine learning techniques on data collected from a wide range of cities. The TBS employs Convolutional Neural Networks (CNNs) to capture spatial dependencies based on normalized latitude and longitude coordinates of the cities. Simultaneously, time series model, specifically the ARIMA (AutoRegressive Integrated Moving Average) was employed to capture temporal dependencies using pollutant concentration readings over time. The dataset included information such as date, time, pollutant concentrations and AQI was further preprocessed and divided into training and testing sets. The CNN was configured to utilize the normalized latitude and longitude grid, while the ARIMA model concurrently processed the pollutant concentrations. The model was trained on the training dataset, and a 6 hour forecast is generated for each test instance. The outcomes demonstrate the TBS model’s ability to accurately predict AQI values. The integration of CNNs and time series model allowed for an clearer and deeper understanding of geographical and pollutant concentration factors that contribute to air quality variations.
Personalized metronomic radiopharmaceutical therapy through injection profile optimization via physiologically based pharmacokinetic (PBPK) modeling
Enhancing counterfeit RFID tag classification through distance based cognitive risk control
AI-driven video summarization for optimizing content retrieval and management through deep learning techniques
The impact of action descriptions on attribution of moral responsibility towards robots
Ecological overview of hard ticks (Ixodida: Ixodidae) in Nagasaki prefecture of western Japan during winter 2021–2022
Evaluation of an aquatic liverwort and terrestrial moss as biomonitors of heavy metals associated with particulate matter
Environmental and health risk assessment of polycyclic aromatic hydrocarbons and toxic elements in the red sea using Monte Carlo simulation
Abstract This research evaluates the environmental and health risks linked to potentially toxic elements (PTEs) and PAHs along the western coast of the Gulf of Suez, Egypt. This study investigated the concentration of 16 PAH compounds in the Suez Gulf, revealing significantly higher levels than the EU (0.20 µg/L) and US (0.030 µg/L) standards. The average total PAH concentration across eight locations was significantly higher, with the Suez area having the highest concentration at 479 µg/L. Pyrene (Pyr) was the dominant PAH with a concentration of 443 µg/L in Suez, while acenaphthylene (Ace) had the lowest concentration at 0.120 µg/L in Northern Zaafarana. Carcinogenic PAHs (CAR) ranged from 8.67 µg/L at Ras Gharib to 29.62 µg/L at Suez, highlighting the urgent need for regulatory measures. Confirmatory ratios pointed to industrial and shipping influences as petrogenic sources. Elevated total organic carbon (TOC) levels in Suez Bay indicated aggravated organic pollution, exacerbated by oil rigs and refineries. The ecological risk assessment highlighted substantial risks, particularly in Suez, necessitating immediate interventions to combat PAH contamination and preserve the environmental balance of the Red Sea. The dominant metals in water samples were arranged in descending order as follows: Pb > Fe > Cr > Cu > Zn > Mn > Cd > Ni. The study evaluated environmental and human health risks using a multifaceted approach, including cluster analysis, principal component analysis, and various indices (HPI, RI, MI, HQ, HI, and CR). Most water samples exhibited high pollution risks, surpassing permissible limits for HPI (> 100) and MI (> 6). Notably, HI oral values indicated significant non-carcinogenic risks for adults and children. While HI values for adults suggested low-risk dermal contact, those for children showed a substantial proportion in the high-risk category. Most water samples displayed CR values exceeding 1 × 10–4 for Cd, Cr, and Pb, indicating vulnerability to carcinogenic effects in both age groups. Monte Carlo simulations reinforced these findings, revealing a significant carcinogenic impact on children and adults. The identified clusters, reflective of industrial, petroleum-related, and urban runoff contamination sources, were consistently validated and clarified through PCA, enhancing the reliability of the findings. In light of these results, urgent and comprehensive water treatment measures are imperative to mitigate carcinogenic and non-carcinogenic health risks. These insights provide a foundation for implementing targeted management strategies to effectively address the challenges of heavy metal contamination in the Red Sea.
Publisher Correction: Role of total polyphenol content in seed germination characteristics of spring barley varieties amidst climate change
Iron(III) edta-accelerated growth of gold/silver core/shell nanoparticles for wide-range colorimetric detection of hydrogen peroxide
Long-term trends and patterns in ultra-processed food consumption among Korean adults from 1998 to 2022
Differences in health related quality of life among older migrants and nonmigrants in India
RF communication between dual band implantable and on body antennas for biotelemetry application
Abstract This paper investigates two antennas for implantable communication, which are a wide-band, low-profile transmitting antenna with a circular polarization (CP) merit immersed in a lossy medium and a corresponding wide-band, low-profile receiving antenna with a linear polarization (LP) merit placed on human tissue. The first antenna is implantable inside a human body for sensing, monitoring, and transmitting various vital signs, while the second antenna acts as a nearby receiving end. These antennas work in the 2.4-2.4835 GHz and 5.725-5.875 GHz industrial, scientific, and medical (ISM) bands. The main features of the designed transmitting antenna are its simplicity, the wide-band characteristics, which preserve the detuning effect caused by environmental heterogeneity, and the CP property at both operational ISM bands. Moreover, for introducing an electrically small antenna footprint with proper performance, the implantable antenna is designed with an entire size of 25.4 (5 $$\times$$ 5 $$\times$$ 1.016) $$\hbox {mm}^3$$ . This antenna is designed and dissected in a homogeneous skin model (HSM) as well as a three-layer phantom. On the other hand, the wide-band receiving antenna is designed on flexible material for patients’ comfort with a compact size of 134.6 ( $$20\times 26.5\times 0.254$$ ) $$\hbox {mm}^3$$ . In addition, the implantable antenna performance is evaluated in a chicken slab as well as a saline solution, while the on-body antenna is placed on the chicken slab to measure its reflection coefficient. The measured impedance BWs of the implantable antenna are 13.04 % and 33.2 % in the chicken slab while 19.5% and 25.2 % in the saline solution at the two ISM bands, respectively. While, the measured impedance BWs of the on-body antenna are 24% and 50.4 % at two operating ISM frequencies. Finally, the measured transmission coefficient between the two antennas is evaluated.