Silver nanoparticles (Ag⁺NPs) contamination in the environment is a serious concern. This study investigated selected heavy metal (Ag⁺, Cd^2+, Cr²⁺ and Pb²⁺) concentrations at different sampling points to assess the risk to human health (infants, children, and adults). To do this, an enclosed area (laboratory) of 12.6 m X 8.5 m (107.1 m²) was clearly marked at different coded distances of S1, S2, S3, and S4 representing 2, 4, 6, and 8 m, while unpolluted atmosphere at 50 m away without Ag⁺NPs served as the control (S5). The silver fireworks were allowed to burn for an approximate 00h03m30s at each sampling points using a high-volume air sampler mounted at the Environmental Engineering Departmental Laboratory, Rivers State University, with windows and doors closed to simulate indoor conditions. Samples were digested using a mixture of analytical-grade nitric acid, analytical-grade hydrochloric acid and analyzed to evaluate the levels of heavy metals by atomic absorption spectrophotometry. The Ag⁺ result at S1 shows 30,000 µg/cm³, S2 was 29,000 µg/cm³, while S3 was 28000 µg/cm³ and then S4 was 13,000 µg/cm³. These results exceeded the permissible values of the United States National Ambient Air Concentration for rural, urban and industrial areas (0.0005, 0.004 and 0.6 µg/cm³, respectively). The result for the control (S5) (0.037 µg/cm³) was within the maximum allowable value. Results from other heavy metals such as Cd were 1000, 743, 401, 153, 0.001 µg/cm³, Cr was 5000, 4000, 3729, 2960, 0.002 µg/cm³, Pb was 0.048, 0.041, 0.035, 0.034 and 0.01, µg/cm³, respectively. However, higher values of Ag⁺, Cd, and Cr indicated a higher propensity for the metals to be toxic (bioavailable). In addition, the assessment of the potential health risk posed by these metals proved contaminated and harmful. Visitors recorded high values in exposure concentration (EC) and low values in average daily dose (ADD).

Objective: To evaluate maternal and neonatal outcomes of women with placenta accreta spectrum (PAS) disorders managed by a dedicated multidisciplinary team at a tertiary referral centre in Riyadh, Saudi Arabia. Methods: We conducted a prospective case series of all women with antenatally suspected and intraoperatively or histopathologically confirmed PAS managed at King Fahad Medical City between April 2018 and December 2024. Women with high suspicion of PAS were electively admitted at 31+6 weeks’ gestation for optimisation when feasible and delivered by midline laparotomy and fundal or classical caesarean incision with the placenta left in situ. Definitive management consisted of hand-assisted retrograde caesarean hysterectomy or segmental uterine resection with reconstruction. Outcomes included operative time, quantified blood loss, transfusion requirements, intra- and postoperative complications, intensive care unit (ICU) admission, hospital stay, and neonatal morbidity. Results: A total of 236 women with confirmed PAS were managed. Median maternal age was 36 years and placenta previa coexisted in 86.9%. Elective caesarean delivery at 34+0–35+6 weeks occurred in 72.0%, whereas 28.0% required emergency delivery for haemorrhage or labour. Caesarean hysterectomy was performed in 85.2% and conservative segmental uterine resection in 14.8%. Median operative time was 135 minutes and median blood loss 4.3 L; the median transfusion requirement was six units of packed red blood cells. Intraoperative complications occurred in 27.1%, most commonly bladder injury (14.8%). One woman (0.4%) died intraoperatively from disseminated intravascular coagulation with intracardiac thrombosis. ICU admission was required in 66.0%. Neonatal intensive care unit admission occurred in 53.0%, mainly because of prematurity; there were no neonatal deaths. Conclusion: Centralised multidisciplinary management of PAS with planned delivery at 34–35 weeks, avoidance of placental removal, and use of retrograde hysterectomy or segmental resection can minimise haemorrhage and maternal mortality while maintaining acceptable neonatal outcomes in a high-volume referral centre.

The processes of technical and technological development are unequivocally linked to increasing energy consumption, with a significant portion of energy being produced from fossil fuels worldwide. The reserves of natural energy sources such as petroleum, gas, coal, and turf are finite. The transition to renewable energy sources has been ongoing for a long time, but share in global energy consumption remains lower than desired. The main limitations include limited availability, inability to operate continuously throughout the year, high costs, and a lack of materials and devices capable of withstanding high temperatures and pressures. The goal of our research is to create a device that generates electricity using a new type of renewable energy source based on the thermal expansion and contraction of materials. This paper presents the construction, details, and working principles of the new device. The primary focus is on utilizing materials and components that are readily available. The proposed method has own advantages, addresses some of the aforementioned limitations, and can be particularly beneficial for providing electrical energy in remote areas. Calculations indicate that the device built using this new method will be competitive with appliances that utilize other renewable energy sources in terms of features and efficiency.

Digital signal processing played a central role in two practical studies addressing challenging problems related to high-volume SWIFT financial messaging flows conveyed by the interconnected banking network. Technical methods and results are summarized here for each study, with the links to fundamental concepts underlying the work shown in parentheses. The first addresses real-time fraud detection, integrating pattern recognition and anomaly scoring procedures into a latency conscious processing system. The second focuses on minimizing delay without degrading detection accuracy, balancing speed and fidelity in filter design and control. Together, they demonstrate the potential for applying a DSP perspective to broad classes of problems encountered in processing financial messaging data. The first study extends work on a signal representation of financial messaging data streams and the associated noise characteristics by developing a vocabulary that translates real-world fraud patterns into DSP operations. Examination of the resulting choice of signal features, combined with considerations of detection speed, form the basis for details about implementing the pattern-recognition and anomaly-scoring tasks within a streaming-processing architecture.