Taiz University

Water resources should be used efficiently in order to reduce constraints to future generations. it is important to stress the importance of well-developed management plans with sound forecasts. The need to have exact long-term forecast, limited access to data, changeable demand and some of the significant challenges it faces include integration of different datasets. The objective of this research is to predict Total Water consumption (TWC) and agricultural water use (AWU) which are increasing because of causes like climate change, seasonal highs and lows and financial requirements. Forecasting It is difficult to plan what to do with watering because of the unpredictable weather and soil conditions. In this Research, a Bidirectional Gated Recurrent Unit (Bi-GRU) is applied on the Global Water. These challenges to strategy could be addressed by the Consumption Dataset (2000–2024) in order to obtain the most accurate prediction. This is further enhanced by the fact that the performance of our model (Bi-GRU) is compared to that of other popular models like LSTM, Deep-AR, Mega-CRN and TFT. The play is very active. with an effective mean absolute percentage error (MAPE) of 0.2257, root mean square error (RMSE) by less than the fact that the mean squared error (MSE) = 0.0049 and the mean absolute error (MAE) = 0.0587 confirm that the Bi-GRU model is superior compared to other models used to forecast TWC and AWU that are also our dependent variables. The higher precision in forecasting rendered feasible by using deep learning algorithms enables a more precise evaluation of global water consumption particularly that of the agricultural and industrial sectors. It thus facilitates the development of efficient water-management schemes globally. The choice of Bi-GRU is motivated by its bidirectional temporal learning capability, which enables improved modeling of long-term and multivariate dependencies in global water consumption time-series.

The paper explores analytical solutions to the coupled Konno-Oono and Kadomtsev-Petviashvili (modified) extended wave (KP-MEW) equations in (2 +1)-dimensions, which have applications in the study of nonlinear wave propagation in shallow water, plasma, and optical systems. The method (Riccati Modified Extended Simple Equation Method) was applied to provide us with a wide range of exact traveling wave solutions as hyperbolic, trigonometric, exponential, and rational. The solutions obtained are highly nonlinear, including soliton pulses, periodic waves, kink-like structures and blow-up modes, which give an understanding of the interaction of waves and their stability. It is important to note that the rational-type solutions are a new category that has never been mentioned in other studies. The authors generalize the previous studies by providing a coherent structure in building different families of solutions, which reveal the usefulness and flexibility of the suggested approach in investigating the nonlinear wave dynamics in higher dimensions.

The second non-CO2 greenhouse gas mentioned under the Kyoto Protocol of the United Nations Convention on Climate Change (December 1997) was N2O. According to this protocol, the European Union, Canada, and Japan were committed to reducing their collective greenhouse gas (GHG) emissions by slightly more than 5 percent below their 1990 levels. Developed countries, also, we are asked to reduce our GHG emissions to at least 5 percent of the 1990 levels, and this is to be achieved till 2012. Since in many situations, N2O formation is inevitable in the applied processes, catalysts offer a route to N2O abatement. Over the past several years, more articles have been released that have tried to propose paths through which reduction can be achieved. Nitrous oxide emission, one of the suggested solutions, involves the direct catalytic decomposition of N2O into its elements. Transition metal exchange zeolites, such as Cu-ZSM-5, Co-ZSM-5, and Fe-ZSM-5, have been reported to exhibit high catalytic activity towards N2O direct decomposition. This study focused on the activity of a series of Cu-ZSM-5 catalysts, with copper exchange levels of 10-150%, for nitrous oxide (N2O) decomposition. Different Cu-ZSM-5 catalysts were prepared by applying the solid state ion exchange (SSIE) method through the interaction between NH4-ZSM-5 and the copper(ii) complex. Thermal events emerged during the heat treatment, from ambient temperature to 700 °C, of the two precursors, which were followed by thermal analyses, viz. TGA and DTA. Based on the obtained thermal analysis profiles, different mixtures containing NH4-ZSM-5 and copper(ii) coordination polymers were calcined at 550 °C for 3 h in a static air atmosphere. Various integrated physicochemical techniques were used in the characterization of the obtained Cu-ZSM-5 catalysts, including XRD, FT-IR spectroscopy, SEM, N2-adsorption and electrical conductivity analyses. It was found that the suggested preparation route led to the formation of Cu-ZSM-5, where no CuO or reaction precursors were detected in the 550 °C calcined samples. However, the crystallinity of the obtained Cu-ZSM-5 catalysts was found to decrease with the copper exchange level. The activity of the different Cu-ZSM-5 catalysts was tested for N2O decomposition in the temperature range of 150-500 °C. The highest activity was exhibited by the catalyst with a copper exchange level of 75%.

A broadened polarization bandwidth with a high-gain SADEA-driven metasurface antenna at 5 GHz is investigated for the sub-6 GHz 5G wireless applications. At first, a λo/4 linearly polarized printed monopole antenna is considered. In the next step, a metallic strip that serves as a dynamic switching mechanism is used to short one of the parasitic conducting strips with a partial ground plane to get circular polarization (CP). To make it suitable for the RF energy harvesting application, a crucial part of sub-6 GHz 5G communication, the motive is to achieve broadened performance for antenna gain, impedance (10-dB BW), and axial bandwidths (3-dB BW). It is attained by placing the SADEA-tuned metasurface layer as a parasitic patch at the height of 0.02λo, below the radiator. With the usage of the SADEA optimization method, the process of the metasurface layer is depicted as more effective in performance and less complex towards its execution. It is printed on FR-4 of 1.33λo × 0.9λo × 0.02λo, which offers a measured 58.23% 10-dB BW, 26.39% 3-dB BW, CP gain peak > 5.9 dBic, antenna efficiency > 75%, with a front-to-back ratio > -20 dBic in the sub-6 GHz 5G bands, a potential candidate for the next-generation wireless communication, especially for the RF energy harvesting systems.

The research investigates pulse propagation through mono-mode optical fibers using the fractional Fokas system by integrating the conformable fractional calculus with the generalized Riccati-Bernoulli sub-ODE method along with Bäcklund transformation. The figures demonstrate perturb kink soliton profiles using 2D plots for fractional-order parameter ($$\alpha$$) together with 3D plots for integer-order conditions to depict the solutions dynamic nature. The model demonstrates its physical operation range through different initial condition analyses which increases its potential for widespread application. The derived solutions demonstrate the ability of the combined approach to be an effective mathematical methodology that addresses various types of nonlinear wave phenomena. The optical solitons enable researchers to study energy transport and diffusion mechanisms in fractional-order systems specifically regarding pulse propagation in optical communication networks.

Abstract Background: Uterine rupture is An uncommon but serious obstetric emergency, particularly in low-resource and conflict-affected settings. However, data on its burden in Yemen is limited. Therefore, this study assessed the incidence, determinants and outcomes of uterine rupture among women admitted to a tertiary care hospital in Taiz City, southwest of the country. Methods: A retrospective surveillance study with an integrated case-control analysis was conducted at the Republican General Teaching Hospital in Taiz during 2023. All women with uterine rupture during the study period were included as cases, while controls were randomly selected from those delivered without uterine rupture. Demographic, obstetric, intrapartum and outcome data were extracted from medical records. Associations between uterine rupture and its determinants were assessed at a significance level of <0.05. Results: Out of 8,550 deliveries, 23 cases of uterine rupture were identified, resulting in an incidence of 2.7 per 1,000 deliveries. Most ruptures were complete (82.6%). Rural residence (OR = 4; 95% CI: 1.39–11.49; P = 0.008), interpregnancy interval (IPI) <24 months (OR = 5.2; 95% CI: 1.16–23.08; P = 0.030), and breech fetal malpresentation (OR = 21.9; 95% CI: 1.13–426.9; P = 0.008) were significantly associated with uterine rupture. Substantial maternal morbidity was observed, including bladder rupture (21.7%), severe blood loss (26.1%), and need for transfusion (43.5%). Hysterectomy was performed in 13% of cases. One woman died, whereas stillbirths occurred in 27.3% of cases. Conclusion: The incidence of uterine rupture in Taiz City exceeds regional and global estimates and is associated with substantial maternal and perinatal morbidity, including bladder rupture, severe blood loss, need for blood transfusion, hysterectomy, and stillbirth. Rural residence, short IPIs, and breech presentation are key determinants, showing inequities in maternal care and the need to strengthen antenatal services, referral systems, and antenatal care services.

The study investigated the impact of human-machine collaboration (HMC) in English-Arabic translation, examining both its benefits and challenges. A mixed-methods research design was employed, incorporating both quantitative and qualitative techniques. Sixty-four participants were involved, with four excluded due to a lack of experience with machine translation systems. Data was collected using a semi-structured questionnaire via the Google Forms platform. The findings indicated that HMC offers three major benefits: enhancing expertise in HMC, providing system feedback and optimizing job satisfaction. Despite these benefits, the key accuracy challenges were primarily linked to fundamental linguistic differences, including grammatical, lexical, and contextual variations. Culture and technical differences also posed significant difficulties for collaboration in translation and post-editing processes.

Type 2 diabetes mellitus (T2DM) increases the risk of cardiovascular morbidity and end-stage renal disease. Renin-angiotensin-aldosterone system (RAAS) inhibitors, specifically angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs), are standard therapies for organ protection. However, uncertainty remains regarding their comparative efficacy and the safety of combination therapy. This systematic review and meta-analysis aimed to compare the efficacy of ACEIs versus ARBs in reducing cardiovascular and renal events in patients with T2DM and to assess the safety of dual blockade. PubMed, EMBASE, and Cochrane databases were searched for randomized controlled trials (RCTs) published up to 2025 comparing ACEIs, ARBs, or their combination against placebo or active controls in T2DM patients. The primary outcome was a composite of cardiovascular death, myocardial infarction, stroke, and renal failure. Methodological quality was assessed using the Cochrane Risk of Bias 2 tool. Data were synthesized using frequentist pairwise and Bayesian network meta-analyses. Heterogeneity was explored via meta-regression, and trial sequential analysis (TSA) was used to assess the sufficiency of evidence. In total, 16 RCTs involving 47,406 participants were included. In pairwise analysis, both ACEIs (risk ratio (RR) = 0.87, 95% confidence interval (CI) = 0.81-0.94) and ARBs (RR = 0.90, 95% CI = 0.83-0.98) significantly reduced the risk of the primary composite endpoint compared to control. Network meta-analysis showed no statistically significant difference between ACEIs and ARBs (RR = 0.98, 95% CI = 0.88-1.09). Although ACEIs ranked slightly higher in probability for reducing all-cause mortality (surface under the cumulative ranking = 78% vs. 65%), this difference was not statistically significant. Dual blockade (ACEI + ARB) increased the risk of hyperkalemia (RR = 2.8) and acute kidney injury (RR = 1.7) without improving efficacy. Meta-regression identified baseline systolic blood pressure as a significant modifier of treatment benefit (p = 0.04). TSA indicated that the evidence for the RAAS blockade's benefit is conclusive. ACEIs and ARBs exhibit comparable efficacy in preventing cardiovascular and renal events in patients with T2DM, with a marginal mortality benefit favoring ACEIs. Dual blockade is associated with increased harm and is not recommended. Monotherapy with either agent remains the preferred strategy for organ protection.

Detecting nitrogen dioxide (NO2) at low concentrations and under ambient conditions remains a significant challenge in environmental sensing. In this work, we report a highly responsive TiO2/PEDOT nanocomposite sensor engineered through a facile in situ polymerization approach. The composite integrates the high surface reactivity of n-type TiO2 nanoparticles that provide superior conductivity and ambient operability of p-type PEDOT, forming a synergistic p–n heterojunction that enables efficient charge separation and signal amplification at room temperature, without the need for thermal activation or extrinsic dopants, thereby distinguishing this system from previously reported TiO₂–polymer composites. Comprehensive material characterization confirmed successful nanocomposite formation and favorable structural properties. The sensor demonstrated a high response of 119.9% at 400 ppm when exposed to NO2 gas, with recovery and response times of 137 s and 117 s, respectively, all at room temperature. Furthermore, the device showed excellent repeatability, reproducibility across sensor batches, and operational stability over 30 days. These results show that the TiO2/PEDOT nanocomposite, which combines sensitivity, selectivity, and practicality, is a potential option for NO2 sensing systems.