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Background: The COVID-19 pandemic remains an immediate and present concern, yet as of now there is still no approved therapeutic available for the treatment of COVID-19.This study aimed to investigate and report evidence concerning demographic characteristics and currently-used medications that contribute to the ultimate outcomes of COVID-19 ICU patients. Methods: A retrospective cohort study was conducted among all COVID-19 patients in the Intensive Care Unit (ICU) of Asir Central Hospital in Saudi Arabia between the 1st and 30th of June 2020. Data extracted from patients’ medical records included their demographics, home medications, medications used to treat COVID-19, treatment durations, ICU stay, hospital stay, and ultimate outcome (recovery or death).Descriptive statistics and regression modelling were used to analyze and compare the results. The study was approved by the Institutional Ethics Committees at both Asir Central Hospital and King Khalid University. Results: A total of 118 patients with median age of 57 years having definite clinical and disease outcomes were included in the study. Male patients accounted for 87% of the study population, and more than 65% experienced at least one comorbidity. The mean hospital and ICU stay was 11.4 and 9.8 days, respectively. The most common drugs used were tocilizumab (31.4%), triple combination therapy (45.8%), favipiravir (56.8%), dexamethasone (86.7%), and enoxaparin (83%). Treatment with enoxaparin significantly reduced the length of ICU stay (p = 0.04) and was found to be associated with mortality reduction in patients aged 50−75 (p = 0.03), whereas the triple regimen therapy and tocilizumab significantly increased the length of ICU stay in all patients (p = 0.01, p = 0.02 respectively). Conclusion: COVID-19 tends to affect males more significantly than females. The use of enoxaparin is an important part of COVID-19 treatment, especially for those above 50 years of age, while the use of triple combination therapy and tocilizumab in COVID-19 protocols should be reevaluated and restricted to patients who have high likelihood of benefit.

Canola, Brassica napus L. is a significant oilseed crop, containing 35 to 45% oil in its seeds, and can be cultivated in various climatic regions. Cabbage aphid, Brevicoryne brassicae L. is the most important pest of the canola fields in Iran. Chemical insecticide application using ground sprayers is the primary method for controlling B. brassicae in canola fields. However, the dense and tall growth of canola plants poses challenges for maneuvering ground sprayers, which can potentially cause damage to the plants. Therefore, in this study, we evaluated the feasibility and efficacy of aerial spraying of canola fields against cabbage aphid using drone, and compared it with ground spraying. During two growing seasons, this study was conducted in canola fields of Miandoab and Ilakhchi in northwest Iran. Aphid populations were sampled 24 hours before sprayings and 48 hours, 72 hours, and two weeks after sprayings. A six-rotor drone equipped with micronair rotary atomizers was employed for aerial spraying, while a tractor-mounted sprayer was used for ground applications. Results demonstrated that aerial spraying with drone was significantly more efficient, achieving two to six times higher efficacy against cabbage aphids than ground spraying, as measured by the reduction in aphid populations. Image analysis of water-sensitive cards indicated that drones produced finer droplets with smaller volume median diameters. Economic analysis revealed that aerial spraying was more cost-effective despite higher initial costs due to lower operational expenses and reduced water usage. These findings underscore the potential of using drones for precision pesticide application in canola farming

The discussion about the thought and views of Ayn-al-Qużāt Hamadānī, the famous mystic of the 6th century, has always been attractive due to his special mystical-philosophical system of thought, as well as his openness and exemplary carelessness in expressing his inner thoughts. Along with the rational view of a religious philosopher, he has presented a different view from the point of view of a mystic. One of the important things in the intellectual system of Ayn-al-Qużāt Hamadānī is his definition and analysis of the category of” wisdom”. He has specified a way for wisdom, and where the wisdom cannot reach, he calls it beyond wisdom, and to achieve this, the eyes of human insight must be opened. Moreover, the judge calls wisdom a “special measure” and believes it does not have the ability to reach the realm of the kingdom. Therefore, beyond wisdom, it is pure knowledge and insight that can guide the seeker to the truth of existence. By researching and pondering the works of Ayn-al-Qużāt Hamadānī, this article analyzes his philosophical-mystical points of views on the status and dignity of wisdom and also introduces the definition and characteristics of wisdom from his mystical point of view.

The rapid impact assessment matrix (RIAM) is a widely utilized tool for evaluating environmental impacts in municipal solid waste management. However, the traditional RIAM (T-RIAM) method includes ambiguities in its scoring classification, which can hinder decision-making accuracy. This study introduces a modified RIAM approach, enhancing classification precision by refining impact categories, making it particularly valuable for projects constrained by time and resources. Using the Nazlou landfill in Urmia, Iran, as a case study, two waste management scenarios were assessed: (1) constructing a new landfill cell with leachate treatment facilities and (2) adding a composting plant to divert organic waste. The second scenario was identified as the optimal choice due to its positive environmental impacts across physical-chemical, biological-ecological, and socio-cultural domains, as well as its high public acceptance. Under the proposed classification scheme, the ''+E,'' ''+D,'' and ''–C″ impacts for this scenario decreased from 3, 7, and 3 (as per T-RIAM) to 2, 2, and 0, respectively. The refined scoring system allowed sharper differentiation, with only the most significant impacts classified in ''+E″ or ''–E″ categories, facilitating clearer decision-making compared to T-RIAM. Additionally, the streamlined classification approach reduces the need for extensive data inputs, making the modified RIAM an efficient alternative to resource-intensive methods like life cycle assessment for preliminary evaluations. Beyond waste management, the modified RIAM framework has potential applications in addressing broader environmental challenges, including water resource management, air quality assessment, and infrastructure planning, offering versatile utility for municipal decision-making.

Accurate prediction of daily river flow (Qt) remains a challenging yet essential task in hydrological modeling, particularly crucial for flood mitigation and water resource management. This study introduces an advanced M5 Prime (M5P) predictive model designed to estimate Qt as well as one- and two-day-ahead river flow forecasts (i.e. Qt+1 and Qt+2). The predictive performance of M5P ensembles incorporating Bootstrap Aggregation (BA), Disjoint Aggregating (DA), Additive Regression (AR), Vote (V), Iterative classifier optimizer (ICO), Random Subspace (RS), and Rotation Forest (ROF) were comprehensively evaluated. The proposed models were applied to a case study data in Tuolumne County, US, using a dataset comprising measured precipitation (Pt), evaporation (Et), and Qt. A wide range of input scenarios were explored for predicting Qt, Qt+1, and Qt+2. Results indicate that Pt and Qt significantly influence prediction accuracy. Notably, relying solely on the most correlated variable (e.g., Qt-1) does not guarantee robust prediction of Qt. However, extending the forecast horizon mitigates the influence of low-correlation input variables on model accuracy. Performance metrics indicate that the DA-M5P model achieves superior results, with Nash-Sutcliff Efficiency of 0.916 and root mean square error of 23 m3/s, followed by ROF-M5P, BA-M5P, AR-M5P, AR-M5P, RS-M5P, V-M5P, ICO-M5P, and the standalone M5P model. The ensemble M5P modeling framework enhanced the predictive capability of the stand-alone M5P algorithm by 1.2 %–22.6 %, underscoring its efficacy and potential for advancing hydrological forecasting.

Abstract Heart failure (HF) is a complex, progressive disorder that is associated with substantial morbidity and mortality on a global scale. Relaxin‐2 is a naturally occurring hormone that may have potential therapeutic benefit for patients with HF. To investigate the therapeutic potential of relaxin in the treatment of patients with HF, mRNA‐0184, a novel, investigational, lipid nanoparticle (LNP)–encapsulated mRNA therapy that encodes for human relaxin‐2 fused to variable light chain kappa (Rel2‐vlk) was developed. A translational semi‐mechanistic population pharmacokinetic (PK)/pharmacodynamic (PD) model was developed using data from non‐human primates at dose levels ranging from 0.15 to 1 mg/kg. The PK/PD model was able to describe the PK of Rel2‐vlk mRNA and translated Rel2‐vlk protein in non‐human primates adequately with relatively precise estimates. The preclinical PK/PD model was then scaled allometrically to determine the human mRNA‐0184 dose that would achieve therapeutic levels of Rel2‐vlk protein expression in patients with stable HF with reduced ejection fraction. Model‐based simulations derived from the scaled PK/PD model support the selection of 0.025 mg/kg as an appropriate starting human dose of mRNA‐0184 to achieve average trough relaxin levels between 1 and 2.5 ng/mL, which is the potential exposure for cardioprotective action of relaxin.

Existing artificial neural networks (ANNs) have attempted to efficiently identify underlying patterns in environmental series, but their structure optimization needs a trial-and-error process or an external optimization effort. This makes ANNs time consuming and more complex to be applied in practice. To alleviate these issues, we propose a stabilized ANNs, called SANN. The SANN efficiently optimizes ANN structure via incorporation of an additional numeric parameter into every layer of the ANN. To exemplify the efficacy and efficiency of the proposed approach, we provided two practical case studies involving meteorological drought forecasting at cities of Burdur and Isparta, Türkiye. To enhance SANN forecasting accuracy, we further suggested the hybrid VMD-SANN that integrated variation mode decomposition (VMD) with SANN. To validate the new hybrid model, we compared its results with those obtained from hybrid VMD-ANN and VMD-Radial Base Function (VMD-RBF) models. The results showed superiority of the VMD-SANN to its counterparts. Regarding Nash Sutcliffe Efficiency measure, the VMD-SANN achieves accurate forecasts as high as 0.945 and 0.980 in Burdur and Isparta cities, respectively.

Inducible laryngeal obstruction (ILO) is an upper-airway disorder involving a heightened sensitivity of the larynx, obstructing airflow and potentially leading to breathing difficulties. Speaking can trigger, and be affected by, ILO symptoms. This research explored the feasibility of singing-related workshops for people with ILO. The aim was to increase participants’ vocal confidence by combining relaxation with improved control, tone, and projection. Five participants consented to participate in the research. The workshops were led by a voice teacher (VT) and a speech and language therapist (SLT), focusing on posture, breathing techniques, and singing techniques. Ten weekly workshops took place online, with the final session being hybrid where most participants attended in person. Data collection included weekly response forms with Likert scales to rate speaking and singing confidence and feedback on the workshops; interviews with VT and SLT; workshop observations; and a participant reflection questionnaire following the program. Participants reported a significant improvement in speaking and singing confidence as the workshops progressed. Thematic analysis revealed four themes: improvements in confidence, specifically in speaking and singing; the value of social support and meeting others with the condition; specific techniques and approaches that were beneficial; and benefits and disadvantages of the online format. This research demonstrates the feasibility of group singing workshops for people with ILO who do not have a background in singing, using an online format. It confirms the potential benefits of using singing-related techniques for this condition, supporting confidence in speaking and singing. Further research would be useful to extend the findings from this initial project and to provide a firm basis for introducing further programs using singing-related techniques for people with a range of upper-airway disorders. Future developments could include introducing these techniques in clinical settings and using them alongside (or as part of) speech and language therapy.

Abstract The important mechanical parameters and their hierarchy in the growth and folding of the human brain have not been thoroughly understood. In this study, we developed a multiscale mechanical model to investigate how the interplay between initial geometrical undulations, differential tangential growth in the cortical plate, and axonal connectivity form and regulate the folding patterns of the human brain in a hierarchical order. To do so, different growth scenarios with bilayer spherical models that features initial undulations on the cortex and uniform or heterogeneous distribution of axonal fibers in the white matter were developed, statistically analyzed, and validated by the imaging observations. The results showed that the differential tangential growth is the inducer of cortical folding, and in a hierarchal order, high-amplitude initial undulations on the surface and axonal fibers in the substrate regulate the folding patterns and determine the location of gyri and sulci. The locations with dense axonal fibers after folding settle in gyri rather than sulci. The statistical results also indicated that there is a strong correlation between the location of positive (outward) and negative (inward) initial undulations and the locations of gyri and sulci after folding, respectively. In addition, the locations of 3-hinge gyral folds are strongly correlated with the initial positive undulations and locations of dense axonal fibers. As another finding, it was revealed that there is a correlation between the density of axonal fibers and local gyrification index, which has been observed in imaging studies but not yet fundamentally explained. This study is the first step in understanding the linkage between abnormal gyrification (surface morphology) and disruption in connectivity that has been observed in some brain disorders such as Autism Spectrum Disorder. Moreover, the findings of the study directly contribute to the concept of the regularity and variability of folding patterns in individual human brains.