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Abstract In this project, a new heterogeneous polymeric ionic liquid catalyst based on vinylimidazole, stabilized on magnetic nanoparticles )Fe3O4@Al2O3@[PBVIm]HSO4) was prepared. Then the desired catalyst was identified by TGA, FT-IR, VSM, and TEM techniques. The efficiency of this catalyst was measured in the synthesis of chromene, xanthene, and dihydropyrimidinone. Moreover, the capability of the prepared sorbent for the extraction and determination of BPA (bisphenol A) was studied. Under the optimum conditions, the linearity range of the technique was between 0.5 and 100 µg L−1 with the coefficient of determination (r2) of 0.9948. Relative standard deviations for intra- and inter-day precision for the BPA (bisphenol A) at 20 µg L−1 were in the range of 3.1–3.9% and 3.7–4.2%, respectively. The limit of detection and limit of quantification were 0.07 and 0.48 µg L−1 respectively. Excellent efficiency, compatibility with environmental conditions, and easy recycling of the catalyst are among the most important features of the synthetic catalyst.

Abstract The aim of this paper is to design and Finite Element Analysis (FEA) of a novel rotor topology for a permanent magnet synchronous reluctance machine. According to the advantages and drawbacks of the PMSyncRM and the SPMSM, a conventional PMSyncRM rotor design combined with sur‐face‐mounted magnets is introduced as the SPMSyncRM. The surface‐PM arc size is investigated, so that it is considered as multiplication of an integer coefficient and the angle between two adjacent slots of the stator. The analysis involves simulation of the electromagnetic characteristics and the numerical model of each structure using finite element method. Each E‐Magnetic character is calculated for a better understanding of the benefits of the SPMSyncRM. Applying 2D FEA, the optimised surface‐PM arc size is calculated and the static and dynamic operational behaviour of the SPMSyncRM is simulated. Moreover, short circuit analysis is performed to study the demagnetisation of magnets. All results are reported comparatively considering a conventional PMSyncRM, so that the proposed SPM‐SyncRM topology presents high torque‐power density, lower values of cogging torque, higher values of power factor and efficiency, better static and dynamic performance, and robustness towards demagnetisation.

Abstract Polymer-based catalysts have garnered significant interest for their efficiency, reusability, and compatibility with various synthesis processes. In catalytic applications, polymers offer the advantage of structural versatility, enabling functional groups to be tailored for specific catalytic activities. In this study, we developed a novel magnetic copolymer of methyl methacrylate and maleic anhydride (PMMAn), synthesized via in situ chemical polymerization of methyl methacrylate onto maleic anhydride, using benzoyl peroxide as a free-radical initiator. This polymerization process results in a robust copolymer matrix, which was subsequently hydrolyzed in an alkaline aqueous solution to introduce additional functional groups, yielding hydrolyzed PMMAn. These functional groups enhance the copolymer’s ability to support the deposition of magnetic nanoparticles and participate in catalytic reactions. Following hydrolysis, we fabricated a unique magnetic composite, Fe3O4@Hydrol-PMMAn, by in situ coprecipitating Fe3O4 nanoparticles onto the hydrolyzed copolymer, creating a stable nanocatalyst. The structural and magnetic properties of Fe3O4@Hydrol-PMMAn were thoroughly analyzed using FTIR, XRD, SEM, EDX, VSM, and TGA. The Fe3O4@Hydrol-PMMAn nanocatalyst demonstrated remarkable catalytic performance in synthesizing tetrahydrobenzo[b]pyran derivatives through a three-component reaction, conducted without solvents to support green chemistry principles. A series of reaction parameters were optimized, including solvent choice, catalyst loading, and recyclability. The catalyst performed efficiently across a broad range of aldehydes, delivering high product yields (81–96%) with rapid reaction times (5–30 min) at a low catalyst loading of 0.015 g. A hot filtration test confirmed the heterogeneous nature of the nanocatalyst, which could be recycled up to four cycles with minimal loss in activity. The high yield, short reaction time, solvent-free conditions, and excellent reusability make Fe3O4@Hydrol-PMMAn a promising catalyst. These findings underscore its potential for converting waste products into valuable compounds, highlighting its utility in organic transformations and sustainable synthesis practices. Collectively, this work demonstrates that Fe3O4@Hydrol-PMMAn is highly effective for organic compound synthesis, advancing the development of versatile, sustainable nanocatalysts.

Abstract The oxidation of 5-HMF to HMFCA is an important yet complex process, as it generates high-value chemical intermediates. Achieving this transformation efficiently requires the development of non-precious, highly active catalysts derived from renewable biomass sources. In this work, we introduce UoM-1 (UoM, University of Mazandaran), a novel cobalt-based metal-organic framework (Co-MOF) synthesized using a simple one-step ultrasonic irradiation method. The synthesis employed the ligand 4,4’-((1E,1’E)-((5-carboxy-1,3-phenylene)bis(azaneylylidene))bis (methaneylylidene))dibenzoic acid (H3bdda). A comprehensive suite of analytical techniques, including FT-IR, EDX, ICP, XRD, TEM, DLS, FESEM, and BET-BJH, was used to confirm the structural integrity of the synthesized material. The catalytic performance of UoM-1 was investigated for the selective conversion of HMF to HMFCA, demonstrating its effectiveness as a low-cost, accessible catalyst. To promote a more sustainable and environmentally friendly approach, the oxidation reactions were performed in deep eutectic solvents, which offer a green, low-energy alternative to traditional solvents. This study shows that the UoM-1 catalyst not only provides an economical solution but also aligns with modern green chemistry principles, making it a highly promising candidate for future catalytic applications.

Abstract This study delves into the development and optimization of photocatalysts, namely ZnO NPs/Zeolite and TiO2 NPs/Zeolite, for the degradation of two beta-blocker drugs, including Atenolol (AT) and Metoprolol (ME). Structural and morphological analyses of the catalysts were conducted, and optimal conditions for drug degradation were determined using a Box-Behnken design. The results underscored the significant influence of pH, catalyst amount, drug concentration, and H2O2 concentration on the degradation process using ZnO NPs/Zeolite and TiO2 NPs/Zeolite as the catalysts. The optimal values of drug concentration, pH, catalyst amount, and H2O2 concentration, were determined to be 32 and 33 mg L−1, 4.2 and 4.6, 428 and 386 mg, and 2.6 and 2.5 mM utilizing ZnO NPs/Zeolite and TiO2 NPs/Zeolite as the catalyst, respectively. Following optimization, the kinetics of the photodegradation process were investigated, revealing promising rates and half-life times for both drugs. The pseudo-first-order rate constants for Atenolol and Metoprolol degradation were 0.064 ± 0.007 min−1 and 0.065 ± 0.004 min−1 with ZnO NPs/Zeolite and 0.071 ± 0.007 min−1 and 0.071 ± 0.006 min−1 with TiO2 NPs/Zeolite, respectively. Furthermore, ZnO NPs/Zeolite and TiO2 NPs/Zeolite demonstrated reusability up to 5 and 6 times, respectively, without significant activity loss. The comparative analysis highlighted the superior performance of TiO2 NPs/Zeolite over ZnO NPs/Zeolite, attributed to lower consumption, shorter degradation time, improved reusability, and compatibility with milder acidic conditions. Overall, the research showcases the potential of ZnO NPs/Zeolite and TiO2 NPs/Zeolite as an effective and sustainable solution for removing Metoprolol and Atenolol contaminants.

Abstract In this research, a logical strategy with a recyclable synthetic perspective of view and a rational design to prepare a nanocatalyst with a dendrimer template containing ionic liquid is presented. Magnetic silica nanoparticles were prepared using the Stober method. Their surface was modified with the help of cyanuric chloride, melamine, and 1-methylimidazole as Linkers. Finally, the nanocatalyst was decorated with affordable copper metal. The dendrimer-templated nanocatalyst was identified by different analyses, such as FT-IR, SEM, TEM, XRD, EDX, TGA, CHN, and ICP-OES. Fe3O4@SiO2@NTMP-IL-Cu was used as a heterogeneous nanocatalyst with good performance and reusable in coupling syntheses. The synthesis of A3-coupling and Ullmann coupling was performed under solvent-free and THF conditions, respectively, with high yields. Reusability and high efficiency of products in the vicinity of this catalyst, the use of cheap and available metal are desirable features of this synthetic catalyst.

Abstract Graphite carbon nitride (g-C3N4) is a two-dimensional nano-sheet with electronic properties, which shows unique characteristics with high chemical and thermal stability in its structure. The functionalization of these compounds through covalent bonding is an important step towards significantly improving their properties and capabilities. To achieve this goal, a novel strategy for the covalent functionalization of Fe3O4@g-C3N4 with thiamine hydrochloride (vitamin B1) via cyanuric chloride (TCT), which is a divalent covalent linker, was presented. The efficiency of Fe3O4@gC3N4@Thiamine as a heterogeneous organic catalyst in the synthesis of spirooxindole-pyran derivatives and 2-amino-4H-pyran under solvent-free conditions was evaluated and the yields of high-purity products were presented. In addition, easy recycling and reuse for seven consecutive cycles without significant reduction in catalytic activity are other features of this catalyst. Moreover, the performance of the prepared sorbent in the microextraction technique (herein, magnetic solid phase extraction) was studied. The tebuconazole was selected as the target analyte. The target analyte was extracted and determined by HPLC–UV. Under the optimum condition, the linear range of the method (LDR) was estimated in the range of 0.2–100 μg L−1 (the coefficient of determination of 0.9962 for tebuconazole). The detection limit (LOD) of the method for tebuconazole was calculated to be 0.05 µg L−1. The limit of quantification (LOQ) of the method was also estimated to be 0.16 µg L−1. In order to check the precision of the proposed method, the intra-day and inter-day relative standard deviations (RSD%) were calculated, which were in the range of 1.5- 2.8%. The method was used for the successful extraction and determination of tebuconazole in tomato, cucumber, and carrot samples.

Natural deep eutectic solvents (NADESs) have emerged as a novel class of solvents with properties reminiscent of ionic liquids while offering additional advantages in terms of cost, environmental impact, and synthesis. This article focuses on the applications of NADESs of mannose:urea and glucose:dimethylurea as inexpensive, accessible, and reusable catalysts in the synthesis of dihydropyrimidinone and polyhydroquinoline derivatives. The results demonstrate significant yields for both dihydropyrimidinones (47–99%) and polyhydroquinolines (90–97%) reactions using mannose:urea and glucose:dimethylurea as catalysts. The advantages of NADESs as catalysts include their simple and reproducible preparation, low cost, environmentally benign nature, long-term durability, and tunable properties. This NADESs can also be recovered and reused for four times without a significant loss of activity.

Abstract In this research, Fe3O4@SiO2@NTMPThio-Cu was introduced as a novel and green heterogeneous nanocatalyst with a dendrimer template that is environmentally friendly and reusable based on Fe3O4@SiO2. In this way, magnetic silica nanoparticles were first modified with cyanuric chloride, followed by melamine and thiosemicarbazide, and ultimately, it’s decorated with the cost-effective metal copper. The synthesized nanocatalyst was characterized by various analyses such as FT-IR, XRD, SEM, TGA, and EDX. The efficiency of Fe3O4@SiO2@NTMPThio-Cu was measured in one-pot synthesis of xanthene and spirooxindole-pyran derivatives under mild solvent-free conditions. High efficiency, excellent yield of products, mild reaction conditions, simple operation, no use of toxic organic solvents, and reusability of this catalyst increase the attractiveness of this technique for large-scale environmentally friendly operations.

There has been a growing curiosity and enthusiasm surrounding recent advancements in nanotechnology, electromagnetism, and optics. This interdisciplinary collaboration encompasses fields such as nanomaterials, nanoelectronics, and nanobiotechnology, which often overlap in their applications. One area that has attracted significant attention is the use of metal nanoparticles (MNPs), which has resulted in notable advancements in medicine. MNPs hold the promise of significantly boosting drug delivery efficacy, reducing unwanted side effects, and enhancing delivery precision. They also have applications in diagnostics, the development of biocompatible materials, and the exploration of nutraceuticals. Using metal nanoparticles in drug delivery provides benefits such as increased stability, prolonged circulation time, enhanced distribution, and precise targeting. The field of nanobiotechnnolgy has facilitated the creation of eco-friendly approaches, referred to as green synthesis, for the production of MNPs. MNPs offer improved stability and targeted release in drug delivery, while also providing a more sustainable alternative to chemical synthesis. This review aims to address the challenges and prospects of utilizing MNPs in drug delivery, with a specific focus on sustainable approaches for fabricating and modifying metal nanocarriers. It also explores the application of various MNPs in drug delivery systems (DDSs).

Background: Relationship disengagement is one of the most common reasons reported by couples when explaining the distress and dissolution of the marriage. The present study aimed to investigate the factors affecting relationship disengagement in Iranian couples.Methods: This qualitative study was conducted using the conventional content analysis approach. The participants were 24 Iranian married couples (in Mashhad) who were selected using non-random and purposive sampling. The data were collected through in-depth semi-structured interviews with the couples and the interviews continued until data saturation. The collected were analyzed using Graneheim and Lundman’s qualitative content analysis method.Results: Data analysis revealed three themes (each with some categories): (1) Interpersonal factors (problems related to the family of origin, conflict in couple interactions, distancing behaviors, and ineffective spouse selection), (2) individual-personality factors (emotional instability and character traits), and (3) socioeconomic factors (financial and vocational issues and perceived fairness and inequality).Conclusion: The findings indicated that marital relationship disengagement leads to emotional apathy and dissolution of marital relationships. Couples therapy approaches should target the causes of relationship disengagement to increase the quality of couples’ relationships and prevent divorce. The insights from this study can be used for formulating treatment and preventive approaches to prevent couple relationship disengagement.

Background and Aim: For the Word Recognition Score (WRS) test, homogenous lists of words with similar difficulty levels are needed. This study aimed to develop and validate Turkish-Azeri monosyllabic words with phonetic balance and psychometric homogeneity for the WRS test in young adult Turkish-Azeri speakers in Iran and to compile four 25-item word lists. Methods: In this cross-sectional/comparative study, four lists of 25 monosyllabic words with phonetic balance were created by extracting common words from Turkish-Azeri dialects and assessing them in terms of ease of use, familiarity, and relevance. Then, the lists were tested on 40 young adult Azari speakers aged 18–25 years to determine the validity and reliability. Results: All four lists showed adequate face and content validity. Cronbach’s alpha and split-half values for all four lists were above 0.9, indicating acceptable internal consistency and reliability. Construct validity was confirmed the factor analysis with one-dimensional variance of 77.9%, 80.0%, 79.9%, and 88% for the word lists 1 to 4, respectively, and reported the single-factor solution of the index in all four lists. Also, test-retest reliability with a two-week interval with Pearson correlation coefficients of the lists were 0.94, 0.97, 0.97, and 0.96, respectively. Conclusion: The four developed Turkish-Azeri word lists have phonetic balance and psychometric homogeneity with a high level of validity and reliability, which makes them suitable for evaluating the recognition of monosyllabic words by young adults in hearing centers of Azeri cities in Iran.

Background and Aim: One of the various measures used in speech audiometry is the speech recognition threshold. The aim of this study is to construct psychometrically equivalent lists containing Azari two-syllable words to evaluate speech reception threshold in Azari-speaking adults. Methods: This study is a cross-sectional comparative study of test construction. Common two-syllable words were collected from Azari books. Words with features of ease, familiarity, and relatedness as well as phonetic balance and phonetic dissimilarity were included in 5 lists of 10 words. The lists were evaluated for psychometric evaluations and validity and reliability on young Azari population at 5 intensity levels from –5 to 15 dB HL. After two to four weeks, people were tested again under the same conditions. Results: All 5 lists showed favorable face, content validity index and content validity ratio. The average speech thresholds obtained were 9.62, 9.77, 9.57, 9.67 and 9.57, respectively. Cronbach’s alpha coefficient and halving were obtained above 0.8 in all 5 lists. Test-retest reliability was also significant (p

Abstract Deep eutectic solvents in the extraction of plant metabolites have found many advantages, such as low toxicity, biodegradability, low cost and ease of preparation over the conventional methods. This work aims to compare natural deep eutectic solvents in extraction and optimization of oleoresin from Ferula gummosa and determining its chemical and structure properties. Box–Behnken design was applied to optimize the extraction of oleoresin from Ferula gummosa using eutectic solvents. The variables of extraction were extraction time, temperature, and ratio of eutectic solvents. Six mixtures of eutectic solvents including choline chloride/urea, acetic acid, lactic acid, formic acid, formamide and glycerol at ratios of 2:1 and 3:1 were evaluated. The highest yields were obtained for choline chloride/formic acid, choline chloride/formamide. The quadratic regression equation was set up as a predictive model with an R2 value of 0.85. The optimum condition was 6 h, 40 °C, and ratio 12.5% (w/v). No significant difference was found between the predicted and experimental yield. The main components of the oleoresin were β-pinene (40.27%), cylcofenchen (11.93%) and α-pinene (7.53%) as characterized by gas chromatography-mass spectrometry. The chemical structure study by spectroscopy showed that no solvents remained in the oleoresin. Therefore, F. gummosa oleoresin can be explored as a novel promising natural pharmaceutical ingredient extracted with eutectic solvents.

In this work, we consider multi-hop and mesh hybrid teraHertz/free-space optics (THz/FSO)-based backhaul networks for high data-rate communications. The results are presented for the cases with both out-band integrated access and backhaul (IAB) and non-IAB based communication setups. We consider different deployments of the THz and FSO networks and consider both switching and combining methods between the hybrid THz/FSO links. We study the impact of atmospheric turbulence, atmospheric attenuation, and the pointing error on the FSO communication. The THz communication suffers from small scale fading, path-loss, and the misalignment error. Finally, we evaluate the effects of atmospheric attenuation/path-loss, pointing/misalignment error, small-scale fading, atmospheric turbulence, number of antennas, number of user equipments, number of hops, and the threshold data-rates on the performance of considered systems. As we show, with different network deployments and switching/combining methods, the hybrid implementation of the THz/FSO links improves the network reliability significantly.

In this study, an attempt was made to synthesize a new sorbent based on the second generation of silica coated magnetic poly(amidoamine) (Fe3O4@SiO2@PAMAM) to improve the performance of magnetic solid phase extraction (MSPE) of some antifungal drugs including miconazole, clotrimazole and ticonazole in various real samples such as urine and human plasma. The extracted analytes were measured by high performance liquid chromatography equipped with ultraviolet detection (HPLC-UV). Field emission-scanning electron microscopy (FE-SEM), X-ray diffraction analysis (XRD), Thermogravimetric analysis (TGA), Transmission electron microscopy (TEM) and Fourier transform-infrared spectroscopy (FT-IR) were used to study the morphology and structure of the prepared sorbent. The various factors such as: extraction time, sorbent amount, solvent desorption volume, desorption time, ionic strength and pH were studied and optimized. The method is validated according to ICH guidelines with respect to precision, accuracy, linearity, specificity, robustness, and limits of detection and quantification. Under the optimized condition, the linearity of the method was in the range of 1–500 µg L-1 (miconazole= 1-200 µg L-1, clotrimazole = 1-500 µg L-1 and ticonazole = 1-200 µg L-1). The obtained correlation coefficients (r^2) were between 0.9871-0.9977. The limits of detection (LODs) were also calculated to be 0.14-0.18 µg L-1 (miconazole= 0.16 µg L-1, clotrimazole = 0.18 µg L-1 and ticonazole=0.14 µg L-1). The limits of quantification (LOQs) were also in the range of 0.46-0.60 µg L-1 for the selected analytes. The relative standard deviations (RSDs%), were obtained in the range of 4.6 to 5.9%. Moreover, the calculated enrichment factors were between 85 and 93. The proposed method was also employed for the analysis of various real samples such as urine and plasma samples. The obtained recoveries indicated that the method was useful and applicable in complicated real samples

Abstract Captopril (CAP) is a safe, cost-effective, and environmentally organic compound that can be used as an effective organo-catalyst. Functional groups of captopril make it capable to attach to solid support and acting as promoters in organic transformations. In this work, captopril was attached to the surface of magnetic graphene nitride by employing a linker agent. The synthesized composite efficiently catalyzed two multicomponent reactions including the synthesis of 1,2,3,6-tetrahydropyrimidine and 2-amino-4H-chromene derivatives. A large library of functional targeted products was synthesized in mild reaction conditions. More importantly, this catalyst was stable and magnetically recycled and reused for at least five runs without losing catalytic activity.

Abstract Background In this study, the effect of static magnetic fields (SMFs) on improving the performance of activated sludge process to enhance the higher rate of microbial growth biomass and improve sludge settling characteristics in real operation conditions of wastewater treatment plants has been investigated. The effect of SMFs (15 mT), hydraulic retention time, SRT, aeration time on mixed liquor suspended solids (MLSS) concentrations, mixed liquor volatile suspended solids (MLVSS) concentrations, α-factor, and pH in the complete-mix activated sludge (CMAS) process during 30 days of the operation, were evaluated. Results There were not any differences between the concentration of MLSS in the case (2148.8 ± 235.6 mg/L) and control (2260.1 ± 296.0 mg/L) samples, however, the mean concentration of MLVSS in the case (1463.4 ± 419.2 mg/L) was more than the control samples (1244.1 ± 295.5 mg/L). Changes of the concentration of MLVSS over time, follow the first and second-order reaction with and without exposure of SMFs respectively. Moreover, the slope of the line and, the mean of α-factor in the case samples were 6.255 and, − 0.001 higher than the control samples, respectively. Changes in pH in both groups of the reactors were not observed. The size of the sluge flocs (1.28 µm) and, the spectra of amid I' (1440 cm−1) and II' (1650 cm−1) areas related to hydrogenase bond in the case samples were higher than the control samples. Conclusions SMFs have a potential to being considered as an alternative method to stimulate the microbial growth rate in the aeration reactors and produce bioflocs with the higher density in the second clarifiers.

In this work, we study some introductory properties of the regular Gaussian black holes in pure quadratic gravity. The results show the relative advantages of this model with respect to the similar case in Einstein gravity.

Cancer is a huge phenomenon in human society that it observe in developing countries and even more developed countries in terms of economic as well. Colon cancer is created by increasing cancer cells that its main reason is the uncontrollable growth of cells in Colon. In this research, two groups of stable chromene compounds which was calculated in the previous study using bioinformatics software selected and their toxicity effect and the kind of cell death that they cause investigated on HT-29 cancer cell line, which is related to colon cancer. Also, toxicity of 2-amino-4-(4-chlorophenyl)-5-oxo-4H,5H-pyrano [2,3-c] chromene -2-carbonitrile (S1), 2-amino-4-(4-bromophenyl)-5-oxo-4H,5H-pyrano [2,3-c] chromene -2-carbonitrile (S2) which had an appropriate stable determined. At concentrations of 1, 2, 3, 5, 10 and 20 μg / ml, a control group was performed on HT-29 cancer cell lines in comparison with the chemotherapeutic drug Campusar with similar concentrations of the chemotherapy drug using MTT assay. Analysis of data was done by statistical software Graphpad Prism 8 and ANOVA test and ultimately, the type of cell death which created by Flow cytometry technique was examined. The results showed that chromium derivatives by causing apoptosis in HT-29 cancer cells could be further studied as a suitable candidate for the effect on colon cancer.

In this research, a novel catalyst GO@[PBVIm]HSO4, which is an acidic polymer ionic liquid supported on a graphene oxide substrate, was synthesized. First, (3-aminopropyl) triethoxysilane was attached as a linker to the prepared graphene oxide. In the next step, 1-butyl vinyl imidazolium bromide was used to synthesize the expected polymer catalyst on a solid support. The efficiency of this catalyst was used in various organic chemical reactions such as the synthesis of chromene, xanthene, and dihydropyrimidinone derivatives. Short reaction time, suitable temperature, excellent yield of products, and very good activity of recycled catalyst are among the advantages of this heterogeneous catalyst synthesis.

This paper provides a comprehensive review of the potential of game theory as a solution for sensor-based human activity recognition (HAR) challenges. Game theory is a mathematical framework that models interactions between multiple entities in various fields, including economics, political science, and computer science. In recent years, game theory has been increasingly applied to machine learning challenges, including HAR, as a potential solution to improve recognition performance and efficiency of recognition algorithms. The review covers the shared challenges between HAR and machine learning, compares previous work on traditional approaches to HAR, and discusses the potential advantages of using game theory. It discusses different game theory approaches, including non-cooperative and cooperative games, and provides insights into how they can improve the HAR systems. The authors propose new game theory-based approaches and evaluate their effectiveness compared to traditional approaches. Overall, this review paper contributes to expanding the scope of research in HAR by introducing game-theoretic concepts and solutions to the field and provides valuable insights for researchers interested in applying game-theoretic approaches to HAR.

Abstract Background Previous studies have been inconclusive about racial disparities in sepsis. This study evaluated the impact of ethnic background on management and outcome in sepsis and septic shock. Methods This analysis included 17,146 patients suffering from sepsis and septic shock from the multicenter eICU Collaborative Research Database. Generalized estimated equation (GEE) population-averaged models were used to fit three sequential regression models for the binary primary outcome of hospital mortality. Results Non-Hispanic whites were the predominant group (n = 14,124), followed by African Americans (n = 1,852), Hispanics (n = 717), Asian Americans (n = 280), Native Americans (n = 146) and others (n = 830). Overall, the intensive care treatment and hospital mortality were similar between all ethnic groups. This finding was concordant in patients with septic shock and persisted after adjusting for patient-level variables (age, sex, mechanical ventilation, vasopressor use and comorbidities) and hospital variables (teaching hospital status, number of beds in the hospital). Conclusion We could not detect ethnic disparities in the management and outcomes of critically ill septic patients and patients suffering from septic shock. Disparate outcomes among critically ill septic patients of different ethnicities are a public health, rather than a critical care challenge.

Abstract The use of the kinetic coefficients for the mathematical expression of the biochemical processes and the relationship between the effective parameters is importance. Change of the biokinetic coefficients in the complete-mix activated sludge processes were calculated for 1 month operation of the activated sludge model (ASM) in a Lab-scale in three series. 15 mT intensity of static magnetic fields (SMFs) applied on the aeration reactor (ASM 1), clarifier reactor (ASM 2) and, sludge returning systems (ASM 3) for 1 h, daily. During the operation of the systems, five basic biokinetic coefficients such as maximum specific substrate utilization rate (k), heterotrophic half-saturation substrate concentration (K s ), decay coefficient (k d ), yield coefficient (Y) and, maximum specific microbial growth rate (μ max ) were determined. The rate of k (g COD/g Cells.d) in ASM 1 was 2.69% and, 22.79% higher than ASM 2 and, ASM 3. The value of K s (mg COD/L) was 54.44 and, 71.13 (mg/L) lower than the ASM 2 and, ASM 3. The rate of k d ASM 1, ASM 2 and, ASM 3 was 0.070, 0.054 and, 0.516 (d−1). The value of Y (kg VSS/kg COD) in ASM 1 was 0.58% and, 0.48% lower than ASM 2 and, ASM 3. The rate of μ max (d−1) in ASM 1 was 0.197, this value for ASM 2 and ASM 3 were 0.324 and 0.309 (d−1). Related to the biokinetic coefficients analyses the best location for the application of 15 mT SMFs was the aeration reactor, where the present of oxygen, substrate and, SMFs have the greatest impact on the positive changes of these coefficients.

The soulful curriculum makes the educational environment dynamic and robust. This study’s primary purpose was to identify the essential components of the soulful curriculum from Miller’s viewpoint. An inductive approach and content analysis were applied to achieve this purpose. The essentials, principles, and techniques of the soulful curriculum were extracted from Miller’s perspective, and finally, the critical components of the soulful curriculum were inferred and explained by integrating the essentials, principles and techniques of Miller’s Curriculum. Accordingly, we reviewed Millers’ two seminal works called Holistic Education and Education and the Soul: Toward a Spiritual Curriculum. The cause for selecting these two works was comprehensiveness and consistency in expressing John Miller’s ideas fundamental to orientation. By integrating the results, the essential components of the soulful curriculum were categorized into six dimensions: holism, introspection, naturalism, connectivism, balancing, and energization.

A complex system is a system that has many components that are interdependent and appear as a whole and exhibit organized behavior. Community structure detection is an optimization problem in complex networks that involves searching for communities belonging to a network that shares nodes of a similar community with standard features. In this paper, we use a multi-agent memetic algorithm to detect the structure of the community in complex networks by optimizing the amount of modularity and calling it MAMA-Net. In the multi-agent memetic algorithm, agents are placed in a network-like environment to detect the community. Local search is used to find solution space. Having a local search in the memetic algorithm allows each member of the population to increase its evaluation function based on the suitability of its neighbors and achieve the desired result in minimum time. We compare the performance of MAMA-Net in detecting community structure with some standard algorithms. Both real-world and synthetic benchmark networks are used to evaluate the performance of the proposed method. The results show that MAMA-Net could detect communities more accurately than other comparable algorithms.

Abstract Introduction Intoxications are common in intensive care units (ICUs). The number of causative substances is large, mortality usually low. This retrospective cohort study aims to characterize differences of intoxicated compared to general ICU patients, point out variations according to causative agents, as well as to highlight differences between survivors and non-survivors among intoxicated individuals in a large-scale multi-center analysis. Methods A total of 105,998 general ICU patients and 4,267 individuals with the admission diagnoses “overdose” and “drug toxicity” from the years 2014 and 2015 where included from the eICU Collaborative Research Database. In addition to comparing these groups with respect to baseline characteristics, intensive care measures and outcome parameters, differences between survivors and non-survivors from the intoxication group, as well as the individual groups of causative substances were investigated. Results Intoxicated patients were younger (median 41 vs. 66 years; p

In this study, a composite of zinc tungsten oxide nanoparticles (W-ZnO NPs) has been synthesized via mixing Na2WO4 and zinc acetate in water, followed by dropwise addition of NaOH. The synthesized W-ZnO NPs were characterized using measurement methods such as XRD, dynamic light scattering (DLS), Scanning electron microscopy (SEM) and UV-Vis. Also, the results were compared with the pure synthesized ZnO and WO3 NPs. Non-linear optical properties of the synthesized composite were measured using the Z-scan technique with a continuous wave Nd-Yag laser. The negative non-linear absorption coefficient of the components was obtained which indicates that the saturation absorption occurred in this composite. In comparison with pure ZnO NPs, non-linear absorption decreases which can be attributed to the negligible optical response of WO3 structures. Also, the negative value of the close aperture Z-scan curve shows that the thermal lensing effect is the main reason for the third-order non-linear refraction.

Six catalysts MnL1–MnL6, containing two crown ether rings and their analogs supported on the MCM-41 heterogeneous substrate (MnL1@MCM41-MnL5@MCM41) were synthesized and characterized. A mixture of molecular oxygen, as an oxidant, and these catalysts were used for the epoxidation of styrene. As a general result, the supported catalysts showed better performance compared with the unsupported analogs. On the other hand, the supported species, in addition to recyclability, did not require an axial base and reducing agent.

Deploying access and backhaul as wireless links, a.k.a. integrated access and backhaul (IAB), is envisioned as a viable approach to enable flexible and dense networks. Even further, mobile IAB (mIAB) is a candidate solution to enhance the connectivity of multiple user equipment (UE) moving together. In this context, different of other works from the literature, the present work overviews the basis for the deployment of mIAB by presenting: 1) the current status of IAB standardization in the fifth generation (5G) new radio (NR); 2) a new taxonomy for state-of-the-art works regarding fixed IAB and mIAB; 3) an extensive performance analysis of mIAB based on simulation results; and 4) open challenges and potential future prospects of mIAB. Specifically, the proposed taxonomy classifies IAB works according to different perspectives and categorizes mIAB works according to the type of mobile node. For each type of mobile node, the main studied topics are presented. Regarding the performance evaluation, we consider an urban macro scenario where mIAB nodes are deployed in buses in order to improve the passengers’ connection. The results show that, compared to other network architectures, the deployment of mIAB nodes remarkably improves the passengers’ throughput and latency in both downlink and uplink.

Background COVID-19 remains a complex disease in terms of its trajectory and the diversity of outcomes rendering disease management and clinical resource allocation challenging. Varying symptomatology in older patients as well as limitation of clinical scoring systems have created the need for more objective and consistent methods to aid clinical decision making. In this regard, machine learning methods have been shown to enhance prognostication, while improving consistency. However, current machine learning approaches have been limited by lack of generalisation to diverse patient populations, between patients admitted at different waves and small sample sizes. Objectives We sought to investigate whether machine learning models, derived on routinely collected clinical data, can generalise well i) between European countries, ii) between European patients admitted at different COVID-19 waves, and iii) between geographically diverse patients, namely whether a model derived on the European patient cohort can be used to predict outcomes of patients admitted to Asian, African and American ICUs. Methods We compare Logistic Regression, Feed Forward Neural Network and XGBoost algorithms to analyse data from 3,933 older patients with a confirmed COVID-19 diagnosis in predicting three outcomes, namely: ICU mortality, 30-day mortality and patients at low risk of deterioration. The patients were admitted to ICUs located in 37 countries, between January 11, 2020, and April 27, 2021. Results The XGBoost model derived on the European cohort and externally validated in cohorts of Asian, African, and American patients, achieved AUC of 0.89 (95% CI 0.89–0.89) in predicting ICU mortality, AUC of 0.86 (95% CI 0.86–0.86) for 30-day mortality prediction and AUC of 0.86 (95% CI 0.86–0.86) in predicting low-risk patients. Similar AUC performance was achieved also when predicting outcomes between European countries and between pandemic waves, while the models showed high calibration quality. Furthermore, saliency analysis showed that FiO2 values of up to 40% do not appear to increase the predicted risk of ICU and 30-day mortality, while PaO2 values of 75 mmHg or lower are associated with a sharp increase in the predicted risk of ICU and 30-day mortality. Lastly, increase in SOFA scores also increase the predicted risk, but only up to a value of 8. Beyond these scores the predicted risk remains consistently high. Conclusion The models captured both the dynamic course of the disease as well as similarities and differences between the diverse patient cohorts, enabling prediction of disease severity, identification of low-risk patients and potentially supporting effective planning of essential clinical resources. Trial registration number NCT04321265. Author summary COVID-19 remains a complex disease, making it challenging to estimate the risk of deterioration of critically ill patients and consequently allocation of clinical resources, such as ventilators. As a result, there is a need to support clinical decision making through objective methods and address some of the limitations of the current clinical scoring systems. In response, we developed machine learning models using routine clinical data of patients from 37 countries worldwide, including 18 European countries. We find that: i) machine learning models can predict outcomes in patients from diverse European countries, that is which patients have a low risk of deterioration and which may require increased care such that resources are allocated efficiently; ii) routine clinical data from European patients can be used to predict outcomes in non-European patients, namely those admitted in Asian, African, and American intensive care units, without significantly affecting the performance, and iii) routine clinical data collected during the first COVID-19 pandemic wave, can be used to predict the risk of deterioration of patients admitted during subsequent waves. Our study is the first step towards improving standardisation and equity of critical care across healthcare institutions and further afield across diverse countries and territories.

Abstract Background Bacterial microleakage is an important cause of apical periodontitis and endodontic treatment failure. This study aimed to assess the bacterial microleakage of nano-mineral trioxide aggregate (nano-MTA) as a sealer, Endoseal MTA, and GuttaFlow Bioseal sealers in atmospheric pressure, and simulated underwater diving and aviation conditions. Methods In this in vitro, experimental study, 180 extracted single-rooted teeth were cleaned and shaped, and were then randomly divided into three groups for single-cone obturation using Endoseal MTA, GuttaFlow Bioseal, or nano-MTA as a sealer. Each group was then randomly divided into three subgroups, and subjected to ambient atmospheric pressure, 2 atm pressure (to simulate underwater diving), and 0.5 atm pressure (to simulate aviation) using a custom-made pressure chamber. The teeth then underwent microbial leakage test using Streptococcus mutans (S. mutans), and the percentage of samples showing microleakage was recorded for up to 1 month, and analyzed using the Chi-square test. Results The three sealer groups were significantly different regarding bacterial microleakage (P 0.05). Conclusion Within the limitations of this in vitro study, it may be concluded that single-cone obturation technique using nano-MTA as a sealer results in lower resistance to bacterial microleakage compared with the use of GuttaFlow Bioseal, and Endoseal MTA. Pressure changes in simulated underwater diving and aviation conditions had no significant effect on bacterial microleakage. Trial Registration Number This is not a human subject research.

The aim of present study was a comparative study of educational achievement assessment system of primary schools in Syria and Iran. For data collection, curriculum document analysis and semi-structured interviews with primary school teachers were used. Participants included 15 primary school teachers in both countries. The data obtained from the interview were analyzed using MAXQDA software. The results showed that assessment system of academic achievement in primary schools of Iran is qualitative-descriptive; whereas In Syria, it is quantitative, and pupils must obtain required scores to be promoted to a higher grade. Iranian students are interested in participating in qualitative assessment and this method has reduced their stress and anxiety. Conversely, Syrian students experience anxiety, fear, stress, and lack of self-confidence, and most feel disgusted with quantitative assessment system of academic achievement. The recommendation of study is reconsideration of assessment system – based on the goals of educational system and philosophical and psychological foundations – in Syria. It is also recommended to deepen and develop descriptive evaluation in Iran.

Abstract Background Mechanical Ventilation (MV) is a complex and central treatment process in the care of critically ill patients. It influences acid–base balance and can also cause prognostically relevant biotrauma by generating forces and liberating reactive oxygen species, negatively affecting outcomes. In this work we evaluate the use of a Recurrent Neural Network (RNN) modelling to predict outcomes of mechanically ventilated patients, using standard mechanical ventilation parameters. Methods We performed our analysis on VENTILA dataset, an observational, prospective, international, multi-centre study, performed to investigate the effect of baseline characteristics and management changes over time on the all-cause mortality rate in mechanically ventilated patients in ICU. Our cohort includes 12,596 adult patients older than 18, associated with 12,755 distinct admissions in ICUs across 37 countries and receiving invasive and non-invasive mechanical ventilation. We carry out four different analysis. Initially we select typical mechanical ventilation parameters and evaluate the machine learning model on both, the overall cohort and a subgroup of patients admitted with respiratory disorders. Furthermore, we carry out sensitivity analysis to evaluate whether inclusion of variables related to the function of other organs, improve the predictive performance of the model for both the overall cohort as well as the subgroup of patients with respiratory disorders. Results Predictive performance of RNN-based model was higher with Area Under the Receiver Operating Characteristic (ROC) Curve (AUC) of 0.72 (± 0.01) and Average Precision (AP) of 0.57 (± 0.01) in comparison to RF and LR for the overall patient dataset. Higher predictive performance was recorded in the subgroup of patients admitted with respiratory disorders with AUC of 0.75 (± 0.02) and AP of 0.65 (± 0.03). Inclusion of function of other organs further improved the performance to AUC of 0.79 (± 0.01) and AP 0.68 (± 0.02) for the overall patient dataset and AUC of 0.79 (± 0.01) and AP 0.72 (± 0.02) for the subgroup with respiratory disorders. Conclusion The RNN-based model demonstrated better performance than RF and LR in patients in mechanical ventilation and its subgroup admitted with respiratory disorders. Clinical studies are needed to evaluate whether it impacts decision-making and patient outcomes. Trial registration: NCT02731898 ( https://clinicaltrials.gov/ct2/show/NCT02731898 ), prospectively registered on April 8, 2016.

In this paper, we introduce a subcategory ∼Sh* of Sh* and obtain some results in this subcategory. First we show that there is a natural bijection Sh(∑(X, x), (Y,y))≅Sh((X,x),Sh((I, Ī),(Y,y))), for every (Y,y)∈ ~Sh* and (X,x)∈ Sh*. By this fact, we prove that for any pointed topological space (X,x) in ∼Sh*,πntop(X,x)≅ πn-ktop(Sh((Sk, *),(X,x)), ex), for all 1≤k ≤n-1.

In this research coated palladium nanoparticles was synthesized on modified GO by thymbraspicata extract with simple and green procedure and used as adequate and renewable nanocatalyst for Suzuki coupling reactions between phenylboronic acid and different aryl halides. The Pd NPs/RGO Nanocatalyst was synthesized by surface modification of GO and in-Situ reduction. The extract of Thymbraspicata was used as a reducing and immobilizing agent for Pd nanoparticles. The results show that Pd(0) nanoparticles are completely dispersed on the GO functionalized surface. Pd NPs/RGO nanocatalyst as a recoverable nanocatalyst shows high catalytic activity in Suzuki coupling reaction. In addition, the synthesized catalyst can be reused several times without significant altering its catalytic activity.

Abstract This current research is based on a bio-inspired procedure for the synthesis of biomolecule functionalized hybrid magnetic nanocomposite with the Fe3O4 NPs at core and Pd NPs at outer shell. The central idea was the initial modification of magnetic NP by the phytochemicals from Fritillaria imperialis flower extract, which was further exploited in the green reduction of Pd2+ ions into Pd NPs, in situ. The flower extract also acted as a capping agent for the obtained Pd/Fe3O4 composite without the need of additional toxic reagents. The as-synthesized Fe3O4@Fritillaria/Pd nanocomposite was methodically characterized over different physicochemical measures like FT-IR, ICP-AES, FESEM, EDX, TEM, XPS and VSM analysis. Thereafter, its catalytic potential was evaluated in the reduction of various nitrobenzenes to arylamines applying hydrazine hydrate as reductant in ethanol/water (1:2) medium under mild conditions. Furthermore, the nanocatalyst was retrieved using a bar magnet and recycled several times without considerable leaching or loss of activity. This green, bio-inspired ligand-free protocol has remarkable advantages like environmental friendliness, high yields, easy workup and reusability of the catalyst.

In this paper, we study the throughput utility functions in buffer-equipped monostatic backscatter communication networks with multi-antenna Readers. In the considered model, the backscatter nodes (BNs) store the data in their buffers before transmission to the Reader. We investigate three utility functions, namely, the sum, the proportional and the common throughput. We design online admission policies, corresponding to each utility function, to determine how much data can be admitted in the buffers. Moreover, we propose an online data link control policy for jointly controlling the transmit and receive beamforming vectors as well as the reflection coefficients of the BNs. The proposed policies for data admission and data link control jointly optimize the throughput utility, while stabilizing the buffers. We adopt the min-drift-plus-penalty (MDPP) method in designing the control policies. Following the MDPP method, we cast the optimal data link control and the data admission policies as solutions of two independent optimization problems which should be solved in each time slot. The optimization problem corresponding to the data link control is non-convex and does not have a trivial solution. Using Lagrangian dual and quadratic transforms, we find a closed-form iterative solution. Finally, we use the results on the achievable rates of finite blocklength codes to study the system performance in the cases with short packets. As demonstrated, the proposed policies achieve optimal utility and stabilize the data buffers in the BNs.

First-order Marcum Q -function is observed in various problem formulations. However, it is not an easy-to-handle function. For this reason, in this article, we first present a semi-linear approximation of the Marcum Q -function. Our proposed approximation is useful because it simplifies, e.g., various integral calculations including Marcum Q -function as well as different operations such as parameter optimization. Then, as an example of interest, we apply our proposed approximation approach to the performance analysis of predictor antenna (PA) systems. Here, the PA system is referred to as a system with two sets of antennas on the roof of a vehicle. Then, the PA positioned in the front of the vehicle can be used to improve the channel state estimation for data transmission of the receive antenna that is aligned behind the PA. Considering spatial mismatch due to the mobility, we derive closed-form expressions for the instantaneous and average throughput as well as the throughput-optimized rate allocation. As we show, our proposed approximation scheme enables us to analyze PA systems with high accuracy. Moreover, our results show that rate adaptation can improve the performance of PA systems with different levels of spatial mismatch.

In this paper, we study the problem of topology optimization and routing in integrated access and backhaul (IAB) networks, as one of the promising techniques for evolving 5G networks. We study the problem from different perspectives. We develop efficient genetic algorithm-based schemes for both IAB node placement and non-IAB backhaul link distribution, and evaluate the effect of routing on bypassing temporal blockages. Here, concentrating on millimeter wave-based communications, we study the service coverage probability, defined as the probability of the event that the user equipments’ (UEs) minimum rate requirements are satisfied. Moreover, we study the effect of different parameters such as the antenna gain, blockage, and tree foliage on the system performance. Finally, we summarize the recent Rel-16 as well as the upcoming Rel-17 3GPP discussions on routing in IAB networks, and discuss the main challenges for enabling mesh-based IAB networks. As we show, with a proper network topology, IAB is an attractive approach to enable the network densification required by 5G and beyond.

In this paper, we determine the structure of the nilpotent multipliers of all pairs (G,N) of finitely generated abelian groups where N admits a complement in G. Moreover, some inequalities for the nilpotent multipliers of pairs of finite groups and their factor groups are given.

The aim of present study was to investigate competencies of employment in the field of educational sciences in Iran and Syria through comparative research method. In the qualitative section, competencies were collected through documentary study and semi-structured interviews. In this section, the participants included 8 faculty members of Department of Educational Sciences, Ferdowsi University of Mashhad and 7 members of Tartus University of Syria, which were selected by targeted sampling method. In quantitative section, expert evaluation and questionnaire were used to validate the competencies. Data analysis of qualitative part was done through open and axial coding and quantitative part was performed using mean comparison test (One Sample T-Test). The research findings showed that employability qualifications of undergraduate course in educational sciences of both universities can be divided into two groups of general and professional competencies. General competencies include four categories: intellectual, interpersonal (communication), leadership and individual skills; and specialized competencies include five categories: educational evaluation, psychological skill, technology skill, curriculum and specialized knowledge. The results of single-sample t-test showed that general competencies in both universities are same in intellectual skill, but there is a difference between two universities in individual, communication and leadership skills. The results also confirm that in terms of professional competence, both universities are similar in terms of educational and technological evaluation components, but there is a difference in psychological skills, curriculum and specialized knowledge.

Glycine is a non-essential amino acid used in fish nutrition, and possess several important roles in physiological process. Despite such functions, little is known about the glycine roles in fish, particularly in sturgeons. Therefore, the present study aimed at assessing the effects of dietary glycine supplementation on growth performance, antioxidant, and immunological parameters in beluga, Huso huso. Four hundred eighty fish (~ 48 g) were randomly distributed in 12 fiberglass tanks (1200 L) at a stocking density of 40 fish per tank. Four diets supplemented with 0% (control), 0.25% (Gly0.25), 0.5% (Gly0.5), and 1% (Gly1) glycine were offered to the fish (each diet to a batch of three tanks) for eight weeks at water temperature of 23.2 ± 0.70 °C. At the end of the feeding trial, the fish were blood-sampled for blood leukocyte count, plasma cortisol, glucose, triglyceride, cholesterol, reduced glutathione (GSH), glutathione reductase (GR), glutathione peroxidase (GPx), malondialdehyde (MDA), lysozyme, and alternative complement activity (ACH50) analysis. The results indicated there were no significant differences in the fish final weight (197–213 g; P = 0.511), weight gain (299–311%; P = 0.956) specific growth rate (2.46–2.52%/d; P = 0.944), feed conversion ratio (0.97–1.03; P = 0.863), protein efficiency ratio (2.29–2.45; P = 0.775), and survival (91.7–100%; P = 0.306) among the treatments. Plasma cortisol level significantly decreased in Gly0.25 treatment, compared to the control (24.7 vs. 28.8 ng/mL; P = 0.035). Plasma glucose levels exhibited significant (P

BackgroundThe COVID-19 pandemic caused by SARS-CoV-2 is challenging health care systems globally. The disease disproportionately affects the elderly population, both in terms of disease severity and mortality risk. ObjectiveThe aim of this study was to evaluate machine learning–based prognostication models for critically ill elderly COVID-19 patients, which dynamically incorporated multifaceted clinical information on evolution of the disease. MethodsThis multicenter cohort study (COVIP study) obtained patient data from 151 intensive care units (ICUs) from 26 countries. Different models based on the Sequential Organ Failure Assessment (SOFA) score, logistic regression (LR), random forest (RF), and extreme gradient boosting (XGB) were derived as baseline models that included admission variables only. We subsequently included clinical events and time-to-event as additional variables to derive the final models using the same algorithms and compared their performance with that of the baseline group. Furthermore, we derived baseline and final models on a European patient cohort, which were externally validated on a non-European cohort that included Asian, African, and US patients. ResultsIn total, 1432 elderly (≥70 years old) COVID-19–positive patients admitted to an ICU were included for analysis. Of these, 809 (56.49%) patients survived up to 30 days after admission. The average length of stay was 21.6 (SD 18.2) days. Final models that incorporated clinical events and time-to-event information provided superior performance (area under the receiver operating characteristic curve of 0.81; 95% CI 0.804-0.811), with respect to both the baseline models that used admission variables only and conventional ICU prediction models (SOFA score, P

In this article, we introduce and study the potentials and challenges of integrated access and backhaul (IAB) as one of the promising techniques for evolving 5G networks. We study IAB networks from different perspectives. We summarize the recent Rel-16 as well as the upcoming Rel-17 3GPP discussions on IAB, and highlight the main IAB-specific agreements on different protocol layers. Also, concentrating on millimeter wave-based communications, we evaluate the performance of IAB networks in both dense and suburban areas. Using a finite stochastic geometry model, with random distributions of IAB nodes as well as user equipments (UEs) in a finite region, we study the service coverage rate defined as the probability of the event that the UEs' minimum rate requirements are satisfied. We present comparisons between IAB and hybrid IAB/fiber-backhauled networks where a part or all of the small base stations are fiber-connected. Finally, we study the robustness of IAB networks to weather and various deployment conditions and verify their effects, such as blockage, tree foliage, rain as well as antenna height/gain on the coverage rate of IAB setups, as the key differences between the fiber-connected and IAB networks. As we show, IAB is an attractive approach to enable the network densification required by 5G and beyond.

Non-orthogonal multiple access (NOMA) has been considered as a study-item in 3GPP for 5G new radio (NR). However, it was decided not to continue with it as a work-item, and to leave it for possible use in beyond 5G. In this paper, we first review the discussions that ended in such decision. Particularly, we present simulation comparisons between the Welch-bound equality spread multiple access (WSMA)-based NOMA and multi-user multiple-input-multiple-output (MU-MIMO), where the possible gain of WSMA-based NOMA, compared to MU-MIMO, is negligible. Then, we summarize the 3GPP discussions on NOMA, and propose a number of methods to reduce the implementation complexity and delay of both uplink (UL) and downlink (DL) NOMA-based transmission, as different ways to improve its efficiency. Here, particular attention is paid to reducing the receiver complexity, the cost of hybrid automatic repeat request as well as the user pairing complexity. As demonstrated, different smart techniques can be applied to improve the energy efficiency and the end-to-end transmission delay of NOMA-based systems.

ABSTRACT The growth in the elderly population has posed a social, economic and health challenge for the twenty-first century. Objective: Aging is often characterized by changes in cognitive functions which affect the receptive and expressive capabilities of language. Since language plays a significant role in human life, we evaluate the existence of age-related differences in narrative and persuasive discourses. Methods: The narrative discourse of 91 adults and persuasive discourse of 92 adults,aged from 19 to 75 years and stratified into four age groups,were examined. Results: There was a statistically significant difference between coherence in the elderly group and each of the other three age groups for both types of discourse. There was also a significant difference for the cohesion variable between the elderly and the first age group for narrative discourse only. Conclusion: The results of this study demonstrate that discourse is influenced by aging and type (genre) of discourse task. Therefore, it is essential for clinicians to take into account the linguistic needs of elderly and incorporate these into their clinical programs. Also, this finding can help clinicians to distinguish between discourses of normal aging and other neurologic disorders (for example dementia, right hemisphere damage, aphasia).

Background: Performance-based payment is a payment model that attempts to reward the measured dimensions of performance and encourages health service providers to achieve predetermined goals by financial incentives. This study aimed to identify executive challenges of performance-based payment from medical and educational hospitals administrators’ perspective and offering solutions in Isfahan 2018. Methods: This study was a qualitative study. Semi structured interviews were used to collect data. The research population was 11 people (the administrators of educational and medical hospitals in Isfahan) who were selected purposefully. All interviews were recorded and then written on a paper. The duration of the interviews varied between 45 to 60 minutes. The data were analyzed using MAXQDA12 software and based on thematic analysis. Results: In this study, , regarding executive challenges, seven themes and fifteen sub-themes were obtained, including the weakness of the performance-based payment project, weakness in education and educational support, low employee participation, weakness of information and communication technology, weakness of laws and regulations, unfavorable economic conditions of the public sector, and special conditions governing public hospitals. Conclusion: performance-based payment, if implemented correctly, can lead to the improvement of quantitative and qualitative indicators related to employees’ performance. Correct implementation requires identifying challenges and obstacles and then corrective actions. This study was able to identify and present some of the operational challenges of the performance-based payment from the viewpoint of hospital administrators.

Purpose: Old (>64 years) and very old (>79 years) intensive care patients with sepsis have a high mortality. In the very old, the value of critical care has been questioned. We aimed to compare the mortality, rates of organ support, and the length of stay in old vs. very old patients with sepsis and septic shock in intensive care.Methods: This analysis included 9,385 patients, from the multi-center eICU Collaborative Research Database, with sepsis; 6184 were old (aged 65–79 years), and 3,201 were very old patients (aged 80 years and older). A multi-level logistic regression analysis was used to fit three sequential regression models for the binary primary outcome of ICU mortality. A sensitivity analysis in septic shock patients (n = 1054) was also conducted.Results: In the very old patients, the median length of stay was shorter (50 ± 67 vs. 56 ± 72 h; p < 0.001), and the rate of a prolonged ICU stay was lower (>168 h; 9 vs. 12%; p < 0.001) than the old patients. The mortality from sepsis was higher in very old patients (13 vs. 11%; p = 0.005), and after multi-variable adjustment being very old was associated with higher odds for ICU mortality (aOR 1.32, 95% CI 1.09–1.59; p = 0.004). In patients with septic shock, mortality was also higher in the very old patients (38 vs. 36%; aOR 1.50, 95% CI 1.10–2.06; p = 0.01).Conclusion: Very old ICU-patients suffer from a slightly higher ICU mortality compared with old ICU-patients. However, despite the statistically significant differences in mortality, the clinical relevance of such minor differences seems to be negligible.

K. Borsuk in 1979, at the Topological Conference in Moscow, introduced concept of the capacity of a compactum and asked some questions concerning properties of the capacity ofcompacta. In this paper, we give partial positive answers to three of these questions in some cases. In fact, by describing spaces homotopy dominated by Moore and Eilenberg-MacLane spaces, the capacities of a Moore space $M(A,n)$ and an Eilenberg-MacLane space $K(G,n)$ could be obtained. Also, we compute the capacity of wedge sum of finitely many Moore spaces of different degrees and the capacity of product of finitely many Eilenberg-MacLane spaces of different homotopy types. In particular, we compute the capacity of wedge sum of finitely many spheres of the same or different dimensions.