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The Hurst exponent (H) isolated in fractal analyses of neuroimaging time-series is implicated broadly in cognition. Within this literature, H is associated with multiple mental disorders, suggesting that H is transdimensionally associated with psychopathology. Here, we unify these results and demonstrate a pattern of decreased H with increased general psychopathology and attention-deficit/hyperactivity factor scores during a working memory task in 1,839 children. This pattern predicts current and future cognitive performance in children and some psychopathology in 703 adults. This pattern also defines psychological and functional axes associating psychopathology with an imbalance in resource allocation between fronto-parietal and sensory-motor regions, driven by reduced resource allocation to fronto-parietal regions. This suggests the hypothesis that impaired working memory function in psychopathology follows from a reduced cognitive resource pool and a reduction in resources allocated to the task at hand.

This study proposes 3D-printed Poly L-lactic acid (PLA) scaffolds coated with alginate/MgO, and includes three different cellular topologies. Three unique scaffold models were considered: Perovskite type 1 (P1), Perovskite type 2 (P2), and IWP. Each scaffold was coated with alginate/MgO at the concentrations of 0 wt%, 5 wt%, 10 wt%, 15 wt%, and 20 wt%. For morphological and phase study, the microstructure of fabricated scaffolds was characterized using a Field Emission Scanning Electron Microscope (FESEM), energy dispersive spectroscopy (EDS), and X-ray diffraction (XRD) analysis. Besides, the biological characteristics of scaffolds, such as biocompatibility, antibacterial activity, and cell survival were studied after 21 days of soaking in the simulated body fluid (SBF). The results of biological studies indicate that the apatite layer covered the majority of composite scaffold's surface and sealed the pores' surface. The material properties of Alginate/MgO RVEs were evaluated under PBC, and it described that the elastic modulus enhanced from 100 (pure Alginate) to 130 MPA by adding 20 wt% MgO nanoparticles. The presented findings were compared to the results obtained by the experimental procedure and revealed satisfactory agreement. RVE-achieved material properties were used in the additional studies on the scaffolds to find the best candidate due to the material properties and architectures. Furthermore, experiment and finite element simulation were used to evaluate the mechanical properties of scaffolds under the compressive deformation. According to the results, the compressive strength of structures follows the order σ

Introduction: Exercise and the use of herbal supplements are among the therapeutic interventions in controlling type 2 diabetes. This study aimed to compare the effect of exercise and karela supplement on glycemic control and metabolic complications in patients with type 2 diabetes. Methods: In the present quasi-experimental study, 120 patients with type 2 diabetes were selected by purposive sampling and were randomly divided into 4 groups of exercise, karela supplement, combined, and control. Exercises included 8-week pyramid aerobic training, 3 sessions per week. Karela was consumed in a dose of 50 mg/kg body weight daily in form of karela powder. Results: There was a significant decrease in fasting blood sugar (FBS), 2-hour postprandial glucose (2hPP), insulin resistance, and glycated hemoglobin (HbA1 c) in the intervention groups compared to the control group (P0.05). Conclusion: According to the results, it can be said that both methods of exercise and karela consumption have a positive effect on glycemic control in type 2 diabetes, but interventions and the combination of exercise and the supplement are more effective in glycemic control than karela alone.

This study evaluates the vulnerability of aquifers to the nitrate concentration variations. Prediction of nitrate concentration using MT3DMs modeling for a period of 10 years. The results showed th...

Introduction: Regular physical activity provides many health benefits to older adults. As a well-known form of physical activity, cycling can be an appropriate means for older people to meet WHO recommendations and to improve their health. In addition, cycling can help to protect the environment and reduce greenhouse gas emissions. The primary aim of this scoping review is to identify the currently available scientific evidence and gaps of research in this field. Methods: A systematic search in seven databases resulted in 7,192 studies. After the exclusion of duplicates, studies were screened by two independent reviewers in a two-stage process. Based on previously defined inclusion criteria, 123 studies were included. Data extraction was based on a descriptive analytical method, and seven categories for the main topics of studies were developed. Data were extracted by three reviewers to analyze different characteristics of included articles such as age range, study design, data type, gender, type of bicycle, and country of origin. Results: The included studies covered the following topics: (1) traffic safety, (2) cycling as physical activity or for transport, (3) health benefits, (4) environmental factors, (5) facilitators and barriers, (6) application of technology and (7) promotion of cycling. Results show that the majority of studies were performed in both younger (60–79 years) and older (80+ years) adults. Most studies had an observational study design, used conventional bicycles, and were based on quantitative methods. Researchers from the United States, Netherlands, and Japan published the highest number of studies related to cycling. Discussion: Traffic safety was the most prevalent focus of the included studies. Gaps were identified with regard to studies focusing on the promotion of cycling, application of technology, as well as facilitators and barriers of cycling. While research on traffic safety should continue to be a high priority for public health, potentially more research should focus on how to get older people to bicycle more. This is warranted by the proven individual and planetary health benefits of cycling and the urgency of combating climate change.

In this work, a new heterogeneous catalyst, comprising gold supported on DABCO-triazole ionic liquid-modified magnetic nanoparticles (Fe3O4@DT-Au), is developed for A3-coupling reaction. This nano-catalyst is characterized using different techniques, such as TEM, SEM, SEM-elemental mapping, XRD, XPS, and TGA. Using a 0.05 mol% of this catalyst, the three-component reaction of amines, aldehydes and alkynes is efficiently performed at 40 °C in water. This catalyst is easily recovered and recycled through external magnetic forces for six times with a small decrease in the activity and re-used catalyst was characterized. The authors are grateful to Institute for Advanced Studies in Basic Sciences (IASBS) Research Council, Zanjan University and Iran National Science Foundation (INSF-Grant number of 99023403) for support of this work. We gratefully acknowledge financial support from the Spanish Ministerio de Ciencia, Innovación y Universidades (projects CTQ2016-81893REDT, and RED2018-102387-T) the Spanish Ministerio de Economía, Industria y Competitividad, Agencia Estatal de Investigación (AEI) and Fondo Europeo de Desarrollo Regional (FEDER, EU) (projects CTQ2016-76782-P, CTQ2016-80375-P, CTQ2017-82935-P and PID2019-107268GB-I00), the Generalitat Valenciana (IDIFEDER/2021/013), and the University of Alicante.

ObjectivesBrain segmentation of infant magnetic resonance (MR) images is vitally important in studying developmental mental health and disease. The infant brain undergoes many changes throughout the first years of postnatal life, making tissue segmentation difficult for most existing algorithms. Here, we introduce a deep neural network BIBSNet (Baby andInfantBrainSegmentation NeuralNetwork), an open-source, community-driven model that relies on data augmentation and a large sample size of manually annotated images to facilitate the production of robust and generalizable brain segmentations.Experimental DesignIncluded in model training and testing were MR brain images on 84 participants with an age range of 0-8 months (median postmenstrual ages of 13.57 months). Using manually annotated real and synthetic segmentation images, the model was trained using a 10-fold cross-validation procedure. Testing occurred on MRI data processed with the DCAN labs infant-ABCD-BIDS processing pipeline using segmentations produced from gold standard manual annotation, joint-label fusion (JLF), and BIBSNet to assess model performance.Principal ObservationsUsing group analyses, results suggest that cortical metrics produced using BIBSNet segmentations outperforms JLF segmentations. Additionally, when analyzing individual differences, BIBSNet segmentations perform even better.ConclusionsBIBSNet segmentation shows marked improvement over JLF segmentations across all age groups analyzed. The BIBSNet model is 600x faster compared to JLF and can be easily included in other processing pipelines.

The optimization of laser cutting process parameters relies on productivity and obtained edge quality. Whereas maximizing cutting speed is a default procedure to increase the process performance, quality assessment of a cut edge is a non-trivial task. Both contact-based and image-based approaches can be used to quantify the quality of a cut surface. Since contact-based techniques are time-consuming and typically require expert knowledge, the development of simple and fast image-based approaches could improve the performance of sheet metal workshops. Due to the numerous quality characteristics that have to be considered, a significant challenge remains to establish a versatile approach for image-based quality evaluation. Within this paper, the quality assessment of laser cut edges by means of image processing techniques is analyzed. Additionally, the potential for employing visual evaluation to assess all quality indicators in a comprehensive measuring strategy is explored. Finally, the role of the presented approaches in shifting toward intelligent manufacturing is briefly discussed.

PurposeThe present study aims to assess the potential impacts of board members' characteristics, including connectedness and independence, on the level of the firm's involvement in innovation and corporate social responsibility (CSR).Design/methodology/approachVariables of board members' interlock and independence are selected for measuring the board characteristics and their association with innovation. The range of disclosure of social responsibility (SR) of the firms inside and outside the industries is also analyzed through descriptive-correlational. The selected sample includes 280 firm-years listed firms on Iraq Stock Exchange during 2012–2017 and 1,026 firm-years on the Tehran Stock Exchange. The hypotheses are examined using multivariate regression models and panel data.FindingsThe observations show that board interlock and independence in both countries are willing to improve firms' innovation. Moreover, having controlled the industry index, the authors find that business environment innovation is willing to be transmitted into the firms through outside industry sources in Iran. In the Iraq country, regardless of industry index, the positive association between interlocked boards and firm innovation is established. Further analyses also articulate that board interlock is not considered a mechanism to transmit information and experiences about CSR activities.Originality/valueThis paper is a pioneer study to assess the relationship between board member characteristics and the firms' innovation and SR both in Iran and Iraq. Also, it extends the literature by considering the industry index as a significant source of knowledge and experience to gain more precise results. Therefore, the current paper may contribute to the development of knowledge in this field of study.

Purpose This study aims to assess the effect of the COVID 19 on small and medium-sized family firms’ risk-taking in Iraq. Design/methodology/approach Data was collected by distributing the questioners. The statistical population consists of 600 employers and small and medium-sized family and non-family firm managers. Hypothesis analysis was carried out after evaluating the questionnaire’s validity and reliability using the structural equation method. Findings The results indicate that COVID 19 influences small and medium-size family and non-family firms’ risk-taking. Originality/value Since no study carried out so far on the effect of COVID 19 on risk-taking of family and non-family Iraqi small- and medium-enterprise firms and since the political-economic condition of Iraq has been affected recently due to the presence of ISIS, its effects, as well as the civil war that taken place before COVID 19, assessing such a topic can contribute to the development of science and knowledge in this field.

ispartof: pages:564-569 ispartof: Procedia CIRP vol:113 pages:564-569 ispartof: 21st CIRP Conference on Electro Physical and Chemical Machining [ISEM XXI] location:Zurich, Switzerland date:14 Jun - 16 Jun 2022 status: Published online

One of the problems with the current environment due to population growth and development is the issue of Waste, landfill, and leachate production. Waste as a high-volume output source, multiple potential users for landfill sites, and leachate are problems. The study investigates the proper location of the municipal landfill using multi-criteria ANP and entropy. Accordingly, four main criteria were defined for analyzing two methods for an appropriate place in the GIS environment. These four main criteria were taken into account with 15 modeling sub-criteria. Finally, the entropy method identified five suitable locations using the ANP method, and four appropriate sites were determined. The distribution of the selected sites by the entropy and ANP methods showed that the ANP method is more distant than the entropy method, and the two sites, A4 and A5 positions are more distant than the other aquatic sites. To evaluate the identified sites, the vulnerability of groundwater resources downstream of identified sites and the rate of leachate movement from these sites were considered. Based on the results of the DRASTIC Vulnerability Index and MODPATH, a particle-tracking Model, it was found that the northeast part of the city has a longer affected area due to the higher slope and higher permeability than the selected locations in the northwest. Accordingly, the area affected by the A3 site is also the only place where leachate effects enter the aquifer within three years due to its proximity.

The application of simulation-optimization models is a valuable tool for selecting the appropriate cropping pattern. The main objective of this research is to develop a two-objective simulation-optimization model to determine the pattern of cultivation and water allocation. The model performs the optimization with the multi-objective metamorphic algorithm (MOALO) after simulating different states of the cultivation pattern. The decision variables including land and water allocated to ten-day periods of plant growth were designed in a way that the minimum utilization of water resources and economic maximization were identified as target functions. The developed model was used to simulate and optimize the cultivation pattern with an area of ​​5500 hectares and water allocation of Semnan plain with renewable water at the rate of 60.8 million cubic meters. Harvesting scenarios of 80 (GW80) and 100 (GW100) percent of renewable groundwater and scenarios of change in existing cropping pattern of 30 (AC30) and 60 (AC60) percent were considered and each scenario was simulated with the MOALO algorithm. Optimization using the proposed model in four scenarios improved the water and economic objective functions compared to the initial simulation performance. The results showed that the four proposed scenarios were obtained by minimizing the water objective function and maximizing the economic objective function relative to the current situation (simulation). In general, the proposed model had a good performance despite its simplicity, which is a specialized tool to optimize the crop pattern with water allocation.

Despite its importance, pyrazinamide (PZA) is a blind spot in drug susceptibility testing in tuberculosis laboratories. The aim of this study was to set up a reliable agar-based proportion method f...

With the use of technology at water treatment plants (WTPs), it is possible to reduce the uncertainty between the supply and demand of drinking water. In this study, we propose a method for reducing effluent production at water treatment plants using effluent treatment. The effluent resulting from water treatment plants is treated with polyelectrolyte's, and a considerable amount of effluent is reused after sedimentation has taken place. As a result of changing the effluent treatment process at water treatment plants, as well as a shortage of groundwater, the aquifer balance and replacement approach was analyzed. Additionally, a hybrid ANN-WOA model was used to demonstrate that effluent treatment changes at WPTs have positive effects on groundwater resources. Therefore, three input variables were defined as groundwater resources level, aquifer recharge, and aquifer discharge in the hybrid model. In ten years, they were simulated. The model considered the water savings gained by changing the treatment process, and groundwater level changes were based on the desirability index. As a result of considering water thrift, the groundwater level increased by 23% on average. The multiple-criteria decision-making (MCDM) approach was employed due to the importance of increased effluent in water treatment plants. The results of the study found that the priority was to allocate water to industries, followed by a green space in the immediate vicinity of the plant. As a result of the study, novel technologies in effluent treatment at water treatment plants could effectively reduce the exploitation of groundwater resources and the aquifer balance. Water thrift was analyzed with respect to the aquifer balance and replacement approach as a result of altered effluent treatment processes at water treatment plants and a shortage of groundwater. Moreover, the effluent treatment change at water treatment plants was made to have positive effects on groundwater resources using a hybrid ANN-WOA model. Hence, in the hybrid model, groundwater resources level, aquifer recharge, and aquifer discharge were defined as input variables. The model considered the water savings gained by changing the treatment process, and groundwater level changes were based on the desirability index. According to the results, the groundwater level increased by 23% on average when the water thrift was taken into account. On average, groundwater levels increased by 23% when water thrift was considered. This figure can be effective in the groundwater balance. Moreover, the multiple-criteria decision-making (MCDM) approach was employed due to the importance of increased effluent in water treatment plants. Additionally, the results showed that new technologies for effluent treatment at water treatment plants could reduce the exploitation of groundwater resources and maintain aquifer balance.

The production of $\Sigma^0$ hyperons in proton proton collisions at a beam kinetic energy of 3.5 GeV impinging on a liquid hydrogen target was investigated using data collected with the HADES setup. The total production cross section is found to be $\mathrm{\sigma (pK^{+}\Sigma^{0}) [\mu b] = 17.7 \pm 1.7 (stat) \pm 1.6 (syst)}$. Differential cross section distributions of the exclusive channel $\mathrm{pp \rightarrow pK^{+}\Sigma^{0}}$ were analyzed in the center-of-mass, Gottfried-Jackson and helicity reference frames for the first time at the excess energy of 556 MeV. The data support the interplay between pion and kaon exchange mechanisms and clearly demonstrate the contribution of interfering nucleon resonances decaying to $\mathrm{K^{+}\Sigma^{0}}$. The Bonn-Gatchina partial wave analysis was employed to analyse the data. Due to the limited statistics, it was not possible to obtain an unambiguous determination of the relative contribution of intermediate nucleon resonances to the final state. However nucleon resonances with masses around 1.710 $\mathrm{GeV/c^{2}}$ ($\mathrm{N^{*}(1710)}$) and 1.900 $\mathrm{GeV/c^{2}}$ ($\mathrm{N^{*}(1900)}$ or $\mathrm{\Delta^{*}(1900)}$) are preferred by the fit.

The production of $Σ^0$ hyperons in proton proton collisions at a beam kinetic energy of 3.5 GeV impinging on a liquid hydrogen target was investigated using data collected with the HADES setup. The total production cross section is found to be $\mathrm{σ(pK^{+}Σ^{0}) [μb] = 17.7 \pm 1.7 (stat) \pm 1.6 (syst)}$. Differential cross section distributions of the exclusive channel $\mathrm{pp \rightarrow pK^{+}Σ^{0}}$ were analyzed in the center-of-mass, Gottfried-Jackson and helicity reference frames for the first time at the excess energy of 556 MeV. The data support the interplay between pion and kaon exchange mechanisms and clearly demonstrate the contribution of interfering nucleon resonances decaying to $\mathrm{K^{+}Σ^{0}}$. The Bonn-Gatchina partial wave analysis was employed to analyse the data. Due to the limited statistics, it was not possible to obtain an unambiguous determination of the relative contribution of intermediate nucleon resonances to the final state. However nucleon resonances with masses around 1.710 $\mathrm{GeV/c^{2}}$ ($\mathrm{N^{*}(1710)}$) and 1.900 $\mathrm{GeV/c^{2}}$ ($\mathrm{N^{*}(1900)}$ or $\mathrm{Δ^{*}(1900)}$) are preferred by the fit.

Hadron production ($\pi^\pm$, proton, $\Lambda$, $K_S^0$, $K^\pm$) in $\pi^- + \mathrm{C}$ and $\pi^- + \mathrm{W}$ collisions is investigated at an incident pion beam momentum of $1.7~\mathrm{GeV}/c$. This comprehensive set of data measured with HADES at SIS18/GSI significantly extends the existing world data on hadron production in pion induced reactions and provides a new reference for models that are commonly used for the interpretation of heavy-ion collisions. The measured inclusive differential production cross-sections are compared with state-of-the-art transport model (GiBUU, SMASH) calculations. The (semi-) exclusive channel $\pi^- + A \rightarrow \Lambda + K_S^0 +X$, in which the kinematics of the strange hadrons are correlated, is also investigated and compared to a model calculation. Agreement and remaining tensions between data and the current version of the considered transport models are discussed.

The double differential production cross sections, $d^2\sigma/d\Omega dE$, for hydrogen isotopes and charged pions in the reaction of p + Nb at 3.5 GeV proton beam energy have been measured by the High Acceptance DiElectron Spectrometer (HADES). Thanks to the high acceptance of HADES at forward emission angles and usage of its magnetic field, the measured energy range of hydrogen isotopes could be significantly extended in comparison to the relatively scarce experimental data available in the literature. The data provide information about the development of the intranuclear cascade in the proton-nucleus collisions. They can as well be utilized to study the rate of energy/momentum dissipation in the nuclear systems and the mechanism of elementary and composite particle production in excited nuclear matter at normal density. Data of this type are important also for technological and medical applications. Our results are compared to models developed to describe the processes relevant to nuclear spallation (INCL++) or oriented to probe either the elementary hadronic processes in nuclear matter or the behavior of compressed nuclear matter (GiBUU).

The global polarization of {\Lambda} hyperons along the total orbital angular momentum of a relativistic heavy-ion collision is presented based on the high statistics data samples collected in Au+Au collisions at \sqrt{s_{NN}} = 2.4 GeV and Ag+Ag at 2.55 GeV with the High-Acceptance Di-Electron Spectrometer (HADES) at GSI, Darmstadt. This is the first measurement below the strangeness production threshold in nucleon-nucleon collisions. Results are reported as a function of the collision centrality as well as a function of the hyperon transverse momentum (p_T) and rapidity (y_{CM}) for the range of centrality 0--40%. We observe a strong centrality dependence of the polarization with an increasing signal towards peripheral collisions. For mid-central (20--40%) collisions the polarization magnitudes are (%) = 6.8 \pm 1.3 (stat.) \pm 2.1 (syst.) for Au+Au and (%) = 6.2 \pm 0.4 (stat.) \pm 0.6 (syst.) for Ag+Ag, which are the largest values observed so far. This observation thus provides a continuation of the increasing trend previously observed by STAR and contrasts expectations from recent theoretical calculations predicting a maximum in the region of collision energies about 3 GeV. The observed polarization is of a similar magnitude as predicted by 3D fluid dynamics and the UrQMD plus thermal vorticity model and significantly above results from the AMPT model., Comment: 8 pages, 4 figures

IntroductionThe appropriate use of antibiotics is an important strategy in slowing the development of antimicrobial resistance. This study aimed to evaluate antibiotic consumption and antibiotic use during the coronavirus disease 2019 (COVID-19) pre-pandemic period and pandemic period.Material and methodsAntibiotic consumption was evaluated with the antibiotic consumption index (ACI).ResultsAntibiotics with the largest increase in ACI value during the pandemic period compared to the previous year increased from 0.4 to 1.8 DDI/100 bed days in moxifloxacin. Teicoplanin, linezolid, and clindamycin were not affected in terms of consumption.ConclusionsIt was observed that the use of many intravenous antibiotics in our hospital increased during the pandemic period.

Evaporation is one of the key factors in the hydrological cycle, and it is one of the most critical parameters in hydrological, agricultural, and meteorological studies, especially in arid and semi-arid regions. By estimating evaporation, it is possible to make a significant contribution to studies related to water balance, management and design of irrigation systems, estimation of crop amount, and management of water resources. In this regard, in the present study, using artificial neural network (ANN) and its hybrid algorithms including Harris Hawks Optimization (HHO), Whale Optimization Algorithm (WOA), and Particle Swarm Optimization (PSO), the daily evaporation value from the reservoir of Qaleh Chay Ajab Shir dam was estimated. For this purpose, the effective parameters in the evaporation process were introduced to each of the models in the form of different input patterns, and the evaporation value from the reservoir was also considered as output parameter. The results showed that the best selected model for ANN is the P3 model including three parameters of minimum air temperature, and daily evaporation data with NASH of 0.89, RMSE of 1.5 mm/day, and MAE of 1.1 mm/day, which was optimized by applying hybrid algorithms to train the neural network. The results disclosed that all three models had a good performance in estimating the daily evaporation value, so that the value of the correlation coefficient for all three models is in the range of 0.95–0.99. Based on evaluation criteria, ANN–HHO has better performance than the two other algorithms in estimating daily evaporation value. The values of NASH, RMSE and MAE for the selected pattern of the test data are 0.943, 0.908 and 0.736 mm/day, respectively. For better analysis, Taylor diagram is used (RMSD = 0.98, CC = 0.97, STD = 4 for ANN–HHO). The results of this diagram also showed that the ANN–HHO model provides acceptable performance when compared with other models. Considering the promising results of the models in predicting the daily evaporation from dam, it is suggested to use the existing approach for landscaping the groundwater balance and design of irrigation systems.

This study aimed to investigate the association between serum levels and polymorphic variants of IL-35 with susceptibility, clinical features, and disease severity in multiple sclerosis (MS) patients. This case–control study recruited 186 MS patients and 195 sex- and age-matched healthy controls. Serum levels and polymorphic variants of IL-35 were determined by ELISA and restriction fragment length polymorphism (RFLP)-PCR or high resolution melting (HRM) analysis methods, respectively. In addition, by in silico analysis, we evaluated the location and function of the polymorphism. Serum levels of IL-35 were significantly lower in the patients than those of healthy controls (49.3 ± 3.7 vs. 69.5 ± 7.8, p = 0.009). EBI3 rs4740 polymorphism of IL-35 was associated with 2.2-fold increased risk of MS susceptibility (95% CI, 1.3–3.9, p = 0.005). However, there were no differences in the genotype distribution and allele frequencies of IL-35 rs568408 between the patients and controls (p > 0.05). In silico results showed that variation in IL-12A and EBI3 may affect on protein pathways of the cells and different components of the immune system such as NF-κB and INF-γ. The results show that IL-35 polymorphisms might be a genetic risk factor for the development of MS.

Groundwater quality management is challenging due to the fate and transport of multiple pollutants in the porous media, extensive polluters, and late aquifer responses to pollution reduction practices. Water quality trading (WQT) is a regionally incentive-based strategy for self monitoring and groundwater quality improvement. This study evaluates the effectiveness of 12 waste load allocation (WLA) scenarios on groundwater nitrate and chloride abatement, simultaneously using MODFLOW and MT3D. The theoretical efficiencies of multi-pollutant WQT are also testified out of these WLA policies by considering environmental, economic and practical conditions. For these purposes, Varamin plain, south eastern Tehran, Iran was chosen as the study area where both point and non-point emission sources were considered in WQT. At first, an allowable groundwater quality limit (AQL) was set for pollutants regarding groundwater impairment and simulation outcomes. The AQL violations of WLAs were then calculated in addition to their marginal abatement costs and penalties. Here, nitrate abatement ranges between 3.3–15.3% while chloride abatement ranges between 4.5–23.6%. However, 5 WLA scenarios could pass the conditions of not violating any AQLs, and gaining remarkable benefits (> 25%) for all market attendants. Potential WQT strategies are finally prioritized regarding their viability and marginal costs. According to these conditions, trading discharge permits between WWTPs with 25% nitrate removal (sellers) and current farmers (buyers) is recommended as the optimal WQT alternative which imposes no penalties or land-use changes. Here, the overall benefits of sellers and buyers exceed 42% and 85%, respectively in comparison with not attending at any WLA scenario.

Further improvement of quality and productivity are some of the most relevant laser cutting process challenges. One way of affecting the process performance is manipulating the laser beam intensity distribution. Within this work, the feasibility of enhancing the cutting speed and edge quality using dynamic beam shaping in 4 kW fiber laser cutting of 15 mm stainless steel is investigated. Moreover, in order to evaluate the effect of dynamic beam shaping parameters on the process zone, a simplified thermal simulation model is introduced. As a result, the effect of longitudinal beam oscillation on the cutting efficiency is studied experimentally and explained using numerical calculation. The obtained results have shown a significant improvement for laser fusion cutting compared with a static top-hat intensity distribution. In particular, the cutting speed can be increased up to 45 % with considerably better quality. Finally, further steps to optimize the dynamic beam shaping technology for laser cutting applications are proposed. ispartof: pages:740-745 ispartof: Procedia CIRP vol:111 pages:740-745 ispartof: 12th CIRP Conference on Photonic Technologies [LANE 2022] location:Fürth, Germany date:4 Sep - 8 Sep 2022 status: Published online

In a terminating band, the nucleon number changes in a specific orbital not only lead to deformation changes of the band but also the type of the band termination is impressed. In this work, we consider the role of the orbitals near the Fermi surface in some of the nuclei with [Formula: see text]; such as Dy ([Formula: see text]), Ho ([Formula: see text]) and Er ([Formula: see text]) isotopes. Our results show that the contribution of the number of the proton holes in the core is very effective to energy cost at the end of the rotational bands and then, termination type. Change the number of the protons on high-[Formula: see text] orbitals ([Formula: see text]) in [Formula: see text] isotones and also, the neutrons on high-[Formula: see text] [Formula: see text] and low-[Formula: see text] [Formula: see text] neutron orbitals do not affect in the type of termination. They cause only to move up or down the terminating bands in energy.

Aim: To investigate the prevalence and drug-resistance M. tuberculosis isolated from HIV seropositive individuals in Tehran, Iran. Background: Human immunodeficiency virus (HIV) is one of the most important risk factors for developing active tuberculosis (TB). Objective: To determine the rate of transmission and drug resistant M. tuberculosis (MTB) strains isolated from HIV seropositive patients in Tehran province, Iran. Methods: This study consecutively enrolled 217 TB/HIV coinfected patients from April 2018 to August 2019 at Emam Khomeini referral hospital and 5 other health centers in Tehran province. The isolates were genotyped using 15 loci Mycobacterial interspersed repetitive unit-variable number tandem repeats (MIRU-VNTR). Minimum inhibitory concentration (MIC) was determined for 6 drugs. In addition, mutations were assessed in rpoB, katG, inhA, and ahpC genes using Reverse Blot Hybridization Assay System. Results: A 20 (9.2%) patients were culture-positive for M. tuberculosis and typed by MIRU-VNTR, 13 (65%) strains formed 5 clusters, but 6 (30%) isolates had a unique pattern. The total Hunter– Gaston discrimination index (HGDI) for all 15 loci was 0.846, and the cluster size was 2 to 4 patients. The estimated proportion of recent transmission was 45%. The mutation was identified in 1 isolate, lost inhAW1 and mutation in MT1 loci, which was resistant to isoniazid (INH). Moreover, 1 (5%) and 3 (15%) isolates were resistant to INH and ethambutol (EMB), respectively, of which 1 was resistant to INH and EMB. Conclusion: The transmission rate of TB in HIV patients was relatively high; however, the prevalence of drug-resistant strains and TB infection in females was insignificant in this study (p

In this study, a new 3-stage approach that consists of clustering, simulation, and optimization stages is proposed for the simulation of groundwater level (GWL) in an arid region of eastern Iran. In the first stage, K-means clustering was used to divide the study aquifer into five different clusters based on precipitation, water recharge, water discharge, transmissivity, earth level, and water table. In the second stage, to simulate GWL in each cluster, several input variables, such as water level at the previous month, aquifer discharge, aquifer recharge, evaporation, temperature, and precipitation, were used in the form of various input patterns that were fed to an artificial neural network (ANN). Finally, in the third stage, two advanced optimization methods, i.e., particle swarm optimization (PSO) and whale optimization algorithm (WOA), were utilized to optimize the ANN results. Various patterns were identified as suitable clusters based on the studied models. A pattern including water level at the previous month, aquifer discharge, aquifer recharge, and precipitation was identified as the best model for four clusters, except for cluster 3. The validation with root mean squared error (RMSE), mean absolute percentage error (MAPE), and Nash Sutcliffe index (NSE) revealed RMSE = 0.01, NSE = 0.97, and MAPE = 0.13 for the first cluster, RMSE = 0.011, NSE = 0.99, and MAPE = 0.22 for the second cluster, RMSE = 0.003, NSE = 0.99, and MAPE = 0.30 for the fourth cluster, and RMSE = 0.001, NSE = 0.98, and MAPE = 0.05 for the fifth cluster. For the third cluster, a pattern including water level at the previous month, aquifer discharge, and aquifer recharge was identified as the best model resulting in RMSE = 0.006, NSE = 0.99, and MAPE = 0.05. Finally, according to the results, the ANN–PSO model was applied to three clusters, while the ANN–WOA model was applied to the remaining clusters. In general, this study showed that optimization algorithms can improve the simulation accuracy of ANN, and the efficient use of each method depends on the clustering type. The application of the approach proposed here can be extended to other aquifers that have a relatively large area and limited data availability.