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Background: The use of online psychological services has shown potential in alleviating mental health concerns during the coronavirus epidemic. This study aimed to investigate the effects of online psychological services on COVID-19 fear and academic achievement among students with addicted parents. Methods: The current study is a quasi-experimental study with pretest, posttest, and control group. The statistical population of this study included all male and female students in Tehran province in 2022. In order to select the sample, the call to participate in the study was made by the social media (Telegram, WhatsApp, Instagram, LinkedIn) for two months. Then, corona fear questionnaire link was sent to the email addresses of the respondents and 120 students who met the inclusion criteria were selected as the sample of the study. In the next stage, 120 students were randomly assigned in the experimental and control groups. After 8 online sessions, 4 students from the experimental group and 5 students from the control group ended their cooperation due to personal reasons and as a result, 56 and 55 students constituted the experimental and control groups, respectively. Results: The results indicated a significant increase in academic achievement for students in the experimental group post-intervention compared to the control group. Additionally, online psychological services appeared to mitigate COVID-19 related fears. Conclusion: This study suggests that online psychological services play a pivotal role in enhancing student's mental well-being during the COVID-19 epidemic.

Abstract Objective The high rate of treatment failure is a common problem in the treatment of methamphetamine use. Therefore, the aim of this research is to identify the most common causes of relapse in methamphetamine users. Method This is a qualitative study and of content analysis type. Information was collected using purposeful sampling and through semi-structured interviews and focus group discussions. The statistical population consisted of all people with the methamphetamine-use disorder in 2022 who were in the abstinence phase and participated in the meetings of the Narcotics Anonymous (NA) Center of Bojnord. Theoretical sampling continued until data saturation. A total of 10 one-on-one interviews were conducted, each lasting between 45 to 80 min. Additionally, two focus group interviews were conducted with six members in each group, lasting between 95 to 110 min and data saturation was achieved through these interviews. Data analysis was done using the content analysis method (Sterling). Recoding and Holsti's method were used to measure reliability; validity was then calculated through content validity assessment. Findings The results of the thematic analysis showed that laps and relapse factors were identified and categorized into 5 organizing themes, including negative emotional states, positive emotional states, negative physical states, interpersonal factors, and environmental factors, consisting of 39 basic themes. Result Identifying the risk factors leading to laps and relapse in methamphetamine users and increasing the knowledge in this field can lay the groundwork for preventive therapeutic interventions in this community.

Cancer remains one of the main causes of death in the world due to its increasing incidence and treatment difficulties. Although significant progress has been made in this field, innovative approaches are needed to reduce tumor incidence, progression, and spread. In particular, the development of cancer vaccines is currently ongoing as both a preventive and therapeutic strategy. This concept is not new, but few vaccines have been approved in oncology. Antigen-based vaccination emerges as a promising strategy, leveraging specific tumor antigens to activate the immune system response. However, challenges persist in finding suitable delivery systems and antigen preparation methods. Exosomes (EXs) are highly heterogeneous bilayer vesicles that carry several molecule types in the extracellular space. The peculiarity is that they may be released from different cells and may be able to induce direct or indirect stimulation of the immune system. In particular, EX-based vaccines may cause an anti-tumor immune attack or produce memory cells recognizing cancer antigens and inhibiting disease development. This review delves into EX composition, biogenesis, and immune-modulating properties, exploring their role as a tool for prevention and therapy in solid tumors. Finally, we describe future research directions to optimize vaccine efficacy and realize the full potential of EX-based cancer immunotherapy.

Wastewaters containing heavy metals produced by industries has detrimental effects on the environment. One of the effective methods for removal of heavy metals is the use of adsorption method by nanoparticles. The aim of this study was to remove zinc and nickel elements from effluents of Tarom industrial Town of Zanjan using modified multi-walled carbon nanotubes. In this descriptive-analytical study, effect of effective parameters such as contact time, adsorbent content, pH, temperature and concentration of metal ions on the removal efficiency of metals from Ni(II) and Zn(II) from wastewater and isotherm, kinetics and thermodynamic models of adsorption process was investigated. SEM and FTIR spectrums were taken to prove nanotubes and to determine adsorbent factor groups before and after preparation, respectively. The results of study showed that the absorption of Zn and Ni metals is highly dependent on pH. Study results showed that by increasing the pH of effluent up to the range of 8, and 7 for Ni(II) and Zn(II) metals, respectively, the removal percentage of metal ions increased and then decreased. By increasing in the adsorbent amount and contact time, the removal percentage of metal ions increased and by increasing the reaction temperature and concentration of metal ions in the effluent, the removal percentage of metal ions decreased. So that, the highest removal percentage of Ni(II) and Zn(II) ions was obtained in adsorbent value of 2 mg/L, contact time of 120 min, concentration of 100 mg/L and temperature of 15 °C. The results also showed that the adsorption of Ni(II) and Zn(II) metals from effluent follows Langmir isotherm absorption model and the adsorption kinetics is adapted to the second-order pseudo-reaction (R2>0.98), this mechanism is controlled by adsorption. Also, based on the obtained results, with increasing temperature, the free energy of Gibbs system standard decreased, which indicates the adsorption process is done spontaneously. The maximum adsorption capacity of nickel and zinc metals was 43 and 54 mg/g, respectively. According to the results, it is concluded that modified multi-walled carbon nanotubes have good ability to remove nickel and zinc from effluents and can be used in wastewater treatment containing heavy metals.

Background and aims: Over the last six months, the use of technology and the internet in Iran is significantly increased due to the coronavirus pandemic. This study aimed to investigate the effect of online career counseling on students’ psychological capital (i.e., self-efficacy, resilience, optimism, and hope) during corona isolation. Methods: The research design was quasi-experimental. The statistical population of this study included all students who were members of social media (i.e., WhatsApp, Telegram, Facebook, and LinkedIn). After the announcement and completion coronavirus anxiety questionnaire, 30 students who had obtained scores higher than the average level were selected and randomly assigned into experimental (15 students) and control (15 students) groups. Results: The findings showed that after the online counseling course, the intervention group outperformed the control group in psychological capital components (i.e., self-efficacy, resilience, optimism, and hope). Conclusion: According to the findings of this study, online counseling can be an effective source for career counselors, especially in developing countries. Besides face-to-face counseling, its services can help students increase their psychological capital.

In this study, Ti3C2Tx MXene nanosheets were synthesized and loaded into UV-curable acrylate polyvinyl alcohol (APVA) to fabricate a novel APVA-MXene mixed matrix membrane (MMM) for ethanol dehydration by pervaporation (PV) process. UV-curable APVA was synthesized by substituting the hydroxyl groups of PVA with the methacryloyl groups of glycidyl methacrylate (GMA). A rapid and energy-efficient method for fabricating the active layer was achieved by UV-crosslinking of APVA over a 2-min period. The morphology, crystal structure, chemical composition, and thermo-mechanical properties of the membranes were investigated by FESEM, XRD, FTIR, TGA, and static mechanical stretching. Incorporating MXene nanosheets into the APVA matrix resulted in an increase in permeation flux and separation factor for APVA-MXene MMMs due to its laminated structure with interlayer transport channels of two dimensions, excellent compatibility with the polymer matrix, and high surface hydrophilicity. When the MXene loading reached 3 wt%, the optimal separation performance was achieved with a permeation flux of 942 g/(m2.h) (increased by 106% compared to pristine APVA membranes) and a separation factor of 294 (increased by 79% compared to pristine APVA membranes).

Surface modification of ultrafiltration membranes has shown a significant potential to reduce fouling and increase flux and lifetime, which are the most important factors in membrane filtration. In this study, the surface-modified membranes were prepared by grafting hyperbranched polyethyleneimine (HBPEI) onto polyvinylidene fluoride (PVDF)-sulfonated polyethersulphone (SPES) blending membranes. Electrostatic interactions between HBPEI and SPES result in a well-attached positive-charged HBPEI grafting layer on the PVDF membrane surface. Surface-modified membranes were examined for the removal of cationic E-coat paint and their performance was measured in terms of total permeation flux, paint rejection, and fouling resistance parameters. In addition, the physicochemical properties and morphology of the membranes were examined by field emission scanning electron microscopy (FESEM), Fourier-transformed infrared spectroscopy (FTIR), atomic force microscopy (AFM), and water contact angle (CA). The optimum membrane shows a total permeation flux of 35.5 L per square meter per hour (LMH) and paint rejection of 99.9%. Additionally, the fouling parameter of the optimized membrane shows a flux recovery ratio of 90%. As a result of its considerable properties, such as the high flux and separation performance as well as its antifouling properties, the surface modified membrane is an excellent candidate for the removal of E-coat paint at industrial scale.

Background: The association between gender and time of receiving services (TRS) after traumatic injuries is rarely documented in developing countries. This study aimed to examine gender differences in time between occurring injuries and receiving services in hospital after trauma injuries in northern Iran. Materials and Methods: A total of 7085 injured patients were included in this study. Data on sociodemographic and clinical characteristics were extracted from the Guilan province trauma system registry (GTSR) from July 2017 to July 2018. The Oaxaca–Blinder (OB) method was used to explain the gender differences in the TRS after traumatic injuries. Results: There were significant differences between men and women in marital statues (P < 0.001), education level (P < 0.001), time of injury (P = 0.025), occupation (P < 0.001), type of trauma (P < 0.001), mode of transfer (P < 0.001), mean age (P < 0.001), average distance from hospital (P = 0.052), and average transfer time to the hospital (P < 0.001). We found gender differences in TRS after falling trauma (P = 0.006) when the transfer was performed by emergency medical services (EMSs) and in penetrating trauma (P < 0.001) when the transfer was performed by private vehicles. The difference in the observed characteristics of men and women explained 67% of gender differences in TRS (P = 0.06). Conclusion: The gender difference in the transfer of injured patients was in favor of men, depending on the socio-demographic and clinical factors. In OB analysis, the gender differences in falling trauma and transfer by EMS and the gender differences in penetrating trauma and private transmission to the hospital were also confirmed. Steps need to be taken to ensure that services are equally beneficial to both men and women.

The Aircraft Cargos Heavy C-130 in the Army Air Force Organization of the Islamic Republic of Iran, As one of the most effective support battle aircraft in the world (especially during the Holy Defense years), has played a significant role in the missions provided to this force. The present research is related to an Electronic Warfare Airborne to Standoff Jamming mission, And its main purpose:" The Feasibility Study of Using the C-130 Aircraft to Standoff Jamming the Mission Electronic Warfare Airborne." Is considered; And The main question raised in this research is:"Is it possible to use the C-130 to Aircraft to Standoff Jamming an electronic warfare Airborne mission?" In this research, a population of about 120 people was selected using the Cochran formula in a sample population of 48 people. Also, for gathering information, tools such as interviews, questionnaires and study documents have been used, Also, the validity of questionnaires Visited by prominent scholars And reliability of questionnaires Using Cronbach's alpha coefficient is 0.824. Eventually, Findings with a mixed approach Using descriptive and inferential statistics, Has been analyzed And the results are: " Due to Airborne threats And new technological approaches to weapons And smart guidance systems, The need to pay attention to Electronic Warfare Airborne With all its components and indicators; That is, electronic support, Electronic attack And tactical electronic protection of the aircraft Is applicable And applying it To strengthen and Development of martial power As air force operational And other parts of the AJA, Is serious.

The use of ionic liquids (ILs) for biomass pretreatment to produce cellulose-rich materials (CRMs) has been well proven. In this research, due to the wide range of applications and ease of using artificial intelligence procedures, on the basis of the algorithm of stochastic gradient boosting (SGB) decision tree, an artificial intelligence approach is proposed to estimate the properties of cellulose-rich materials (CRMs). That being the case, the dataset of the empirical output values was gathered and was randomly broken down into datasets for testing and training. These results show that the best forecasting tool for calculating the properties of CRMs is the developed model. Furthermore, the accuracy of the databank of the biodiesel target values has been examined. In contrast, the influences of model contributed variables on the output have been examined as a new issue. It reveals that the most influencing variable in determining the properties of CRMs is the cellulose enrichment factor. Therefore, this research provides an innovative and accurate tool for predicting the properties of CRMs and sensitivity investigation on effective parameters to help investigators developing the optimized process.

Nowadays, the high consumption of fossil fuels has caused many pollutants and environmental problems. Biodiesel has recently been considered as a clean and renewable alternative to fossil fuels. They are found in some molecular structures including fatty acid ethyl esters (FAEEs) and also fatty methyl esters (FAMEs), having various thermophysical characteristics. Thus, it appears essential to select the suitable methods for a particular diesel engine to estimate the ester characteristics. The current research sets out to develop a new and robust method predicting isothermal compressibility of long-chain fatty acid methyl and ethyl esters directly from several basic efficient parameters (pressure, temperature, normal melting point, and molecular weight). Therefore, as a novel and prevailing mathematical method in this field, an extreme learning machine was implemented for isothermal compressibility on the massive dataset. According to statistical evaluations, this novel established model had high accuracy and applicability (R2 = 1 and RMSE = 0.0018714) which is more accurate than previous models presented by former researchers. Among various factors of the sensitivity analysis, temperature and pressure had the greatest effect on the output values, so that the output parameter has a direct relationship with temperature and an inverse relationship with pressure with relevancy factors of 22.44% and −79.81%.

Water saturation determination in core laboratory is known as a cost and time consuming labor. Hitherto, many scientists attempted to estimate accurately water saturation from well-logging data which has a continuous record without losing information. Therefore, various model were introduced to relate reservoir properties and water saturation. Since carbonate reservoir is very heterogeneous in shape and size of pore throat, the relation between water saturation and other carbonates reservoir properties is very complex, and causes considerable overall errors in water saturation calculation. By increasing the usage and improvement of soft computing methods in engineering problems, petroleum engineers have been attended them to measure the petrophysical properties of the reservoir. In this study, a radial basis function neural network (RBFNN) improved by genetic algorithm has been employed to estimate formation water saturation by using conventional well-logging data. The used logging and core data have been gathered from a carbonated formation from one of oilfield located in south-west Iran, and finally their results of the proposed model were compared with the core analysis results. By checking the testing data from another well, it showed this method had a 0.027 for mean square errors and its correlation coefficient is equal to 0.870. These results implied on high accuracy of this model for oil saturation degree estimation. While the common methods like Archie, had a 0.041 mean square error and 0.720 of the correlation coefficient, which indicate a high ability of RBF model than the other usual empirical methods.

In recent years, the intrinsic magnetic properties of magnetic nanoparticles (MNPs) have made them one of the most promising candidates for magnetic resonance imaging (MRI). This study aims to evaluate the effect of different coating agents (with and without targeting agents) on the magnetic property of MNPs. In detail, iron oxide nanoparticles (IONPs) were prepared by the polyol method. The nanoparticles were then divided into two groups, one of which was coated with silica (SiO2) and hyperbranched polyglycerol (HPG) (SPION@SiO2@HPG); the other was covered by HPG alone (SPION@HPG). In the following section, folic acid (FA), as a targeting agent, was attached on the surface of nanoparticles. Physicochemical properties of nanostructures were characterized using Fourier transform infrared spectroscopy (FT-IR), transmission electron microscopy (TEM), and a vibrating sample magnetometer (VSM). TEM results showed that SPION@HPG was monodispersed with the average size of about 20 nm, while SPION@SiO2@HPG had a size of about 25 nm. Moreover, HPG coated nanoparticles had much lower magnetic saturation than the silica coated ones. The MR signal intensity of the nanostructures showed a relation between increasing the nanoparticle concentrations inside the MCF-7 cells and decreasing the signal related to the T2 relaxation time. The comparison of coating showed that SPION@SiO2@HPG (with/without a targeting agent) had significantly higher r2 value in comparison to Fe3O4@HPG. Based on the results of this study, the Fe3O4@SiO2@HPG-FA nanoparticles have shown the best magnetic properties, and can be considered promising contrast agents for magnetic resonance imaging applications.

Background: attachment styles are some sustainable patterns of connections which influence the persons' behaviors throughout the life, since childhood, and play important rule in individual growing and job creation. Purpose: the purpose of this paper is to study Prediction of job search efficacy and career decision-making self-efficacy based on attachment styles. Method: this research is descriptive type of correlation . Population of this study includes all studentsthat studying in Isfahan University ,during 92/93 academic year ,which selected by Simple Random Sampling method from a sample with 180 person. Data was collected from Attachment Styles ( Hazen& Shiver. 1987), job search efficacy (Salehi.2005) and career decision-making self-efficacy (Bets .1996) questionnaires and has been analyzed by SPSS. Findings: The research data determined that ambivalent and safe attachment style could predict 49 % of career decision-making self-efficacy and 37 % of job search efficacy. Results: we can deduce from current study that attachment styles has an important role in predicted of of job search efficacy and career decision-making self-efficacy career adaptability as well as explaining the career adaptability aspect, that should be attention.

Cementation factor is a critical parameter, which affects water saturation calculation. In carbonate rocks, due to the sensitivity of this parameter to pore type, water saturation estimation has associated with high inaccuracy. Hence developing a reliable mathematical strategy to determine these properties accurately is of crucial importance. To this end, genetic algorithm pattern search is employed to find accurate cementation factor by using formation resistivity factor and the porosity obtained from laboratory core analyses with considering the assumption that tortuosity factor is not unity. Subsequently, particle swarm optimization (PSO) fuzzy inference system (FIS) was used for the classification of cementation factor according to the predominated rock pore type by using the input variables such as cementation factor, porosity, and permeability to classify the core samples in three groups, namely fractured, interparticle, and vuggy pore system. Then, the experimental data which was collected from Sarvak formation located in one of the Iran southwestern oil fields was applied to the proposed model. Next, for each class, a cementation factor-porosity correlation was created and the results were used to calculate cementation factor and water saturation profile for the studied well. The results showed that the constructed model could predict cementation factor with high accuracy. The comparison between the model presented herein and the conventional method demonstrated that the proposed model provided a more accurate result with a mean square error (MSE) of around 0.024 and led to an R2 value of 0.603 in calculating the water saturation.

By studying of present situation of universities in Iran, through research regarding students' lives, this article seeks to consider the features of students' professional identity. The professional identity is a social one, made, in relation with other individuals, through practical learning and instruction and professional experiments. For the students, the formally start of a social involvement, coincides with the start of their studies, and the formation of their professional identities will be intensified and reinforced through practical instructions concerning their fields. The method used in this study is qualitative research in the way of grounded theory method. To create the sample, the theoretical method is used and continued to reach saturation stage. The findings, hence, are collected applying the prevalence interview technique for 19 students and group interview for 15 students of University ofMazandaran. The research findings suggest that, the professional identities of the students have two features of scientific and personal identities. The students' scientific identity is formed by the students' tendencies and attitudes, and also their scientific actions and efforts. The personal identity is a perception that student builds up of himself as a scientific actor present at university environment. The development of a professional identity, in addition, is associated with the position of the individual within the community. Hence, the gender, socio-economic status, supports by family and friends, individual's social environment and networks influence on the formation of his professional identity.

Agricultural processing industries in rural areas could bring the benefits of efficiency of products, increased employment and reduced agricultural waste. However, the success of the packaging for processing industries in the developing rural economy depends on the choice of the best location for the establishment of related industries. The purpose of this study was to determine the optimal location of processing industries - depending on the direction of economic development in rural saffron packaging in the Torbat city. Information was collected in two ways from a library. The population of the study area was in the fields of Torbat city. 19 villages were selected as samples using Cochran formula, 356 households were defined as households in the sample. Then to locate the packaging processing industries for saffron use of index of localization of the human dimension was considered normal. The data collected for analysis was gathered by using questionnaires, and the AHP model and SPSS software package were used. In this regard, the results suggest that the correlation between processing industries - depending on the size of saffron and economic development in the rural fields is based on research. Thus, the best location for saffron processing industries in the region, the villages and Colonel Asad were identified considering the natural conditions and human factors (fertile soil, access roads, etc.).

Cancer remains one of the main causes of death in the world due to its increasing incidence and treatment difficulties. Although significant progress has been made in this field, innovative approaches are needed to reduce tumor incidence, progression, and spread. In particular, the development of cancer vaccines is currently ongoing as both a preventive and therapeutic strategy. This concept is not new, but few vaccines have been approved in oncology. Antigen-based vaccination emerges as a promising strategy, leveraging specific tumor antigens to activate the immune system response. However, challenges persist in finding suitable delivery systems and antigen preparation methods. Exosomes (EXs) are highly heterogeneous bilayer vesicles that carry several molecule types in the extracellular space. The peculiarity is that they may be released from different cells and may be able to induce direct or indirect stimulation of the immune system. In particular, EX-based vaccines may cause an anti-tumor immune attack or produce memory cells recognizing cancer antigens and inhibiting disease development. This review delves into EX composition, biogenesis, and immune-modulating properties, exploring their role as a tool for prevention and therapy in solid tumors. Finally, we describe future research directions to optimize vaccine efficacy and realize the full potential of EX-based cancer immunotherapy. [ABSTRACT FROM AUTHOR]

Automatic detection of intake gestures is a key element of automatic dietary monitoring. Several types of sensors, including inertial measurement units (IMU) and video cameras, have been used for this purpose. The common machine learning approaches make use of labeled sensor data to automatically learn how to make detections. One characteristic, especially for deep learning models, is the need for large datasets. To meet this need, we collected the Objectively Recognizing Eating Behavior and Associated Intake (OREBA) dataset. The OREBA dataset aims to provide comprehensive multi-sensor data recorded during the course of communal meals for researchers interested in intake gesture detection. Two scenarios are included, with 100 participants for a discrete dish and 102 participants for a shared dish, totalling 9069 intake gestures. Available sensor data consist of synchronized frontal video and IMU with accelerometer and gyroscope for both hands. We report the details of data collection and annotation, as well as details of sensor processing. The results of studies on IMU and video data involving deep learning models are reported to provide a baseline for future research. Specifically, the best baseline models achieve performances of F1=0.853 for the discrete dish using video and F1=0.852 for the shared dish using inertial data.

Wrist-worn inertial measurement units have emerged as a promising technology to passively capture dietary intake data. State-of-the-art approaches use deep neural networks to process the collected inertial data and detect characteristic hand movements associated with intake gestures. In order to clarify the effects of data preprocessing, sensor modalities, and sensor positions, we collected and labeled inertial data from wrist-worn accelerometers and gyroscopes on both hands of 100 participants in a semi-controlled setting. The method included data preprocessing and data segmentation, followed by a two-stage approach. In Stage 1, we estimated the probability of each inertial data frame being intake or non-intake, benchmarking different deep learning models and architectures. Based on the probabilities estimated in Stage 1, we detected the intake gestures in Stage 2 and calculated the F1 score for each model. Results indicate that top model performance was achieved by a CNN-LSTM with earliest sensor data fusion through a dedicated CNN layer and a target matching technique (F1 = .778). As for data preprocessing, results show that applying a consecutive combination of mirroring, removing gravity effect, and standardization was beneficial for model performance, while smoothing had adverse effects. We further investigate the effectiveness of using different combinations of sensor modalities (i.e., accelerometer and/or gyroscope) and sensor positions (i.e., dominant intake hand and/or non-dominant intake hand).

Objectives: This in vitro study is aimed at assessing whether implant primary stability is influenced by implant length in artificial bone with varying densities., Materials and Methods: A total of 120 truncated-conical implants (60 long-length: 3p L, 3.8 × 14 mm; 60 short-length: 3p S, 3.8 × 8 mm) were inserted into 20, 30, and 40 pounds per cubic foot (PCF) density polyurethane blocks. The insertion torque (IT), removal torque (RT), and resonance frequency analysis (RFA) values were recorded for each experimental condition., Results: In 30 and 40 PCF blocks, 3p S implants exhibited significantly higher IT values (90 and 80 Ncm, respectively) than 3p L (85 and 50 Ncm, respectively). Similarly, RT was significantly higher for 3p S implants in 30 and 40 PCF blocks (57 and 90 Ncm, respectively). However, there were no significant differences in RFA values, except for the 20 PCF block, where 3pS implants showed significantly lower values (63 ISQ) than 3p L implants (67 ISQ) in both the distal and mesial directions., Conclusions: These results demonstrated that the implant's length mainly influences the IT and RT values in the polyurethane blocks that mimic the mandibular region of the bone, resulting in higher values for the 3p S implants, while the RFA values remained unaffected. However, in the lowest density block simulating the maxillary bone, 3p L implants exhibited significantly higher ISQ values., Clinical Relevance: Therefore, our data offer valuable insights into the biomechanical behavior of these implants, which could be clinically beneficial for enhancing surgical planning., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)