Recent publications
Objective
This study aims to elucidate the cognitive underpinnings of language abnormalities in Alzheimer's Disease (AD) using a computational cross‐linguistic approach and ultimately enhance the understanding and diagnostic accuracy of the disease.
Methods
Computational analyses were conducted on language samples of 156 English and 50 Persian speakers, comprising both AD patients and healthy controls, to extract language indicators of AD. Furthermore, we introduced a machine learning‐based metric, Language Informativeness Index (LII), to quantify empty speech.
Results
Despite considerable disparities in surface structures between the two languages, we observed consistency across language indicators of AD in both English and Persian. Notably, indicators of AD in English resulted in a classification accuracy of 90% in classifying AD in Persian. The substantial degree of transferability suggests that the language abnormalities of AD do not tightly link to the surface structures specific to English. Subsequently, we posited that these abnormalities stem from impairments in a more universal aspect of language production: the ability to generate informative messages independent of the language spoken. Consistent with this hypothesis, we found significant correlations between language indicators of AD and empty speech in both English and Persian.
Interpretation
The findings of this study suggest that language impairments in AD arise from a deficit in a universal aspect of message formation rather than from the breakdown of language‐specific morphosyntactic structures. Beyond enhancing our understanding of the psycholinguistic deficits of AD, our approach fosters the development of diagnostic tools across various languages, enhancing health equity and biocultural diversity.
Introduction
Upper Cross Syndrome is a pattern of muscle imbalance and postural dysfunction that can cause discomfort and pain. This study’s objective was to compare the effects of Pilates exercises, corrective exercises, and Alexander’s technique on upper cross syndrome in adolescent girls aged 13–16 years: a six-week intervention study.
Methods
The present study was Quasi-experimental, and its statistical population consisted of 13 to 16-year-old female students. Forty-five students who were diagnosed with upper cross syndrome were purposefully selected as samples and randomly assigned to three groups: Pilates exercises (N = 15), corrective exercises (N = 15), and Alexander’s technique (N = 15). The participants performed exercises for 60 min per session, three sessions per week, and six weeks. This study’s objective was to compare the effects of Pilates exercises, corrective exercises, and Alexander’s technique on upper cross syndrome in adolescent girls aged 13–16 years: a six-week intervention study. This study was retrospectively registered in the Iranian Registry of Clinical Trials (IRCT) on 2023-09-19 to comply with the journal’s policies. The assigned trial registration number is IRCT20230810059106N1.
Results
The results of the dependent t-test showed significant decreases in forward head angle (p = 0.0001), rounded shoulder (p = 0.001), and kyphosis (p = 0.0001) as a result of corrective exercises. There were also significant decreases in forward head angle (p = 0.0001), rounded shoulder (p = 0.002), and kyphosis (p = 0.001) after six weeks of practising Alexander’s technique. However, in the case of Pilates exercises, a significant decrease in forward head angle (p = 0.110), rounded shoulder (p = 0.598), and kyphosis (p = 0.371) was not observed. The one-way analysis of variance revealed a significant difference in the forward head angle (p = 0.012), rounded shoulders (p = 0.013), and kyphosis (p = 0.009).
Conclusions
The effect of Alexander’s technique and corrective exercises on forward head angle, rounded shoulder, and kyphosis abnormalities was almost similar and more effective than pilates exercises.
Water-soluble vitamins have a pivotal role in nurturing ocular vitality and forestalling ocular diseases. Profound importance of vitamin C and B-complex vitamins in the preservation of ocular well-being and the mitigation of susceptibility to afflictions such as cataracts and age-related macular degeneration (ARMD) has been illustrated. Conceivable role of these vitamins in risk attenuation in cardiac diseases has been studied, although the uniform manifestation of cardiovascular benefits through randomized trials remains equivocal. The convergence of water-soluble vitamins and biosensors proffers a dual promise - on one hand, the potential for real-time, personalized insights into an individual's nutritional status, and on the other, a pathway to unraveling the complexities underpinning the absorption, utilization, and disposition of these vital micronutrients within the human body. However, it is prudent to recognize that while the alliance holds significant transformative potential, it also navigates the frontiers of scientific exploration, and its full realization requires continued research and innovation.
Fat-soluble vitamins have a pivotal role in in maintaining good vision and overall eye health. Profound importance of vitamin A in lowering risk of cataracts and age-related macular degeneration (ARMD) has been illustrated. Also, plausible role of fat-soluble vitamins in risk attenuation in cardiac diseases has been studied. This chapter also discusses the role of Vitamin D in the immune system and its potential impact on infectious diseases. It highlights that Vitamin D has a significant influence on both innate and adaptive immunity, affecting various immune cells. Vitamin D fosters immune tolerance by promoting regulatory T cells (Tregs) and suppresses inflammation by altering the type of T cells produced. It also enhances the function of immune cells like macrophages and dendritic cells. Moreover, Vitamin D is linked to infectious diseases, and there’s evidence suggesting it may play a role in combating conditions such as tuberculosis, respiratory infections, and influenza. However, randomized controlled trials have produced inconsistent results regarding the prophylactic use of Vitamin D for infectious diseases. The importance of avoiding Vitamin D toxicity has been discussed. Further research is needed to fully understand its role in infectious diseases. Finally, the chapter emphasizes the importance of informed decision-making when it comes to vitamin supplementation and dispelling common myths and misconceptions.
Flood early warning requires rainfall data with a high temporal and spatial resolution for flood risk analysis to simulate flood dynamics in all small and large basins. However, such high-quality data are still very scarce in many developing countries. In this research, in order to identify the best and most up-to-date rainfall estimation tools for early flood forecasting in arid and semi-arid regions, the northeastern region of Iran with 17 meteorological stations and four rainfall events was investigated. The rainfall products of satellites (PERSIANN-CDR and GSMaP, ERA5, GPM CHIRPS) along with the most widely used microphysical schemes of Weather Research and Forecasting (WRF) model (Purdue-Lin (Lin), WRF Single-Moment class 3, 6 (WSM3, WSM6), and WRF Double-Moment class 6 (WDM6). were used for rainfall modeling. The efficiency of each of these models to forecasting the amount of rainfall was verified by four methods: Threat Scores (TS), False Alarm Ratio (FAR), Hit Rate (H), and False Alarm (F). Analysis of research findings showed that the WRF meteorological model has better accuracy in rainfall modeling for the next 24 hours. In this model, Lin's microphysical scheme has the highest accuracy, and its threat score (TS) quantity is up to 98% efficient in some stations. The best accuracy of satellite products for estimating the amount of rainfall is up to 50%. This accuracy value is related to the satellite product (ERA5). In this method, an 18 km distance from the ground station is the best distance for setting up the space station, which is used for input to hydrological/hydraulic models. Based on the results of this research, by using the connection of the WRF model with hydrology/hydraulic models, it is possible to predict and simulate rainfall-runoff up to 72 hours before its occurrence. Also, by using these space stations, the amount of rainfall is estimated for the entire area of the basin and an early flood warning is issued.
Located in Khorasan Razavi province, Torghabeh city is a year-round tourist attraction in the north–east of Iran because of its natural and environmental beauty and semi-rural ecosystems. The aim of this article is to describe the challenges Torghabeh faces regarding rapid urbanisation with an environmental and biophilic approach. This article uses the qualitative–quantitative research method, and the results are analyzed in SPSS software and with the linear regression method to identify the most important factors. Based on the results, the most influential components in improving the urban environment of the city are as follows: the extent and severity of soil contamination; amount and severity of acoustic pollution; conservation, restoration and enhancement of biodiversity of the city; low-impact development; innovative and new urban green spaces and considerations and provision of water resources.
The present paper simulates cyberattacks in DIgSILENT for energy management and state estimation. Assuming hackers have adequate information to alter input data, they can alter the power market and the available transmission capability (ATC). Detection programs may fail if false information is coordinated in the presence of error information. The minimum number of network measurements before the state estimation program converges is 54% of the total measurements. In the new method, weighted least squares improve the state estimation speed. The new method can also improve the speed of ATC. In addition to identifying the cyberattack, the algorithm in the present paper can be used to identify the target of the attack. It also uses complete and correct information and even incorrect measurements to report state estimator errors. The present paper shows that ATC values follow the inverse pattern of load and loss. A real sample network is presented at the end of the paper to test the suggested method.
Background and Aims Aging causes alterations in various body functions, such as motor, sensory, cognitive and psychosocial. The present study was performed to compare the effects of two types of gait-retraining approach on the balance and motor performance of elderly women at risk of falling Methods This study is a semi experimental research with pretest-posttest plan, in which 45 women elderly between 60 and 75 years were randomly divided into two experimental (n=30) and one control groups (n=15). The experimental group (8 weeks, 3 sessions per week, each session 45 minutes). In order to assess on balance and motor performance of subject, Berg Balance Scale, and 10 meter walk test was used. Analysis of covariance (ANCOVA) was used to analyze the data, SPSS statistical package was used for all analyzes. In this study, significance level equal was considered to 95% and level of alpha was considered less than or equal to 0/05. Results The findings of this study showed that both selected exercises had significance effect on balance and motor performance in non reactive elderly women. Conducting a between-group comparison also showed that the which was related to the training with ground balance ladder, respectively (P≤0.05). However, there was no significant difference in the control group for all three variables. Conclusion This study showed that exercise two kinds of tutorial gait approach reduce can improve postural control and decrease the risk of falls in the elderly. Therefore it can be used to reduce risk of falls.
DC microgrid is a high‐efficiency plan for exploiting and controlling distributed generation (DG) resources that can supply local loads in grid‐connected or islanded mode. Conventionally, the droop control method is utilized to attain proper load sharing among the DGs as a decentralized approach in DC microgrids. However, accurate current sharing among DG units with different line resistances is not achievable by the conventional droop control, whereas this method also increases the DC bus voltage deviation. In this paper, a new droop‐based distributed control method is proposed in the secondary control level to overcome the limitations of droop control. To implement the proposed method, only the amount of precalculated virtual voltage drop of DG units is shared with adjacent DGs through a low‐bandwidth communication, and other calculations are local. So, there is no need to define and share new parameters, and get feedback from the DC bus voltage. By employing the proposed method, not only accurate current sharing among the DG units is guaranteed but also DC bus voltage is restored to the nominal value. To ensure the stability of the proposed method, the robust stability and performance of the closed‐loop system are analyzed by structured singular value (µ) under resistive load and communication delay changes. Finally, a DC microgrid is evaluated using MATLAB/Simulink as well as experimental tests to illustrate the validity and efficiency of the proposed method.
Diabetic retinopathy (DR) is the major cause of visual impairment among diabetic patients. Significant works have been done to hybrid a modified CNN architecture such as AlexNet with some of classifiers such as support vector machines (SVMs) or fuzzy C-Means (FCM) to improve the DR screening. This new hybrid innovative structure uses more efficient extracting features of a retinal images in both spatial and spectral domains. In spite the advantages of this innovative architecture, the different kernel functions affect the performance of the proposed algorithm. Using the appropriate transformed data into two- or three-dimensional feature maps and using an improved support vector domain description (ISVDD) can obtain more flexible and more accurate image description. To this end, the optimal degree values of different kernel functions can be extracted by using a particle swarm optimization (PSO) algorithm. Also, we compared the performance of our approach (modified-AlexNet-ISVDD) with the results obtained by hybrid modified AlexNet and some of classifiers such as K-Nearest Neighbors (KNN) and FCM clustering. We achieve the proposed CNN architecture using ISVDD on the DIARETDB1 and MESSIDOR datasets, with more than 99% sensitivity.
Available transfer capability or available transmission capacity (ATC) is defined as the excessive power that can be safely and effectively transacted along and beyond transactions previously conducted in a power system. DELF (Differential Equation Load Flow) is a new method of turning a power flow model into a dynamic system. The speed of DELF is improved in the present study through enhancing the inverse matrix approach. Furthermore, a highly effective and precise approach is taken to the evaluation of Static ATC with the (n-1) contingency. This method has been successfully employed in six different systems for multilateral and bilateral transactions. Compared with the outcome of five older techniques, the present findings showed that the new approach is faster and more accurate.
Edge Cloud Computing (ECC) is a new approach for bringing Mobile Cloud Computing (MCC) services closer to mobile users in order to facilitate the complicated application execution on resource-constrained mobile devices. The main objective of the ECC solution with the cloudlet approach is mitigating the latency and augmenting the available bandwidth. This is basically done by deploying servers (a.k.a. “Cloudlets”) close to the user’s device on the edge of the cellular network. When considering the users’ mobility along with the limited resource of the cloudlets serving them, the user-cloudlet communication may need to go through multiple hops, which may seriously affect the communication delay between them and the quality of services (QoS). To reduce as much as possible the negative effects of such a QoS degradation, service execution must be dynamically migrated to a better placement. This study proposes a novel Cost-aware Virtual Machine (VM) placement and migration (CoPaM) framework for mobile services in a network of cloudlets. A Mixed Integer Linear Programming (MILP) model is proposed to select the least cost cloudlets for serving mobile users to a given trajectory in advance based on path prediction methods. Since the proposed model is NP-hard, it is not applicable within large-scale environments with a centralized approach and the use of Software Defined Networking (SDN) technology. Therefore, a heuristic algorithm is presented. Experiments are conducted by emulating the proposed framework in Mininet-WiFi with the Floodlight usage as the SDN controller. The simulation results show the superiority of the performance of the proposed architecture in terms of the service rate and the costs imposed on the operator in comparison to existing approaches.
Dynamic Available Transfer Capability (DATC) is one of the critical calculations in the electricity market. A combined method for DATC calculation (CDATC) is proposed. The CDATC as a combination of the Newton-Raphson-Seydel (NRS) and the Down-Hill (DH) evolves while overcoming their limitations. The proposed method makes use of Estimate-PEBS (EPEBS) and Estimate-POMP (EPOMP) to find transient stability. Further, online state estimation (ES) is integrated into the model to sound the solution more realistic. Simulation results exhibited that the proposed CDATC can cater to a quality solution represented by fast computational performance and higher accuracy results as compared with FADATC method. Implementation of the developed model on the real-world system of the West-Iran with 848 bus and Iowa State with 145 bus proved its suitability for utilities even in presence of large wind farms. The simulation results further indicated that the CDATC can be used for online applications for large systems.
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