Search

In today’s competitive environment, taking the advantage of supply chain which is both effective and efficient is a competitive advantage. An adequate supply chain has a multifaceted structure that focuses on integrating all factors, including pricing. The final product is delivered to customers based on maintaining market values and increasing strategic interactions. Present study aims to present the most effective functioning of competitive supply chain pricing in accordance with aspects of social responsibility. In doing so, we conducted a case study on oil-related products of Iranian knowledge-based companies. A combined analysis with 15 university-level industrial management experts was employed in this study to establish the components (competitive supply chain pricing function) and research propositions (dimensions of social responsibility). Twenty managers of knowledge-based enterprises in the oil field evaluated the components and propositions identified in the form of matrix questions using interpretative rating (IRP). The results showed that the proposition of the ethical dimension is the most effective measure of the social responsibility of knowledge-based companies in the oil field, creating competitive supply chain pricing functions based on value. This result shows that, under the ethical dimension of social responsibility, processes of competitive supply chain pricing are formed in accordance with the customer values and, according to the strategic relationship between the company and the economy with regional and global partners, maintaining values are a critical factor in developing our interactions between pricing factors. Given the results, in the first step for success, knowledge-based companies are recommended to consider the priorities of professional ethics in addition to knowledge in order to be able to gain the trust of customers by understanding their functional nature in the country’s developing economy. In this situation, the pricing process based on the creation of comprehensive values for customers can help to increase the company’s competitive position and make these companies to be at the first level of strategic interactions with companies that use petroleum products.

Abstract Wild-type cultivations are of invaluable relevance for industrial biotechnology when it comes to the agricultural or food sector. Here, genetic engineering is hardly applicable due to legal barriers and consumer’s demand for GMO-free products. An important pillar for wild-type cultivations displays the genus Bacillus. One of the challenges for Bacillus cultivations is the global ComX-dependent quorum sensing system. Here, molecular process control can serve as a tool to optimize the production process without genetic engineering. To realize this approach, quantitative knowledge of the mechanism is essential, which, however, is often available only to a limited extent. The presented work provides a case study based on the production of cyclic lipopeptide surfactin, whose expression is in dependence of ComX, using natural producer B. subtilis DSM 10 T. First, a surfactin reference process with 40 g/L of glucose was performed as batch fermentation in a pilot scale bioreactor system to gain novel insights into kinetic behavior of ComX in relation to surfactin production. Interestingly, the specific surfactin productivity did not increase linearly with ComX activity. The data were then used to derive a mathematic model for the time course of ComX in dependence of existing biomass, biomass growth as well as a putative ComX-specific protease. The newly adapted model was validated and transferred to other batch fermentations, employing 20 and 60 g/L glucose. The applied approach can serve as a model system for molecular process control strategies, which can thus be extended to other quorum sensing dependent wild-type cultivations.

Abstract Background Bacillus subtilis is a well-established host for a variety of bioproduction processes, with much interest focused on the production of biosurfactants such as the cyclic lipopeptide surfactin. Surfactin production is tightly intertwined with quorum sensing and regulatory cell differentiation processes. As previous studies have shown, a non-sporulating B. subtilis strain 3NA encoding a functional sfp locus but mutations in the spo0A and abrB loci, called JABs32, exhibits noticeably increased surfactin production capabilities. In this work, the impacts of introducing JABs32 mutations in the genes spo0A, abrB and abh from 3NA into strain KM1016, a surfactin-forming derivative of B. subtilis 168, was investigated. This study aims to show these mutations are responsible for the surfactin producing performance of strain JABs32 in fed-batch bioreactor cultivations. Results Single and double mutant strains of B. subtilis KM1016 were constructed encoding gene deletions of spo0A, abrB and homologous abh. Furthermore, an elongated abrB version, called abrB*, as described for JABs32 was integrated. Single and combinatory mutant strains were analysed in respect of growth behaviour, native P srfA promoter expression and surfactin production. Deletion of spo0A led to increased growth rates with lowered surfactin titers, while deletion or elongation of abrB resulted in lowered growth rates and high surfactin yields, compared to KM1016. The double mutant strains B. subtilis KM1036 and KM1020 encoding Δspo0A abrB* and Δspo0A ΔabrB were compared to reference strain JABs32, with KM1036 exhibiting similar production parameters and impeded cell growth and surfactin production for KM1020. Bioreactor fed-batch cultivations comparing a Δspo0A abrB* mutant of KM1016, KM681, with JABs32 showed a decrease of 32% in surfactin concentration. Conclusions The genetic differences of B. subtilis KM1016 and JABs32 give rise to new and improved fermentation methods through high cell density processes. Deletion of the spo0A locus was shown to be the reason for higher biomass concentrations. Only in combination with an elongation of abrB was this strain able to reach high surfactin titers of 18.27 g L−1 in fed-batch cultivations. This work shows, that a B. subtilis strain can be turned into a high cell density surfactin production strain by introduction of two mutations.

Background: Deep neural networks have been widely used in detection of P300 signal in Brain Machine Interface (BMI) systems which are rely on Event-Related Potentials (ERPs) (i.e. P300 signals). Such networks have high curvature variation in their error surface hampering their favorable performance. Therefore, the variations in curvature of the error surface must be minimized to improve the performance of these networks in detecting P300 signals. Objective: The aim of this paper is to introduce a method for minimizing the curvature of the error surface during training Convolutional Neural Network (CNN). The curvature variation of the error surface is highly dependent on model parameters of deep neural network; therefore, we try to minimize this curvature by optimizing the model parameters.Material and Methods: In this experimental study an attempt is made to tune the CNN parameters affecting the curvature of its error surface in order to obtain the best possible learning. For achieving this goal, Genetic Algorithm is utilized to optimize the above parameters in order to minimize the curvature variations. Results: The performance of the proposed algorithm was evaluated on EPFL dataset. The obtained results demonstrated that the proposed method detected the P300 signals with maximally 98.91% classification accuracy and 98.54% True Positive Ratio (TPR). Conclusion: The obtained results showed that using genetic algorithm for minimizing curvature of the error surface in CNN increased its accuracy in parallel with decreasing the variance of the results. Consequently, it may be concluded that the proposed method has considerable potential to be used as P300 detection module in BMI applications.

Research on knowledge distillation has become active in deep neural networks. Knowledge distillation involves training a low-capacity model from a high-capacity model. However, when the capacities of the teacher and student models differ, it can result to poor learning and low generalization performance. We propose here a novel teacher assistant model called Knowledge in Attention Assistant. This model learns learning a discriminative representation of important regions and statistical information along with spatial and channel knowledge. Moreover, by using a triplet attention mechanism, the student model can learn both the inner and outer distribution of different categories, and also memorize the knowledge distribution of the teacher model. This alignment improves the effectiveness and generalization of knowledge distillation and reduces the capacity gap between the teacher and student models. The present model addresses feature inconsistency by adjusting the attention weight distribution based on the resemblance between the features of the teacher and student. The evaluation of the proposed teacher assistant method shows remarkable results. The student model outperforms the teacher model in terms of generalization performance, achieving improvements of 93.37% and 94.09% on CIFAR-10 and CIFAR-100 datasets, respectively. Furthermore, the proposed model enhances the F1-scores 91.98% on CIFAR-10 and 79.69% on CIFAR-100. [ABSTRACT FROM AUTHOR]

Abstract A novel approach targeting self-inducible surfactin synthesis under oxygen-limited conditions is presented. Because both the nitrate (NarGHI) and nitrite (NasDE) reductase are highly expressed during anaerobic growth of B. subtilis, the native promoter P srfA of the surfactin operon in strain B. subtilis JABs24 was replaced by promoters P narG and P nasD to induce surfactin synthesis anaerobically. Shake flask cultivations with varying oxygen availabilities indicated no significant differences in native P srfA expression. As hypothesized, activity of P narG and P nasD increased with lower oxygen levels and surfactin was not produced by P srfA ::P narG as well as P srfA ::P nasD mutant strains under conditions with highest oxygen availability. P narG showed expressions similar to P srfA at lowest oxygen availability, while maximum value of P nasD was more than 5.5-fold higher. Although the promoter exchange P srfA ::P narG resulted in a decreased surfactin titer at lowest oxygen availability, the strain carrying P srfA ::P nasD reached a 1.4-fold increased surfactin concentration with 696 mg/L and revealed an exceptional high overall Y P/X of 1.007 g/g. This value also surpassed the Y P/X of the reference strain JABs24 at highest and moderate oxygen availability. Bioreactor cultivations illustrated that significant cell lysis occurred when the process of “anaerobization” was performed too fast. However, processes with a constantly low agitation and aeration rate showed promising potential for process improvement, especially by employing the strain carrying P srfA ::P nasD promoter exchange. Additionally, replacement of other native promoters by nitrite reductase promoter P nasD represents a promising tool for anaerobic-inducible bioprocesses in Bacillus.

Abstract Background Plipastatin is a potent Bacillus antimicrobial lipopeptide with the prospect to replace conventional antifungal chemicals for controlling plant pathogens. However, the application of this lipopeptide has so far been investigated in a few cases, principally because of the yield in low concentration and unknown regulation of biosynthesis pathways. B. subtilis synthesizes plipastatin by a non-ribosomal peptide synthetase encoded by the ppsABCDE operon. In this study, B. subtilis 3NA (a non-sporulation strain) was engineered to gain more insights about plipastatin mono-production. Results The 4-phosphopantetheinyl transferase Sfp posttranslationally converts non-ribosomal peptide synthetases from inactive apoforms into their active holoforms. In case of 3NA strain, sfp gene is inactive. Accordingly, the first step was an integration of a repaired sfp version in 3NA to construct strain BMV9. Subsequently, plipastatin production was doubled after integration of a fully expressed degQ version from B. subtilis DSM10T strain (strain BMV10), ensuring stimulation of DegU-P regulatory pathway that positively controls the ppsABSDE operon. Moreover, markerless substitution of the comparably weak native plipastatin promoter (P pps ) against the strong constitutive promoter P veg led to approximately fivefold enhancement of plipastatin production in BMV11 compared to BMV9. Intriguingly, combination of both repaired degQ expression and promoter exchange (P pps ::P veg ) did not increase the plipastatin yield. Afterwards, deletion of surfactin (srfAA-AD) operon by the retaining the regulatory comS which is located within srfAB and is involved in natural competence development, resulted in the loss of plipastatin production in BMV9 and significantly decreased the plipastatin production of BMV11. We also observed that supplementation of ornithine as a precursor for plipastatin formation caused higher production of plipastatin in mono-producer strains, albeit with a modified pattern of plipastatin composition. Conclusions This study provides evidence that degQ stimulates the native plipastatin production. Moreover, a full plipastatin production requires surfactin synthetase or some of its components. Furthermore, as another conclusion of this study, results point towards ornithine provision being an indispensable constituent for a plipastatin mono-producer B. subtilis strain. Therefore, targeting the ornithine metabolic flux might be a promising strategy to further investigate and enhance plipastatin production by B. subtilis plipastatin mono-producer strains.

Introduction: Recent studies have acknowledged the potential of convolutional neural networks (CNNs) in distinguishing healthy and morbid samples by using heart sound analyses. Unfortunately the performance of CNNs is highly dependent on the filtering procedure which is applied to signal in their convolutional layer. The present study aimed to address this problem by applying filter bank learning concept in CNNs. Material and Methods: In proposed method, the filter bank of CNN is updated based on a cross-entropy minimization rule to extract higher-level features from spectral characteristics of the heart sound signal. The deeper level of the extracted features in parallel with their spectral-based nature leads to better discrimination between healthy and morbid heart sounds. The proposed method was applied to three different heart sound datasets of PASCAL-A, PASCAL-B, and Kaggle, including normal and abnormal categories. Results: The proposed method obtained a true positive rate (TPR) between minimally 86% and maximally 96% (if FPR=0%) among all the examined datasets. In addition, the false-positive rate (FPR) was obtained as 7-8% (if TPR=100%) among the mentioned datasets. Finally, the accuracy was achieved in the range of 93-98% when the FPR was 0% and within the range of 96-96.5% when the TRP was 100%. Conclusion: Increased TPR in the proposed method (96% for the proposed method vs. 87% for CNN) in parallel with a decrease in its FPR (7% for the proposed method vs. 10% for CNN) showed the proposed method's superiority against its well-known alternative in automated self-assessment of the heart.

In the modern era, intellectual capital encompasses all resources within an organization that enhance the value and competence of the organization. Consequently, this indicates that managing intellectual capital effectively will enhance the value and performance of an organization. This study aims to investigate the effects of intellectual capital on business performance through the use of customer knowledge management in the Bank Mellat branches of Iran. In this study, all managers and employees working for Bank Mellat in Tehran are included. Based on Morgan’s table, the sample size was 220 people. Sampling was done by the simple random method. We used a descriptive correlation method to conduct this study and a questionnaire was used to collect data. The questionnaires were scored using a Likert scale. It was confirmed by a consensus of experts that the research instrument was valid, and the reliability of the research was 0.894%. Structural equation modeling was used to analyze the data. According to the results, the dimensions of intellectual capital (human, structural, and relational) have a significant impact on business performance. However, relational capital has been more influential on business performance than other factors.

Abstract Bacillus subtilis is described as a promising production strain for lipopeptides. In the case of B. subtilis strains JABs24 and DSM10T, surfactin and plipastatin are produced. Lipopeptide formation is controlled, among others, by the DegU response regulator. The activating phospho‐transfer by the DegS sensor kinase is stimulated by the pleiotropic regulator DegQ, resulting in enhanced DegU activation. In B. subtilis 168, a point mutation in the degQ promoter region leads to a reduction in gene expression. Corresponding reporter strains showed a 14‐fold reduced expression. This effect on degQ expression and the associated impact on lipopeptide formation was examined for B. subtilis JABs24, a lipopeptide‐producing derivative of strain 168, and B. subtilis wild‐type strain DSM10T, which has a native degQ expression. Based on the stimulatory effects of the DegU regulator on secretory protease formation, the impact of degQ expression on extracellular protease activity was additionally investigated. To follow the impact of degQ, a deletion mutant was constructed for DSM10T, while a natively expressed degQ version was integrated into strain JABs24. This allowed strain‐specific quantification of the stimulatory effect of degQ expression on plipastatin and the negative effect on surfactin production in strains JABs24 and DSM10T. While an unaffected degQ expression reduced surfactin production in JABs24 by about 25%, a sixfold increase in plipastatin was observed. In contrast, degQ deletion in DSM10T increased surfactin titer by threefold but decreased plipastatin production by fivefold. In addition, although significant differences in extracellular protease activity were detected, no decrease in plipastatin and surfactin produced during cultivation was observed.

Abstract Strain engineering is often a method of choice towards increasing the yields of the biosurfactant surfactin which is naturally synthesized by many Bacillus spp., most notably Bacillus subtilis. In the current study, a genome reduced B. subtilis 168 strain lacking 10% of the genome was established and tested for its suitability to synthesize surfactin under aerobic and anaerobic conditions at 25 °C, 30 °C, 37 °C and 40 °C. This genome reduced strain was named IIG-Bs20-5-1 and lacks, amongst others, genes synthesizing the lipopeptide plipastatin, the antibiotic bacilysin, toxins and prophages, as well as genes involved in sporulation. Amongst all temperatures tested, 37 °C was overall superior. In comparison to the reference strain JABs24, a surfactin synthesizing variant of B. subtilis 168, strain IIG-Bs20-5-1 was both aerobically and anaerobically superior with respect to specific growth rates µ and yields Y X/S. However, in terms of surfactin production, strain JABs24 reached higher absolute concentrations with up to 1147.03 mg/L and 296.37 mg/L under aerobic and anaerobic conditions, respectively. Concomitant, strain JABs24 reached higher Y P/S and Y P/X. Here, an outstanding Y P/X of 1.541 g/g was obtained under anaerobic conditions at 37 °C. The current study indicates that the employed genome reduced strain IIG-Bs20-5-1 has several advantages over the strain JABs24 such as better conversion from glucose into biomass and higher growth rates. However, regarding surfactin synthesis and yields, the strain was overall inferior at the investigated temperatures and oxygen conditions. Further studies addressing process development and strain engineering should be performed combining the current observed advantages of the genome reduced strain to increase the surfactin yields and to construct a tailor-made genome reduced strain to realize the theoretically expected advantages of such genome reduced strains.

Introduction: Brain-Computer Interface (BCI) offers a non-muscle way between the humanbrain and the outside world to make a better life for disabled people. In BCI applicationsP300 signal has an effective role; therefore, distinguishing P300 and non-P300 componentsin EEG signal (i.e. P300 detection) becomes a vital problem in BCI applications. Recently,Convolutional Neural Networks (CNNs) have had a significant application in detection ofP300 signals in the field of BCIs. The P300 signal has low Signal to Noise Ratio (SNR). Onthe other hand, the CNN detection rate is so sensitive to SNR; therefore, CNN detection ratedrops dramatically when it is faces with P300 data. In this study, a novel structure is proposed to improve the performance of CNN in P300 signal detection by means of improving its performance against low SNR signals.Methods: In the proposed structure, Sparse Representation-based Classification (SRC) wasused as the first substructure. This block is responsible for prediction of the expected P300signal among artifacts and noise. The second substructure performed P300 classification with Adadelta algorithm. Thanks to such SNR improvement scheme; the proposed structure i able to increase the rate of accuracy in the field of P300 signal detection.Results: To evaluate the performance of the proposed structure, we applied it on EPFLdataset for P300 detection, and then the achieved results were compared with those obtained from the basic CNN structure. The comparisons revealed the superiority of the proposed structure against its alternative, so that its True Positive Rate (TPR) was promoted about 19.66%. Such improvements for false detections and accuracy parameters were 1.93% and 10.46%, respectively, which show the effectiveness of applying the proposed structure in detecting P300 signals.Conclusion: The better accuracy of the proposed algorithm compared to basic CNN, inparallel with its more robustness, showed that the Sparse Representation-based Classification (SRC) had a considerable potential to be used as an improving idea in CNN-based P300 detection.Keywords: EEG, Neural Networks, Signal Detection, Machine Learning, Brain-ComputerInterfaces, Brain-Computer Interface, Brain, Neuroscience, P300, Convolutional NeuralNetworks, Deep Learning

The anaerobic growth of B. subtilis to synthesize surfactin poses an alternative strategy to conventional aerobic cultivations. In general, the strong foam formation observed during aerobic processes represents a major obstacle. Anaerobic processes have, amongst others, the distinct advantage that the total bioreactor volume can be exploited as foaming does not occur. Recent studies also reported on promising product per biomass yields. However, anaerobic growth in comparison to aerobic processes has several disadvantages. For example, the overall titers are comparably low and cultivations are time-consuming due to low growth rates. B. subtilis JABs24, a derivate of strain 168 with the ability to synthesize surfactin, was used as model strain in this study. Ammonium and nitrite were hypothesized to negatively influence anaerobic growth. Ammonium with initial concentrations up to 0.2 mol/L was shown to have no significant impact on growth, but increasing concentrations resulted in decreased surfactin titers and reduced nitrate reductase expression. Anaerobic cultivations spiked with increasing nitrite concentrations resulted in prolonged lag-phases. Indeed, growth rates were in a similar range after the lag-phase indicating that nitrite has a neglectable effect on the observed decreasing growth rates. In bioreactor cultivations, the specific growth rate decreased with increasing glucose concentrations during the time course of both batch and fed-batch processes to less than 0.05 1/h. In addition, surfactin titers, overall YP/X and YP/S were 53%, ∼42%, and ∼57% lower than in serum flask with 0.190 g/L, 0.344 g/g and 0.015 g/g. The YX/S, on the contrary, was 30% lower in the serum flask with 0.044 g/g. The productivities q were similar with ∼0.005 g/(g⋅h). However, acetate strongly accumulated during cultivation and was posed as further metabolite that might negatively influence anaerobic growth. Acetate added to anaerobic cultivations in a range from 0 g/L up to 10 g/L resulted in a reduced maximum and overall growth rate μ by 44% and 30%, respectively. To conclude, acetate was identified as a promising target for future process enhancement and strain engineering. Though, the current study demonstrates that the anaerobic cultivation to synthesize surfactin represents a reasonable perspective and feasible alternative to conventional processes.

Surfactin is described as a powerful biosurfactant and is natively produced by Bacillus subtilis in notable quantities. Among other industrially relevant characteristics, antimicrobial properties have been attributed to surfactin-producing Bacillus isolates. To investigate this property, stress approaches were carried out with biotechnologically established strains of Corynebacterium glutamicum, Bacillus subtilis, Escherichia coli and Pseudomonas putida with the highest possible amounts of surfactin. Contrary to the popular opinion, the highest growth-reducing effects were detectable in B. subtilis and E. coli after surfactin treatment of 100 g/L with 35 and 33%, respectively, while P. putida showed no growth-specific response. In contrast, other antimicrobial biosurfactants, like rhamnolipids and sophorolipids, showed significantly stronger effects on bacterial growth. Since the addition of high amounts of surfactin in defined mineral salt medium reduced the cell growth of B. subtilis by about 40%, the initial stress response at the protein level was analyzed by mass spectrometry, showing induction of stress proteins under control of alternative sigma factors σB and σW as well as the activation of LiaRS two-component system. Overall, although surfactin is associated with antimicrobial properties, relatively low growth-reducing effects could be demonstrated after the surfactin addition, challenging the general claim of the antimicrobial properties of surfactin.

Introduction: Laboratory science graduates are experts who together with other health care workers will be responsible for performing common clinical laboratories practices. In order to do this, the students must acquire the necessary knowledge and skills during the internship, and various problems will reduce the efficiency of internship in the field of laboratory sciences students. Identifying and solving these problems is essential to enhance the efficiency of this course. This research was done with the purpose of examining the laboratory sciences clerkship course by knowing about the viewpoints of the related faculty members, graduates and students at Hormozgan University of Medical Sciences.. Methods: In this qualitative study, a purposive sampling was used to select the subjects from the population of trainees, graduates and the faculty members, graduates and students of laboratory sciences. Semi-structured interviews were conducted. The results of the interviews led us to select the next sample, until no fresh ideas were gained. After gathering data from 13 persons, the results of the study were investigated by means of content analysis methodology. Results: By analyzing research data, five key themes were identified including clerkship curriculum, Expectations from clerkship, motivation of students for clerkship involvement and clerkship planning and management. Conclusion: The results of this study demonstrated that general view of instructors and students are positive, but in the implementation, there are problems that should be addressed by the authorities.. So it is necessary for officials to improve the quality of clerkship through more incorporated plans

Background: P300 signal detection is an essential problem in many fields of Brain-Computer Interface (BCI) systems. Although deep neural networks have almost ubiquitously used in P300 detection, in such networks, increasing the number of dimensions leads to growth ratio of saddle points to local minimums. This phenomenon results in slow convergence in deep neural network. Hyperparameter tuning is one of the approaches in deep learning, which leads to fast convergence because of its ability to find better local minimums. In this paper, a new adaptive hyperparameter tuning method is proposed to improve training of Convolutional Neural Networks (CNNs). Methods: The aim of this paper is to introduce a novel method to improve the performance of deep neural networks in P300 signal detection. To reach this purpose, the proposed method transferred the non-convex error function of CNN) into Lagranging paradigm, then, Newton and dual active set techniques are utilized for hyperparameter tuning in order to minimize error of objective function in high dimensional space of CNN. Results: The proposed method was implemented on MATLAB 2017 package and its performance was evaluated on dataset of Ecole Polytechnique Fédérale de Lausanne (EPFL) BCI group. The obtained results depicted that the proposed method detected the P300 signals with 95.34% classification accuracy in parallel with high True Positive Rate (i.e., 92.9%) and low False Positive Rate (i.e., 0.77%). Conclusions: To estimate the performance of the proposed method, the achieved results were compared with the results of Naive Hyperparameter (NHP) tuning method. The comparisons depicted the superiority of the proposed method against its alternative, in such way that the best accuracy by using the proposed method was 6.44%, better than the accuracy of the alternative method.

Background: For planning in health,preventing and representing valuable dentistry services, we need to identify and evaluate the information on the status of individuals' dental hygiene and health. In this examination, evaluating dental health which is one of hygienic main and key problems has been conducted according to world's standards in correction center of Tehran province in 2008.. Methods: The examination was performedbased on the suggested standards of World Health Organization (WHO). The mission team sent to this center includes senior students of dentistry who divided into two (examiner and coder) groups. These students examined190 persons (172 male and 18 female) and filled the relevant form. After collecting information and filling examination forms, the statistical analysis was carried out and the results were reported. Results: The DMF index was 6.3 in the studied population. The values for females and males were 6.9 and 6.2, respectively. D, M and F indexes were3.69, 1.89 and 1.72, respectively. About13% of samples were caries free and dental Hypoplasiawas detected in 11% of samples and fluorosiswas observed in 2%. The most required treatment were filling one surfaceand fillingcomplicated and pull a tooth: 27.2%, 8.5% and 6%, respectively. Conclusions: DMF index was averagely lower than 4 which represented low levels of dentistry hygiene.Only 13% of samples were caries free which represented the preventive services weakness of mouth health.Therefore, it is necessary to perform special program for the purpose of WHO about DMFT rate.

Background: Knowledge of existing situation in each region plays great role in order to prevent oral and dental diseases in people. Meanwhile, DMFT index is one of the best epidemiological indices in dentistry representing oral hygiene situation in society. So, this study was conducted in order to evaluate DMFT index in 12- years-old students of Zarand City at 2011. Methods: This descriptive study was done cross – sectionally using interview, examination and questionnaire among 12- years- old students of Zarand city. Considering WHO criteria, 350 samples were selected for the study and periodontal condition, number of caries, decayed, missed and filled teeth, existing fluorosis, occlusion, orthodontic and preventive treatment were evaluated. The data were analyzed by SPSS software Version 17. Results: The mean of DMFT index was 2.03 that it was zero at 121 students (34.6%) and maximum of DMFT reported at 11 persons (0.6%). The 34.6% of students were caries free. Results revealed no significant differences in need to orthodontic treatment between different groups of DMFT. Conclusion: Considering WHO criteria, the achieved, DMFT index in Zarand city was not acceptable. According to the aim of WHO for the year of 2015 for 12 years old people (SCI of less than 3DMFT

Objectives: Consumption of fruits, such as plums and prunes, is useful in treating blood circulation disorder, measles, digestive disorder, and prevention of cancer, diabetes, and obesity. The paper presents a description of antioxidant and antiradical capacity of plum (Prunus domestica L.) in both fresh and dried samples. Materials and Methods: Samples were mixed with methanol and ethanol (as solvents) and were extracted on magnetic shaker, separately. The experiments were carried out to measure the Total Phenolic Content (TPC), Total Flavonoid Content (TFC), Total Antioxidant Capacity (TAC), Reducing Power Assay (RPA), Chain Breaking Activity (CBA), and quantity of Malondialdehyde (MDA), 2,2-Diphenyl-1-Picrylhydrazyl (DPPH),Nitric Oxide (NO),Hydrogen peroxide (H2O2) and superoxide(O2-) radicals inhibition. Results: The results showed that the highest values for the TPC, TFC,TAC, RPA, CBA, DPPH, and NO were related to ethanolic extractsof dried sample which showed statistically significant differences (p2O2 and O2-were related to ethanolic extracts of fresh sample. The correlations data were analyzed among all parameters and the TPC and TFC had a significant correlation (r2=0.977). Moreover, it was found that methanol was more successful in extraction procedure than ethanol (p