Chemical identification,antioxidant, cholinesterase inhibitory,and cytotoxic properties of fucoidan extracted from Persian Gulf Sargassum angustifolium

Marine macroalgal sulfated fucose-containing polysaccharides, like fucoidan, have drawn significant attention due to their biotechnological potentials, such as anti-cancer, antioxidant, and anti-cholinesterase activities. The fucoidan derived from brown macroalgae Sargassum angustifolium species (FSA) was investigated for its cytotoxic effects and alterations in cell proliferation, and cell cycle-related gene expression in the present study occurred on NB4 cell line. The results showed that FSA would induce p53, p21, pro-apoptotic genes and increase expression of the p15 gene as a cell arrest marker. Also, FSA inhibited the anti-apoptotic effect of the Bcl-2 gene and decreased dnmt-1 gene expression. FSA significantly exhibited potent 2, 2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging activity (p<0.05) with an IC₅₀ value of 0.157 mg/mL and showed moderate anti-acetylcholinesterase activity with an IC₅₀ value of 1.20 μg/mL. These results indicated the potential of FSA for the development of therapeutic or preventive agents of cancer and Alzheimer’s disease mainly through cytotoxic effect and AChE (acetylcholinesterase) inhibition as well as additional antioxidant capacities.     

Non-minimal braneworld inflation after the Planck

The recently released Planck data have constrained 4-dimensional inflationary parameters even more accurately than ever. We consider an extension of the braneworld model with induced gravity and a non-minimally coupled scalar field on the brane. We constraint the inflation parameters in this setup, by adopting six types of potential, in confrontation with the joint Planck + WMAP9 + BAO data. We show that a potential of the type V(φ)=V ₀exp(?βφ) has the best fit with newly released observational data.     

Lithospheric structure of NW Iran from P and S receiver functions

We computed P and S receiver functions to investigate the lithospheric structure beneath the northwest Iran and compute the Vp/Vs ratio within the crust of this seismologically active area. Our results enabled us to map the lateral variations of the Moho as well as those of the lithosphere–asthenosphere boundary (LAB) beneath this region. We selected data from teleseismic events (M_b?>?5.5, epicentral distance between 30° and 95° for P receiver functions and M_b?>?5.7, epicentral distance between 60° and 85° for S receiver functions) recorded from 1995 to 2008 at 8 three-component short-period stations of Tabriz Telemetry Seismic Network. Our results obtained from P receiver functions indicate clear conversions at the Moho boundary. The Moho depth was firstly estimated from the delay time of the Moho converted phase relative to the direct P wave. Then we used the H-Vp/Vs stacking algorithm of Zhu and Kanamori to estimate the crustal thickness and Vp/Vs ratio underneath the stations with clear Moho multiples. We found an average Moho depth of 48 km, which varies between 38.5 and 53 km. The Moho boundary showed a significant deepening towards east and north. This may reveal a crustal thickening towards northeast possibly due to the collision between the Central Iran and South Caspian plates. The obtained average Vp/Vs ratio was estimated to be 1.76, which varies between 1.73 and 1.82. The crustal structure was also determined by modeling of P receiver functions. We obtained a three-layered model for the crust beneath this area. The thickness of the layers is estimated to be 6–11, 18–35, and 38–53 km, respectively. The average of the shear wave velocity was calculated to be 3.4 km/s in the crust and reaches 4.3 km/s below the Moho discontinuity. The crustal thickness values obtained from P receiver functions are in good agreement with those derived by S receiver functions. In addition, clear conversions with negative polarity were observed at ~8.7 s in S receiver functions, which could be related to the conversion at the LAB. This may show a relatively thin continental lithosphere of about 85 km implying that the lithosphere was influenced by various geodynamical reworking processes in the past.     

Crustal structure of Northwest Zagros (Kermanshah) and Central Iran (Yazd and Isfahan) using teleseismic Ps converted phases

Receiver functions are widely employed to detect P-to-S converted waves and are especially useful to image seismic discontinuities in the crust. In this study we used the P receiver function technique to investigate the velocity structure of the crust beneath the Northwest Zagros and Central Iran and map out the lateral variation of the Moho boundary within this area. Our dataset includes teleseismic data (M _b ≥ 5.5, epicentral distance from 30° to 95°) recorded at 12 three-component short-period stations of Kermanshah, Isfahan and Yazd telemetry seismic networks. Our results obtained from P receiver functions indicate clear Ps conversions at the Moho boundary. The Moho depths were firstly estimated from the delay time of the Moho converted phase relative to the direct P wave beneath each network. Then, we used the P receiver function inversion to find the properties of the Moho discontinuity such as depth and velocity contrast. Our results obtained from PRF are in good agreement with those obtained from the P receiver function modeling. We found an average Moho depth of about 42 km beneath the Northwest Zagros increasing toward the Sanandaj-Sirjan Metamorphic Zone and reaches 51 km, where two crusts (Zagros and Central Iran) are assumed to be superposed. The Moho depth decreases toward the Urmieh-Dokhtar Cenozoic volcanic belt and reaches 43 km beneath this area. We found a relatively flat Moho beneath the Central Iran where, the average crustal thickness is about 42 km. Our P receiver function modeling revealed a shear wave velocity of 3.6 km/s in the crust of Northwest Zagros and Central Iran increasing to 4.5 km/s beneath the Moho boundary. The average shear wave velocity in the crust of UDMA as SSZ is 3.6 km/s, which reaches to 4.0 km/s while in SSZ increases to 4.3 km/s beneath the Moho.     

Erratum to: Lithospheric structure of NW Iran from P and S receiver functions

We computed P and S receiver functions to investigate the lithospheric structure beneath the northwest Iran and compute the Vp/Vs ratio within the crust of this seismologically active area. Our results enabled us to map the lateral variations of the Moho as well as those of the lithosphere–asthenosphere boundary (LAB) beneath this region. We selected data from teleseismic events (M_b > 5.5, epicentral distance between 30° and 95° for P receiver functions and M_b > 5.7, epicentral distance between 60° and 85° for S receiver functions) recorded from 1995 to 2008 at 8 three-component short-period stations of Tabriz Telemetry Seismic Network. Our results obtained from P receiver functions indicate clear conversions at the Moho boundary. The Moho depth was firstly estimated from the delay time of the Moho converted phase relative to the direct P wave. Then we used the H-Vp/Vs stacking algorithm of Zhu and Kanamori to estimate the crustal thickness and Vp/Vs ratio underneath the stations with clear Moho multiples. We found an average Moho depth of 48 km, which varies between 38.5 and 53 km. The Moho boundary showed a significant deepening towards east and north. This may reveal a crustal thickening towards northeast possibly due to the collision between the Central Iran and South Caspian plates. The obtained average Vp/Vs ratio was estimated to be 1.76, which varies between 1.73 and 1.82. The crustal structure was also determined by modeling of P receiver functions. We obtained a three-layered model for the crust beneath this area. The thickness of the layers is estimated to be 6–11, 18–35, and 38–53 km, respectively. The average of the shear wave velocity was calculated to be 3.4 km/s in the crust and reaches 4.3 km/s below the Moho discontinuity. The crustal thickness values obtained from P receiver functions are in good agreement with those derived by S receiver functions. In addition, clear conversions with negative polarity were observed at ~8.7 s in S receiver functions, which could be related to the conversion at the LAB. This may show a relatively thin continental lithosphere of about 85 km implying that the lithosphere was influenced by various geodynamical reworking processes in the past.     

Cosmological dynamics of a non-minimally coupled bulk scalar field in DGP setup

We consider cosmological dynamics of a canonical bulk scalar field, which is coupled non-minimally to 5-dimensional Ricci scalar in a DGP setup. We show that presence of this non-minimally coupled bulk scalar field affects the jump conditions of the original DGP model significantly. Within a superpotential approach, we perform some numerical analysis of the model parameter space and consider bulk-brane energy exchange in this setup. Also we show that the normal, ghost-free branch of the DGP solutions in this case has the potential to realize a self-consistent phantom-like behavior and therefore explains late time acceleration of the universe in a consistent way.     

Evaluation of deep learning algorithms for national scale landslide susceptibility mapping of Iran

The identification of landslide-prone areas is an essential step in landslide hazard assessment and mitigation of landslide-related losses.In this study,we applied two novel deep learning algorithms,the recurrent neural network(RNN)and convolutional neural network(CNN),for national-scale landslide susceptibility mapping of Iran.We prepared a dataset comprising 4069 historical landslide locations and 11 conditioning factors(altitude,slope degree,profile curvature,distance to river,aspect,plan curvature,distance to road,distance to fault,rainfall,geology and land-sue)to construct a geospatial database and divided the data into the training and the testing dataset.We then developed RNN and CNN algorithms to generate landslide susceptibility maps of Iran using the training dataset.We calculated the receiver operating characteristic(ROC)curve and used the area under the curve(AUC)for the quantitative evaluation of the landslide susceptibility maps using the testing dataset.Better performance in both the training and testing phases was provided by the RNN algorithm(AUC=0.88)than by the CNN algorithm(AUC=0.85).Finally,we calculated areas of susceptibility for each province and found that 6%and 14%of the land area of Iran is very highly and highly susceptible to future landslide events,respectively,with the highest susceptibility in Chaharmahal and Bakhtiari Province(33.8%).About 31%of cities of Iran are located in areas with high and very high landslide susceptibility.The results of the present study will be useful for the development of landslide hazard mitigation strategies.     

Simulation of Salinity Distribution of Anbar Salt Dome in Gotvand Reservoir in Iran,Using System Dynamics and Proposes a Strategy to Reduce Salinity

Water Resources - To water quality management of the Gotvand Reservoir, this paper attempts to determine to what extent the negative impacts of Anbar salt domes dissolution can be reduced...     

Regional precipitation trend analysis at the Langat River Basin,Selangor, Malaysia

Various hydrological and meteorological variables such as rainfall and temperature have been affected by global climate change. Any change in the pattern of precipitation can have a significant impact on the availability of water resources, agriculture, and the ecosystem. Therefore, knowledge on rainfall trend is an important aspect of water resources management. In this study, the regional annual and seasonal precipitation trends at the Langat River Basin, Malaysia, for the period of 1982–2011 were examined at the 95 % level of significance using the regional average Mann–Kendall (RAMK) test and the regional average Mann–Kendall coupled with bootstrap (RAMK–bootstrap) method. In order to identify the homogeneous regions respectively for the annual and seasonal scales, firstly, at-site mean total annual and separately at-site mean total seasonal precipitation were spatialized into 5 km?×?5 km grids using the inverse distance weighting (IDW) algorithm. Next, the optimum number of homogeneous regions (clusters) is computed using the silhouette coefficient approach. Next, the homogeneous regions were formed using the K-mean clustering method. From the annual scale perspective, all three regions showed positive trends. However, the application of two methods at this scale showed a significant trend only in the region AC1. The region AC2 experienced a significant positive trend using only the RAMK test. On a seasonal scale, all regions showed insignificant trends, except the regions I1C1 and I1C2 in the Inter-Monsoon 1 (INT1) season which experienced significant upward trends. In addition, it was proven that the significance of trends has been affected by the existence of serial and spatial correlations.