On the use of formal methods to model and verify neuronal archetypes

Having a formal model of neural networks can greatly help in understanding and verifying their properties, behavior, and response to external factors such as disease and medicine. In this paper, we adopt a formal model to represent neurons, some neuronal graphs, and their composition. Some specific neuronal graphs are known for having biologically relevant structures and behaviors and we call them archetypes. These archetypes are supposed to be the basis of typical instances of neuronal information processing. In this paper we study six fundamental archetypes (simple series, series with multiple outputs, parallel composition, negative loop, inhibition of a behavior, and contralateral inhibition), and we consider two ways to couple two archetypes: (i) connecting the output(s) of the first archetype to the input(s) of the second archetype and (ii) nesting the first archetype within the second one. We report and compare two key approaches to the formal modeling and verification of the proposed neuronal archetypes and some selected couplings. The first approach exploits the synchronous programming language Lustre to encode archetypes and their couplings, and to express properties concerning their dynamic behavior. These properties are verified thanks to the use of model checkers. The second approach relies on a theorem prover, the Coq Proof Assistant, to prove dynamic properties of neurons and archetypes.     

Isolation and molecular identification of cellulolytic bacteria from Dig Rostam hot spring and study of their cellulase activity

Cellulose is the main structural component of lignocellulosic wastes that can be converted to sugars and biofuels by cellulase. Due to wide applications of this enzyme in various industries around the world, cellulase is considered as the third industrial enzyme. The ability of thermophilic bacteria in the production of heat-stable cellulases has made them valuable tools in biotechnology. The aim of this study was isolation and molecular identification of cellulolytic thermophile bacteria from Dig Rostam hot spring and investigating their cellulase activity. Samples were taken from water and sediments of this hot spring, and cellulolytic bacteria were enriched in media containing cellulose as the only carbon source. The bacteria were incubated at 60°C, and single colonies were then isolated on solid media. Congo red assay was used as a quick test for the qualitative screening of cellulase activity. According to these qualitative results, four colonies named CDB1, CDB2, CDB3, and CDB4 were isolated, and their growth curve and some other characteristics were determined by biochemical assays. Moreover, endoglucanase, exoglucanase, and FPase activities of the isolates were investigated quantitatively. Results indicated that CDB1 exhibited the highest endoglucanase (0.096 U/mL) and exoglucanase (0.156 U/mL) activities among other isolates. 16S rDNA partial sequencing indicated that CDB1 had 99% similarity to the genus Anoxybacillus, and the other isolates showed the highest similarity to the genus Geobacillus. The cellulase gene of CDB1 isolate with the highest cellulase activity was also cloned, and its sequence is reported for the first time. Further studies on this thermophilic enzyme might be useful for industrial applications.     

A PROBABILISTIC APPROACH FOR ESTIMATING TUNNELING DURATION

This paper describes an analytical approach for developing the Cumulative Distribution Function, CDF, of time to completion of any segment of the Outfall Tunnel of Boston Harbor Cleanup Project. For any given tunnel length, one can calculate the probability of completing that length within a specified time. The approach proposed is general enough to be used on relatively long tunnels with durations extending over several months. It presents a case in data modeling where a large volume of data is reduced and reported in a usable format. Model application is shown through a numerical example and the results are compared wih the actual data obtained which shows that the difference between actual data and predicted result is not significant.     

经形变热处理铜基形状记忆合金的晶粒生长、形状记忆和腐蚀行为

比较研究了Cu-11．8％Al-3．7％Ni-1％Mn和Cu-11％A1—5．6％Mn形状记忆合金（SMAS）的形状记忆、腐蚀性能。采用光学显微镜（0M）、扫描电子显微镜（SEM）、差示扫描量热法（DSC）、动电位极化、弯曲和拉伸试验,研究了晶粒细化对这些性能的影响。在800。C退火时,在首先的15S内静态再结晶和动态晶粒长达显示出一个快速的再结晶过程,随后才是晶粒生长。退火15S后得到的Cu—A1—Ni-Mn和Cu-Al—Mn合金的最小晶粒尺寸分别为90gm和260pm。拉伸试验表明2种合金呈现典型的三阶段曲线,由此可以看出,晶粒细化后合金具有高的断裂应力和应变。显微组织表明,Cu—Al-Ni—Mn合金中存在锯齿状的所马氏体形态,通过差示扫描量热法也证实了所和rf共存于Cu—A1-Mn合金中。评估了形变热处理前、后及800℃退火15min,随后进行水淬的合金的形状记忆性能。另外,采用动电位极化法分析了晶粒细化后合金的腐蚀行为。结果表明,铜溶解过程中主要为阳极反应,Cu—Al—Ni—Mn合金比Cu—A1-Mn合金具有更好的耐腐蚀性。     

Bioremediation of phenol,sulfate sodium,and polycyclic aromatic hydrocarbons by Rhodococcus sp. first time isolated and molecular characterized from aquatic and terrestrial ecosystems

Environmental pollutions are the most significant problem worldwide. Rhodococcus sp. has a high potential for the production of secondary metabolites and degradation activity. This study aims to screen and characterize biodegradable Rhodococcus from Iranian ecosystems. The Rhodococcus isolates were recovered from 90 environmental samples and identified using conventional and molecular methods. The growth rate in the presence of pollutants and chromatography (high-performance liquid chromatography [HPLC]) was used to determine their biodegradation capability. A total of 13 Rhodococcus isolates were characterized from the cultured samples (14.5%) that belonged to seven species. The prevalent species were R. erythropolis (4 isolates; 30.8%), R. atherivorans (3 isolates; 23%), R. ruber (2 isolates; 15.4), and R. zopfii, R. phenolicus, R. equi and R. rhodochrous 1 isolate each. The result showed that these isolates could degrade and consume phenol, polycyclic aromatic hydrocarbon (PAH) and sulfate sodium. Our results showed that the Rhodococcus species have significant potential for bioremediation of diverse types of pollutants. Therefore, more studies are recommended for the biodegradation activity of Rhodococcus.