Search results for: biological molecular networks

Authors: Dong Zhao

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Abstract—Extensive research on obtaining applicable room temperature superconductors meets the major barrier, and the record Tc of 135 K achieved via cuprate has been idling for decades. Even though, the accomplishment of higher Tc than the cuprate was made through pressurizing certain compounds composed of light elements, such as for the LaH10 and for the metallic hydrogen. Room temperature superconductivity under ambient pressure is still the preferred approach and is believed to be the ultimate solution for many applications. While racing to find the breakthrough method to achieve this room temperature Tc milestone in superconducting research, a report stated a discovery of a possible high-temperature superconductor, i.e., the thorium sulfide ThS. Apparently, ThS’s Tc can be at room temperature or even higher. This is because ThS revealed an unusual property of the ‘coexistence of high electrical conductivity and diamagnetism’. Noticed that this property of coexistence of high electrical conductivity and diamagnetism is in line with superconductors, meaning ThS is also at its superconducting state. Surprisingly, ThS owns the property of superconductivity at least at room temperature and under atmosphere pressure. Further study of the ThS’s electrical and magnetic properties in comparison with thorium di-iodide ThI2 concluded its molecular configuration as [Th4+(e-)2]S. This means the ThS’s cation is composed of a [Th4+(e-)2]2+ cation core. It is noticed that this cation core is built by an oxidation state +4 of thorium atom plus an electron pair on this thorium atom that resulted in an oxidation state +2 of this [Th4+(e-)2]2+ cation core. This special construction of [Th4+(e-)2]2+ cation core may lead to the ThS’s room temperature superconductivity because of this characteristic electron lone pair residing on the thorium atom. Since the study of thorium chemistry was carried out in the period of before 1970s. the exploration about ThS’s possible room temperature superconductivity would require resynthesizing ThS. This re-preparation of ThS will provide the sample and enable professionals to verify the ThS’s room temperature superconductivity. Regrettably, the current regulation prevents almost everyone from getting access to thorium metal or thorium compounds due to the radioactive nature of thorium-232 (Th-232), even though the radioactive level of Th-232 is extremely low with its half-life of 14.05 billion years. Consequently, further confirmation of ThS’s high-temperature superconductivity through experiments will be impossible unless the use of corresponding thorium metal and related thorium compounds can be deregulated. This deregulation would allow researchers to obtain the necessary starting materials for the study of ThS. Hopefully, the confirmation of ThS’s room temperature superconductivity can not only establish a method to obtain applicable superconductors but also to pave the way for fully understanding the mechanism of superconductivity.

Keywords: co-existence of high electrical conductivity and diamagnetism, electron pairing and electron lone pair, room temperature superconductivity, the special molecular configuration of thorium sulfide ThS

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Authors: Ashiq Hussain, Mahwash Hussain, Zeenat Parveen

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Now a days the demand for broadband service has increased. Due to which the researchers are trying to find a solution to provide a large amount of service. There is a shortage of bandwidth because of the use of downloading video, voice and data. One of the solutions to overcome this shortage of bandwidth is to provide the communication system with passive optical components. We have increased the data rate in this system. From experimental results we have concluded that the quality factor has increased by adding passive optical networks.

Keywords: WDM-PON, optical fiber, BER, Q-factor, eye diagram

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Authors: Luminita Marin, Dalila Belei, Carmen Dumea

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Aggregation induced emission (AIE) is an intriguing optical phenomenon recently evidenced by Tang and his co-workers, for which aggregation works constructively in the improving of light emission. The AIE challenging phenomenon is quite opposite to the notorious aggregation caused quenching (ACQ) of light emission in the condensed phase, and comes in line with requirements of photonic and optoelectronic devices which need solid state emissive substrates. This paper reports a series of ten new aggregation induced emission (AIE) low molecular weight compounds based on triazole and pyridine-N-oxide heterocyclic units bonded by short flexible chains, obtained by a „click” chemistry reaction. The compounds present extremely weak luminescence in solution but strong light emission in solid state. To distinguish the influence of the crystallinity degree on the emission efficiency, the photophysical properties were explored by UV-vis and photoluminescence spectroscopy in solution, water suspension, amorphous and crystalline films. On the other hand, the compound morphology of the up mentioned states was monitored by dynamic light scattering, scanning electron microscopy, atomic force microscopy and polarized light microscopy methods. To further understand the structural design – photophysical properties relationship, single crystal X-ray diffraction on some understudy compounds was performed too. The UV-vis absorption spectra of the triazole water suspensions indicated a typical behaviour for nanoparticle formation, while the photoluminescence spectra revealed an emission intensity enhancement up to 921-fold higher of the crystalline films compared to solutions, clearly indicating an AIE behaviour. The compounds have the tendency to aggregate forming nano- and micro- crystals in shape of rose-like and fibres. The crystals integrity is kept due to the strong lateral intermolecular forces, while the absence of face-to-face forces explains the enhanced luminescence in crystalline state, in which the intramolecular rotations are restricted. The studied flexible triazoles draw attention to a new structural design in which small biologically friendly luminophore units are linked together by small flexible chains. This design enlarges the variety of the AIE luminogens to the flexible molecules, guiding further efforts in development of new AIE structures for appropriate applications, the biological ones being especially envisaged.

Keywords: aggregation induced emission, pyridine-N-oxide, triazole

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Authors: Muhammad Arif Khan, Haroon Idrees, Imran Aziz, Sidra Mushtaq

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Social platforms like online discussion and mailing groups are well aligned with academic as well as professional learning spaces. Professional communities are increasingly moving to online forums for sharing and capturing the intellectual abilities. This study investigated dynamics of social connectivity of yahoo mailing groups of Pakistani Library and Information Science (LIS) professionals using Graph Theory technique. Design/Methodology: Social Network Analysis is the increasingly concerned domain for scientists in identifying whether people grow together through online social interaction or, whether they just reflect connectivity. We have conducted a longitudinal study using Network Graph Theory technique to analyze the large data-set of email communication. The data was collected from three yahoo mailing groups using network analysis software over a period of six months i.e. January to June 2016. Findings of the network analysis were reviewed through focus group discussion with LIS experts and selected respondents of the study. Data were analyzed in Microsoft Excel and network diagrams were visualized using NodeXL and ORA-Net Scene package. Findings: Findings demonstrate that professionals and students exhibit intellectual growth the more they get tied within a network by interacting and participating in communication through online forums. The study reports on dynamics of the large network by visualizing the email correspondence among group members in a network consisting vertices (members) and edges (randomized correspondence). The model pair wise relationship between group members was illustrated to show characteristics, reasons, and strength of ties. Connectivity of nodes illustrated the frequency of communication among group members through examining node coupling, diffusion of networks, and node clustering has been demonstrated in-depth. Network analysis was found to be a useful technique in investigating the dynamics of the large network.

Keywords: emailing networks, network graph theory, online social platforms, yahoo mailing groups

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Authors: Ahmed G. Mahgoub, Dahlia H. Hafez, Mostafa A. Abu Kiefa

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The Cone Penetration Test (CPT) is a common in-situ test which generally investigates a much greater volume of soil more quickly than possible from sampling and laboratory tests. Therefore, it has the potential to realize both cost savings and assessment of soil properties rapidly and continuously. The principle objective of this paper is to demonstrate the feasibility and efficiency of using artificial neural networks (ANNs) to predict the soil angle of internal friction (Φ) and the soil modulus of elasticity (E) from CPT results considering the uncertainties and non-linearities of the soil. In addition, ANNs are used to study the influence of different parameters and recommend which parameters should be included as input parameters to improve the prediction. Neural networks discover relationships in the input data sets through the iterative presentation of the data and intrinsic mapping characteristics of neural topologies. General Regression Neural Network (GRNN) is one of the powerful neural network architectures which is utilized in this study. A large amount of field and experimental data including CPT results, plate load tests, direct shear box, grain size distribution and calculated data of overburden pressure was obtained from a large project in the United Arab Emirates. This data was used for the training and the validation of the neural network. A comparison was made between the obtained results from the ANN's approach, and some common traditional correlations that predict Φ and E from CPT results with respect to the actual results of the collected data. The results show that the ANN is a very powerful tool. Very good agreement was obtained between estimated results from ANN and actual measured results with comparison to other correlations available in the literature. The study recommends some easily available parameters that should be included in the estimation of the soil properties to improve the prediction models. It is shown that the use of friction ration in the estimation of Φ and the use of fines content in the estimation of E considerable improve the prediction models.

Keywords: angle of internal friction, cone penetrating test, general regression neural network, soil modulus of elasticity

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Authors: Kalyan S. Ghosh, B. L. Dhananjaya

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Snake bite causes fatal injuries in multi-organs and even many deaths due to several adverse physiological effects of various phospholipases (PLA2s) present in snake venom. Though these PLA2s bear highly homologues sequences and also structure but exhibit a different extent of those pharmacological effects. In this study, we have explored the difference in the neurotoxicity of two PLA2 namely PLA2-V, PLA2-VIIIa present in the venom from Vipera russellii. Bioinformatics studies on sequences of these two proteins along with detailed structural comparison enable us to explore the differences unambiguously. The identification of the residues involved in neurotoxicity will further lead towards proper designing of inhibitors against such killing effects of the venom.

Keywords: electrostatic potential, homology modeling, hydrophobicity, neurotoxicity, Phospholipase A2

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Authors: Olalekan Lawrence Ojo

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Designing microwave terrestrial propagation networks requires a thorough evaluation of the severity of multipath fading, especially at frequencies below 10 GHz. In nations like Nigeria, without a large enough databases to support the existing empirical models, the mistakes in the prediction technique intended for the evaluation may be severe. The need for higher bandwidth for various satellite applications makes the investigation of the effects of radio refractivity, fading due to multipath, and Geoclimatic factors on satellite propagation links more important. One of the key elements to take into account for the best functioning of microwave frequencies is the clear air effects. This work has taken into account the geographical distribution of radio refractivity and fades depth over a number of stations in Nigeria. Data from five locations in Nigeria—Akure, Enugu, Jos, Minna, and Sokoto—based on five-year (2017–2021) measurement methods of atmospheric pressure, relative, and humidity temperature—at two levels (ground surface and 100 m heights)—are studied to deduced their effects on signals propagated through a µwave communication links. The assessments included considerations for µwave communication systems as well as the impacts of the dry and wet components of radio refractivity, the effects of the fade depth at various frequencies, and a 20 km link distance. The results demonstrate that the percentage occurrence of the dry terms dominated the radio refractivity constituent at the surface level, contributing a minimum of about 78% and a maximum of about 92%, while at heights of 100 meters, the percentage occurrence of the dry terms dominated the radio refractivity constituent, contributing a minimum of about 79% and a maximum of about 92%. The spatial distribution reveals that, regardless of height, the country's tropical rainforest (TRF) and freshwater swampy mangrove (FWSM) regions reported the greatest values of radio refractivity. The statistical estimate shows that fading values can differ by as much as 1.5 dB, especially near the TRF and FWSM coastlines, even during clear air conditions. The current findings will be helpful for budgeting Earth-space microwave links, particularly for the rollout of Nigeria's 5G and 6G projected microcellular networks.

Keywords: fade depth, geoclimatic factor, refractivity, refractivity gradient

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Authors: Safwan Mawlood Hussien

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Internet of Things (IoT) is a promising technology has received considerable attention in different fields such as health, industry, defence, and agro, etc. Due to the limitation capacity of computing, storage, and communication, IoT objects are more vulnerable to attacks. Many solutions have been proposed to solve security issues, such as key management using symmetric-key ciphers. This study provides a scalable group distribution key management based on ECcryptography; with less transmitted messages The method has been validated through simulations in OMNeT++.

Keywords: elliptic curves, Diffie–Hellman, discrete logarithm problem, secure key exchange, WSN security, IoT security, smart-agro

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Authors: Renata Swislocka, Grzegorz Swiderski, Agata Jablonska-Trypuc, Wlodzimierz Lewandowski

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Forming a complex of a phenolic compound with a metal not only alters the physicochemical properties of the ligand (including increase in stability or changes in lipophilicity), but also its biological activity, including antioxidant, antimicrobial and many others. As part of our previous projects, we examined the physicochemical and antimicrobial properties of phenolic acids and their complexes with metals naturally occurring in foods. Previously we studied the complexes of manganese(II), copper(II), cadmium(II) and alkali metals with ferulic, caffeic and p-coumaric acids. In the framework of this study, the physicochemical and biological properties of cicoric acid, its sodium salt, and complexes with copper and zinc were investigated. Cichoric acid is a derivative of both caffeic acid and tartaric acid. It has first been isolated from Cichorium intybus (chicory) but also it occurs in significant amounts in Echinacea, particularly E. purpurea, dandelion leaves, basil, lemon balm and in aquatic plants, including algae and sea grasses. For the study of spectroscopic and biological properties of cicoric acid, its sodium salt, and complexes with zinc and copper a variety of methods were used. Studies of antioxidant properties were carried out in relation to selected stable radicals (method of reduction of DPPH and reduction of FRAP). As a result, the structure and spectroscopic properties of cicoric acid and its complexes with selected metals in the solid state and in the solutions were defined. The IR and Raman spectra of cicoric acid displayed a number of bands that were derived from vibrations of caffeic and tartaric acids moieties. At 1746 and 1716 cm-1 the bands assigned to the vibrations of the carbonyl group of tartaric acid occurred. In the spectra of metal complexes with cichoric these bands disappeared what indicated that metal ion was coordinated by the carboxylic groups of tartaric acid. In the spectra of the sodium salt, a characteristic wide-band vibrations of carboxylate anion occurred. In the spectra of cicoric acid and its salt and complexes, a number of bands derived from the vibrations of the aromatic ring (caffeic acid) were assigned. Upon metal-ligand attachment, the changes in the values of the wavenumbers of these bands occurred. The impact of metals on the antioxidant properties of cicoric acid was also examined. Cichoric acid has a high antioxidant potential. Complexation by metals (zinc, copper) did not significantly affect its antioxidant capacity. The work was supported by the National Science Centre, Poland (grant no. 2015/17/B/NZ9/03581).

Keywords: chicoric acid, metal complexes, natural antioxidant, phenolic acids

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Authors: Alaa Eddien Abdallah, Bajes Yousef Alskarnah

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Ant colony based routing algorithms are known to grantee the packet delivery, but they suffer from the huge overhead of control messages which are needed to discover the route. In this paper we utilize the network nodes positions to group the nodes in connected clusters. We use clusters-heads only on forwarding the route discovery control messages. Our simulations proved that the new algorithm has decreased the overhead dramatically without affecting the delivery rate.

Keywords: ad-hoc network, MANET, ant colony routing, position based routing

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Authors: Billel Kenidra, Mohamed Benmohammed

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Data mining technique used in the field of clustering is a subject of active research and assists in biological pattern recognition and extraction of new knowledge from raw data. Clustering means the act of partitioning an unlabeled dataset into groups of similar objects. Each group, called a cluster, consists of objects that are similar between themselves and dissimilar to objects of other groups. Several clustering methods are based on partitional clustering. This category attempts to directly decompose the dataset into a set of disjoint clusters leading to an integer number of clusters that optimizes a given criterion function. The criterion function may emphasize a local or a global structure of the data, and its optimization is an iterative relocation procedure. The K-Means algorithm is one of the most widely used partitional clustering techniques. Since K-Means is extremely sensitive to the initial choice of centers and a poor choice of centers may lead to a local optimum that is quite inferior to the global optimum, we propose a strategy to initiate K-Means centers. The improved K-Means algorithm is compared with the original K-Means, and the results prove how the efficiency has been significantly improved.

Keywords: microarray data mining, biological pattern recognition, partitional clustering, k-means algorithm, centroid initialization

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Authors: Nigatu Tadesse, Li Juan, Liuhong Ming

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Gastric cancer (GC) is the fifth most common and fourth deadly cancer in the world with limited treatment options at late advanced stage in which surgical therapy is not recommended with chemotherapy remain as the mainstay of treatment. However, the occurrence of chemoresistance as well as intera-tumoral and inter-tumoral heterogeneity of response to targeted and immunotherapy underlined a clear unmet treatment need in gastroenterology. Several molecular and cellular alterations ascribed for chemo resistance in GC including cancer stem cells (CSC) and tumor microenvironment (TME) remodeling. Cancer cells including CSC bears higher metabolic demand and major changes in TME involves alterations of gut microbiota interacting with nutrients metabolism. Metabolic upregulation in lipids, carbohydrates, amino acids, fatty acids biosynthesis pathways identified as a common hall mark in GC. Metabolic addiction to methionine metabolism occurs in many cancer cells to promote the biosynthesis of S-Adenosylmethionine (SAM), a universal methyl donor molecule for high rate of transmethylation in GC and promote cell proliferation. Targeting methionine metabolism found to promotes chemo-sensitivity with treatment non-heterogeneity. Methionine restriction (MR) promoted the arrest of cell cycle at S/G2 phase and enhanced downregulation of GC cells resistance to apoptosis (including ferroptosis), which suggests the potential of synergy with chemotherapies acting at S-phase of the cell cycle as well as inducing cell apoptosis. Accumulated evidences showed both the biogenesis as well as intracellular metabolism of exogenous methionine could be safe and effective target for therapy either alone or in combination with chemotherapies. This review article provides an over view of the upregulation in methionine biosynthesis pathway and the molecular signaling through the PI3K/Akt/mTOR-c-MYC axis to promote metabolic reprograming through activating the expression of L-type aminoacid-1 (LAT1) transporter and overexpression of Methionine adenosyltransferase 2A(MAT2A) for intercellular metabolic conversion of exogenous methionine to SAM in GC, and the potential of targeting with novel therapeutic agents such as methioninase (METase), Methionine adenosyltransferase 2A (MAT2A), c-MYC, methyl like transferase 16 (METTL16) inhibitors that are currently under clinical trial development stages and future perspectives.

Keywords: gastric cancer, methionine metabolism, pi3k/akt/mtorc1-c-myc axis, gut microbiota, MAT2A, c-MYC, METTL16, methioninase

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Authors: Nouf M. Al-Ourfi, A. S. Bashammakh, M. S. El-Shahawi

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The redox behavior of dianabol steroid (DS) on Nafion Multiwalled Carbon nano -tubes (MWCNT) composite film modified glassy carbon electrode (GCE) in various buffer solutions was studied using cyclic voltammetry (CV) and differential pulse- adsorptive cathodic stripping voltammetry (DP-CSV) and successfully compared with the results at non modified bare GCE. The Nafion-MWCNT composite film modified GCE exhibited the best electrochemical response among the two electrodes for the electro reduction of DS that was inferred from the EIS, CV and DP-CSV. The modified sensor showed a sensitive, stable and linear response in the concentration range of 5 – 100 nM with a detection limit of 0.08 nM. The selectivity of the proposed sensor was assessed in the presence of high concentration of major interfering species. The analytical application of the sensor for the quantification of DS in pharmaceutical formulations and biological fluids (urine) was determined and the results demonstrated acceptable recovery and RSD of 5%. Statistical treatment of the results of the proposed method revealed no significant differences in the accuracy and precision. The relative standard deviations for five measurements of 50 and 300 ng mL−1 of DS were 3.9 % and 1.0 %, respectively.

Keywords: dianabol steroid, determination, modified GCE, urine

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Authors: Diana M. Torres, Anngie K. Hernandez, Andrea Villareal, Magda R. Gomez, Sadao Kobayashi

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Colombian Garlic crops exhibited mild mosaic, yellow stripes, and deformation. This group of symptoms suggested a viral infection. Several viruses belonging to the genera Potyvirus, Carlavirus and Allexivirus are known to infect garlic and lower their yield worldwide, but in Colombia, there are no studies of viral infections in this crop, only leek yellow stripe virus (LYSV) has been reported to our best knowledge. In Colombia, there are no management strategies for viral diseases in garlic because of the lack of information about viral infections on this crop, which is reflected in (i) high prevalence of viral related symptoms in garlic fields and (ii) high dispersal rate. For these reasons, the purpose of the present study was to evaluate the viral status of garlic in Colombia, which can represent a major threat on garlic yield and quality for this country 55 symptomatic leaf samples were collected for virus detection by RT-PCR and mechanical inoculation. Total RNA isolated from infected samples were subjected to RT-PCR with primers 1-OYDV-G/2-OYDV-G for Onion yellow dwarf virus (OYDV) (expected size 774pb), 1LYSV/2LYSV for LYSV (expected size 1000pb), SLV 7044/SLV 8004 for Shallot latent virus (SLV) (expected size 960pb), GCL-N30/GCL-C40 for Garlic common latent virus (GCLV) (expected size 481pb) and EF1F/EF1R for internal control (expected size 358pb). GCLV, SLV, and LYSV were detected in infected samples; in 95.6% of the analyzed samples was detected at least one of the viruses. GCLV and SLV were detected in single infection with low prevalence (9.3% and 7.4%, respectively). Garlic generally becomes coinfected with several types of viruses. Four viral complexes were identified: three double infection (64% of analyzed samples) and one triple infection (15%). The most frequent viral complex was SLV + GCLV infecting 48.1% of the samples. The other double complexes identified had a prevalence of 7% (GCLV + LYSV and SLV + LYSV) and 5.6% of the samples were free from these viruses. Mechanical transmission experiments were set up using leaf tissues of collected samples from infected fields, different test plants were assessed to know the host range, but it was restricted to C. quinoa, confirming the presence of detected viruses which have limited host range and were detected in C. quinoa by RT-PCR. The results of molecular and biological tests confirm the presence of SLV, LYSV, and GCLV; this is the first report of SLV and LYSV in garlic plants in Colombia, which can represent a serious threat for this crop in this country.

Keywords: SLV, GCLV, LYSV, leek yellow stripe virus, Allium sativum

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Authors: Paola Leon, Hugo Garcia, Adan Leon, Samuel Munoz

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The enhanced oil recovery by steam injection was considered a process that only generated physical recovery mechanisms. However, there is evidence of the occurrence of a series of chemical reactions, which are called aquathermolysis, which generates hydrogen sulfide, carbon dioxide, methane, and lower molecular weight hydrocarbons. These reactions can be favored by the addition of a catalyst during steam injection; in this way, it is possible to generate the original oil in situ upgrading through the production increase of molecules of lower molecular weight. This additional effect could increase the oil recovery factor and reduce costs in transport and refining stages. Therefore, this research has focused on the experimental evaluation of the catalytic aquathermolysis on a Colombian heavy oil with 12,8°API. The effects of three different catalysts, reaction time, and temperature were evaluated in a batch microreactor. The changes in the Colombian heavy oil were quantified through nuclear magnetic resonance 1H-NMR. The relaxation times interpretation and the absorption intensity allowed to identify the distribution of the functional groups in the base oil and upgraded oils. Additionally, the average number of aliphatic carbons in alkyl chains, the number of substituted rings, and the aromaticity factor were established as average structural parameters in order to simplify the samples' compositional analysis. The first experimental stage proved that each catalyst develops a different reaction mechanism. The aromaticity factor has an increasing order of the salts used: Mo > Fe > Ni. However, the upgraded oil obtained with iron naphthenate tends to form a higher content of mono-aromatic and lower content of poly-aromatic compounds. On the other hand, the results obtained from the second phase of experiments suggest that the upgraded oils have a smaller difference in the length of alkyl chains in the range of 240º to 270°C. This parameter has lower values at 300°C, which indicates that the alkylation or cleavage reactions of alkyl chains govern at higher reaction temperatures. The presence of condensation reactions is supported by the behavior of the aromaticity factor and the bridge carbons production between aromatic rings (RCH₂). Finally, it is observed that there is a greater dispersion in the aliphatic hydrogens, which indicates that the alkyl chains have a greater reactivity compared to the aromatic structures.

Keywords: catalyst, upgrading, aquathermolysis, steam

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Authors: Mohsen Shirani, Micaela Demichela

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Food supply chain is one of the most complex supply chain networks due to its perishable nature and customer oriented products, and food safety is the major concern for this industry. IT system could help to minimize the production and consumption of unsafe food by controlling and monitoring the entire system. However, there have been many issues in adoption of IT system in this industry specifically within SMEs sector. With this regard, this study presents a novel approach to use IT and tractability systems in the food supply chain, using application of RFID and central database.

Keywords: food supply chain, IT system, safety, SME

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Authors: Benslimane Marwa, Benabbas-Sahki Ilham

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Spiders play an important role in agroecosystems due to their great abundance. They are considered a valuable group of invertebrates in agricultural land. They are predators of insects harmful to crops, but their use in biological control requires in-depth research on their ecology. During our study, we counted a total of 768 spiders, which we were able to identify and classify into 14 families over a period between March 2021 and October of the same year. This study aims to compare a station subjected to agricultural practices, including the spreading of herbicides, with another station subjected to the same practices but without the use of phytosanitary products. The inventory shows a strong dominance of the Gnaphosidae family (75.8%). This result affirms that the proliferation of this family is very favorable to the knowledge of the fruits by limiting the populations of aphids infesting the plot, which can therefore be proposed for biological control. The comparative study of the populations of spiders in the stations studied shows the negative effect of agricultural practices on the species richness and abundance of these species; as for the diversity, this one is only slightly affected. Finally, we can note that the effects of herbicides did not cause a significant imbalance in this agroecosystem, unlike plowing, which showed harmful consequences on spiders.

Keywords: spiders, predator, species richness, herbicides, agricultural practices

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Authors: Zafer Yüce, Paşa Yayla, Alev Taşkın

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There are heaps of analytical methods to estimate the crack growth life of a component. Soft computing methods have an increasing trend in predicting fatigue life. Their ability to build complex relationships and capability to handle huge amounts of data are motivating researchers and industry professionals to employ them for challenging problems. This study focuses on soft computing methods, especially random forest regressors and artificial neural networks with hyperparameter optimization algorithms such as grid search and random grid search, to estimate the crack growth life of an aircraft wing splice joint under variable amplitude loading. TensorFlow and Scikit-learn libraries of Python are used to build the machine learning models for this study. The material considered in this work is 7050-T7451 aluminum, which is commonly preferred as a structural element in the aerospace industry, and regarding the crack type; corner crack is used. A finite element model is built for the joint to calculate fastener loads and stresses on the structure. Since finite element model results are validated with analytical calculations, findings of the finite element model are fed to AFGROW software to calculate analytical crack growth lives. Based on Fighter Aircraft Loading Standard for Fatigue (FALSTAFF), 90 unique fatigue loading spectra are developed for various load levels, and then, these spectrums are utilized as inputs to the artificial neural network and random forest regression models for predicting crack growth life. Finally, the crack growth life predictions of the machine learning models are compared with analytical calculations. According to the findings, a good correlation is observed between analytical and predicted crack growth lives.

Keywords: aircraft, fatigue, joint, life, optimization, prediction.

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Authors: Armin Nabaei, M. Omair Ahmad, M. N. S. Swamy

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Many facial expression and emotion recognition methods in the traditional approaches of using LDA, PCA, and EBGM have been proposed. In recent years deep learning models have provided a unique platform addressing by automatically extracting the features for the detection of facial expression and emotions. However, deep networks require large training datasets to extract automatic features effectively. In this work, we propose an efficient emotion detection algorithm using face images when only small datasets are available for training. We design a deep network whose feature extraction capability is enhanced by utilizing several parallel modules between the input and output of the network, each focusing on the extraction of different types of coarse features with fined grained details to break the symmetry of produced information. In fact, we leverage long range dependencies, which is one of the main drawback of CNNs. We develop this work by introducing a Dynamic Soft-Margin SoftMax.The conventional SoftMax suffers from reaching to gold labels very soon, which take the model to over-fitting. Because it’s not able to determine adequately discriminant feature vectors for some variant class labels. We reduced the risk of over-fitting by using a dynamic shape of input tensor instead of static in SoftMax layer with specifying a desired Soft- Margin. In fact, it acts as a controller to how hard the model should work to push dissimilar embedding vectors apart. For the proposed Categorical Loss, by the objective of compacting the same class labels and separating different class labels in the normalized log domain.We select penalty for those predictions with high divergence from ground-truth labels.So, we shorten correct feature vectors and enlarge false prediction tensors, it means we assign more weights for those classes with conjunction to each other (namely, “hard labels to learn”). By doing this work, we constrain the model to generate more discriminate feature vectors for variant class labels. Finally, for the proposed optimizer, our focus is on solving weak convergence of Adam optimizer for a non-convex problem. Our noteworthy optimizer is working by an alternative updating gradient procedure with an exponential weighted moving average function for faster convergence and exploiting a weight decay method to help drastically reducing the learning rate near optima to reach the dominant local minimum. We demonstrate the superiority of our proposed work by surpassing the first rank of three widely used Facial Expression Recognition datasets with 93.30% on FER-2013, and 16% improvement compare to the first rank after 10 years, reaching to 90.73% on RAF-DB, and 100% k-fold average accuracy for CK+ dataset, and shown to provide a top performance to that provided by other networks, which require much larger training datasets.

Keywords: computer vision, facial expression recognition, machine learning, algorithms, depp learning, neural networks

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Authors: Kristin Prentice, Carri Hand

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As the Canadian population ages and chronic health conditions continue to escalate, older adults will require various types of housing, such as long term care or retirement homes. Moving to a new home may require a change in leisure activities and social networks, which could be challenging to maintain identity and create a sense of home. Leisure has been known to help older adults maintain or increase their quality of life and life satisfaction and may help older adults in moving to new homes. Sense of home and identity within older adults' transitions to new homes are concepts that may also relate to leisure engagement. Literature is scant regarding the role of leisure in older adults moving to new homes and how the sense of home and identity inter-relate. This study aims to explore how leisure may play a role in older adults' transitioning to new homes, including how sense of home and identity inter-relate. An ethnographic approach will be used to understand the culture of older adults transitioning to new homes. This study will involve older adults who have recently relocated to a mid-sized city in Ontario, Canada. The study will focus on the older adult’s interactions with and connections to their home environment through leisure. Data collection will take place via video-conferencing and will include a narrative interview and two other interviews to discuss an activity diary of leisure engagement pre and post move and mental maps to capture spaces where participants engaged in leisure. Participants will be encouraged to share photographs of leisure engagement taken inside and outside their home to help understand the social spaces the participants refer to in their activity diaries and mental maps. Older adults attempt to adjust to their new homes by maintaining their identity, developing a sense of home through creating attachment to place, and maintaining social networks, all of which have been linked to engaging in leisure. This research will provide insight into the role of leisure in this transition process and the extent that the home and community can contribute to aiding their transition to the new home. This research will contribute to existing literature on the inter-relationships of leisure, sense of home, and identity and how they relate to older adults moving to new homes. This research also has potential for influencing policy and practice for meeting the housing needs of older adults.

Keywords: leisure, older adults, transition, identity

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Authors: N. Amraoui, D. Hammoutene

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We have performed a theoretical study using dispersion-corrected Density Functional Methods to evaluate a variety of artificial nucleobases as candidates for metal-mediated Hoogsteen-type base pairs. We focus on A-M-T Hoogsteen-type base pair with M=Co(II), Ru(I), Ni(I). All calculations are performed using (ADF 09) program. Metal-mediated Hoogsteen-type base pairs are studied as drug candidates, their geometry optimizations are performed at ZORA/TZ2P/BLYP-D level. The molecular geometries and different energies as total energies, coordination energies, Pauli interactions, orbital interactions and electrostatic energies are determined.

Keywords: chemistry, biology, density functional method, orbital interactions

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Authors: R. Rezaeipour, A. R. Mehrabi

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Recent increase of the DGs and microgrids in distribution systems, disturbs the tradition structure of the system. Coordination between protection devices in such a system becomes the concern of the network operators. This paper presents a new method for fault location detection in the active distribution networks, independent of the fault type or its resistance. The method uses synchronized voltage and current measurements at the interconnection of DG units and is able to adapt to changes in the topology of the system. The method has been tested on a 38-bus distribution system, with very encouraging results.

Keywords: fault location detection, active distribution system, micro grids, network operators

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Authors: El Mahdi Barrah, Said Safi, Abdessamad Malaoui

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In this paper, we present an algorithm for reconstruction from incomplete 2D scans for tifinagh characters. This algorithm is based on using correlation between the lost block and its neighbors. This system proposed contains three main parts: pre-processing, features extraction and recognition. In the first step, we construct a database of tifinagh characters. In the second step, we will apply “shape analysis algorithm”. In classification part, we will use Neural Network. The simulation results demonstrate that the proposed method give good results.

Keywords: Tifinagh character recognition, neural networks, local cost computation, ANN

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Authors: Roberto Cabezas H

Abstract:

The current work shows the methodology developed to create narrative lighting spaces for the multimedia performance piece 'cluster: the vanished paradise.' This empirical research is focused on exploring unconventional roles for machines in subjective creative processes, by delving into the semantics of data and machine intelligence algorithms in hybrid technological, creative contexts to expand epistemic domains trough human-machine cooperation. The creative process in scenic and performing arts is guided mostly by intuition; from that idea, we developed an approach to embed collective intuition in computational creative systems, by joining the properties of Generative Adversarial Networks (GAN’s) and Fuzzy Clustering based on a semi-supervised data creation and analysis pipeline. The model makes use of GAN’s to learn from phenomenological data (data generated from experience with lighting scenography) and algorithmic design data (augmented data by procedural design methods), fuzzy logic clustering is then applied to artificially created data from GAN’s to define narrative transitions built on membership index; this process allowed for the creation of simple and complex spaces with expressive capabilities based on position and light intensity as the parameters to guide the narrative. Hybridization comes not only from the human-machine symbiosis but also on the integration of different techniques for the implementation of the aided design system. Machine intelligence tools as proposed in this work are well suited to redefine collaborative creation by learning to express and expand a conglomerate of ideas and a wide range of opinions for the creation of sensory experiences. We found in GAN’s and Fuzzy Logic an ideal tool to develop new computational models based on interaction, learning, emotion and imagination to expand the traditional algorithmic model of computation.

Keywords: fuzzy clustering, generative adversarial networks, human-machine cooperation, hybrid collective data, multimedia performance

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Authors: Ali Oztuna, Meral Sarper, Deniz Torun, Fatma Bayrakdar, Selcuk Kilic, Mehmet Baysallar

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Bacillus anthracis is one of the biological agents most likely to be used in case of bioterrorist attack as well as being the cause of anthrax. The bacterium's major virulence factors are the anthrax toxins and an antiphagocytic polyglutamic capsule. TEM8 (ANTXR1) and CMG2 (ANTXR2) are ubiquitously expressed type I transmembrane proteins, and ANTXR2 is the major receptor for anthrax toxins. MicroRNAs are 21-24 bp small noncoding RNAs that regulate gene expression by base pairing with the 3' UTR (untranslated regions) of their target mRNAs resulting in mRNA degradation and/or translational repression. MicroRNAs contribute to regulation of most biological processes and influence numerous pathological states like infectious disease. In this study, post-exposure (toxins) protective effect of the hsa-miR-124-3p against Bacillus anthracis was examined. In this context, i) THP-1 and U937 cells were differentiated to MΦ macrophage, ii) miRNA transfection efficiencies were evaluated by flow cytometry and qPCR, iii) protection against Bacillus anthracis toxins were investigated by XTT, cAMP ELISA and MEK2 cleavage assays. Acknowledgements: This work was supported by the Scientific and Technological Research Council of Turkey (TUBITAK) under Grant SBAG-218S467.

Keywords: ANTXR2, hsa-miR-124-3p, MΦ macrophage, THP-1, U937

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Authors: A. Cittadino, P. Gantes, C. Coviella, M. Casset, A. Sanchez Caro

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Three currently active landfills receive the waste from Buenos Aires city and the Great Buenos Aires suburbs. One of the first landfills to receive solid waste from this area was located in Villa Dominico, some 7 km south from Buenos Aires City. With an area of some 750 ha, including riparian habitats, divided into 14 cells, it received solid wastes from June 1979 through February 2004. In December 2010, a biological monitoring program was set up by CEAMSE and Universidad Nacional de Lujan, still operational to date. The aim of the monitoring program is to assess the state of several biological groups within the landfill and to follow their dynamics overtime in order to identify if any, early signs of damage the landfill activities might have over the biota present. Bird and rodent populations, aquatic and terrestrial invertebrates’ populations, cells vegetation coverage, and surrounding areas vegetation coverage and main composition are followed by quarterly samplings. Bird species richness and abundance were estimated by observation over walk transects on each environment. A total of 74 different species of birds were identified. Species richness and diversity were high for both riparian surrounding areas and within the landfill. Several grassland -typical of the 'Pampa'- bird species were found within the landfill, as well as some migratory and endangered bird species. Sherman and Tomahawk traps are set overnight for small mammal sampling. Rodent populations are just above detection limits, and the few specimens captured belong mainly to species common to rural areas, instead of city-dwelling species. The two marsupial species present in the region were captured on occasions. Aquatic macroinvertebrates were sampled on a watercourse upstream and downstream the outlet of the landfill’s wastewater treatment plant and are used to follow water quality using biological indices. Water quality ranged between weak and severe pollution; benthic invertebrates sampled before and after the landfill, show no significant differences in water quality using the IBMWP index. Insect biota from yellow sticky cards and pitfall traps showed over 90 different morphospecies, with Shannon diversity index running from 1.9 to 3.9, strongly affected by the season. An easy-to-perform non-expert demandant method was used to assess vegetation coverage. Two scales of determination are utilized: field observation (1 m resolution), and Google Earth images (that allow for a better than 5 m resolution). Over the eight year period of the study, vegetation coverage over the landfill cells run from a low 83% to 100% on different cells, with an average between 95 to 99% for the entire landfill depending on seasonality. Surrounding area vegetation showed almost 100% coverage during the entire period, with an average density from 2 to 6 species per sq meter and no signs of leachate damaged vegetation.

Keywords: biological indicators, biota monitoring, landfill species diversity, waste management

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Authors: Evan Lowhorn, Rocio Alba-Flores

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The purpose of this work is to develop a method for classifying hand signals and using the output in a drone control algorithm. To achieve this, methods based on Convolutional Neural Networks (CNN) were applied. CNN's are a subset of deep learning, which allows grid-like inputs to be processed and passed through a neural network to be trained for classification. This type of neural network allows for classification via imaging, which is less intrusive than previous methods using biosensors, such as EMG sensors. Classification CNN's operate purely from the pixel values in an image; therefore they can be used without additional exteroceptive sensors. A development bench was constructed using a desktop computer connected to a high-definition webcam mounted on a scissor arm. This allowed the camera to be pointed downwards at the desk to provide a constant solid background for the dataset and a clear detection area for the user. A MATLAB script was created to automate dataset image capture at the development bench and save the images to the desktop. This allowed the user to create their own dataset of 12,000 images within three hours. These images were evenly distributed among seven classes. The defined classes include forward, backward, left, right, idle, and land. The drone has a popular flip function which was also included as an additional class. To simplify control, the corresponding hand signals chosen were the numerical hand signs for one through five for movements, a fist for land, and the universal “ok” sign for the flip command. Transfer learning with PyTorch (Python) was performed using a pre-trained 18-layer residual learning network (ResNet-18) to retrain the network for custom classification. An algorithm was created to interpret the classification and send encoded messages to a Ryze Tello drone over its 2.4 GHz Wi-Fi connection. The drone’s movements were performed in half-meter distance increments at a constant speed. When combined with the drone control algorithm, the classification performed as desired with negligible latency when compared to the delay in the drone’s movement commands.

Keywords: classification, computer vision, convolutional neural networks, drone control

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Authors: Yew Mun Yip, Dawei Zhang

Abstract:

Proteins are the biological machinery that executes specific vital functions in every cell of the human body by folding into their 3D structures. When a protein misfolds from its native structure, the machinery will malfunction and lead to misfolding diseases. Although in vitro experiments are able to conclude that the mutations of the amino acid sequence lead to incorrectly folded protein structures, these experiments are unable to decipher the folding process. Therefore, molecular dynamic (MD) simulations are employed to simulate the folding process so that our improved understanding of the folding process will enable us to contemplate better treatments for misfolding diseases. MD simulations make use of force fields to simulate the folding process of peptides. Secondary structures are formed via the hydrogen bonds formed between the backbone atoms (C, O, N, H). It is important that the hydrogen bond energy computed during the MD simulation is accurate in order to direct the folding process to the native structure. Since the atoms involved in a hydrogen bond possess very dissimilar electronegativities, the more electronegative atom will attract greater electron density from the less electronegative atom towards itself. This is known as the polarization effect. Since the polarization effect changes the electron density of the two atoms in close proximity, the atomic charges of the two atoms should also vary based on the strength of the polarization effect. However, the fixed atomic charge scheme in force fields does not account for the polarization effect. In this study, we introduce the polarized structure-specific backbone charge (PSBC) model. The PSBC model accounts for the polarization effect in MD simulation by updating the atomic charges of the backbone hydrogen bond atoms according to equations derived between the amount of charge transferred to the atom and the length of the hydrogen bond, which are calculated from quantum-mechanical calculations. Compared to other polarizable models, the PSBC model does not require quantum-mechanical calculations of the peptide simulated at every time-step of the simulation and maintains the dynamic update of atomic charges, thereby reducing the computational cost and time while accounting for the polarization effect dynamically at the same time. The PSBC model is applied to two different β-peptides, namely the Beta3s/GS peptide, a de novo designed three-stranded β-sheet whose structure is folded in vitro and studied by NMR, and the trpzip peptides, a double-stranded β-sheet where a correlation is found between the type of amino acids that constitute the β-turn and the β-propensity.

Keywords: hydrogen bond, polarization effect, protein folding, PSBC

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Authors: P. V. Pantyukhov, T. V. Monakhova, A. A. Popov

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The paper studies the diffusion of low molecular weight components from vegetable fillers into polyethylene matrix during the preparation of biocomposites. In order to identify the diffusible substances a model experiment used where the hexadecane acted as a model of polyethylene. It was determined that polyphenolic compounds and chlorophyll penetrate from vegetable fillers to hexadecane to the maximum extent. There was found a correlation between the amount of polyphenolic compounds diffusible from the fillers to hexadecane and thermal oxidation kinetics of real biocomposites based on polyethylene and vegetable fillers. Thus, it has been assumed the diffusion of polyphenols and chlorophyll from vegetable fillers into polyethylene matrix during the preparation of biocomposites.

Keywords: biocomposite, composite, diffusion, polyethylene, vegetable filler

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Authors: Ying Li, Yan Li

Abstract:

A new algorithm for single hidden layer feedforward neural networks (SLFN), Orthogonal Basis Extreme Learning (OBEL) algorithm, is proposed and the algorithm derivation is given in the paper. The algorithm can decide both the NNs parameters and the neuron number of hidden layer(s) during training while providing extreme fast learning speed. It will provide a practical way to develop NNs. The simulation results of function approximation showed that the algorithm is effective and feasible with good accuracy and adaptability.

Keywords: neural network, orthogonal basis extreme learning, function approximation

Procedia PDF Downloads 522