Search results for: globular clusters

Authors: Muntadher Sallal, Gareth Owenson, Mo Adda, Safa Shubbar

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Bitcoin is a digital currency based on a peer-to-peer network to propagate and verify transactions. Bitcoin is gaining wider adoption than any previous crypto-currency. However, the mechanism of peers randomly choosing logical neighbors without any knowledge about underlying physical topology can cause a delay overhead in information propagation, which makes the system vulnerable to double-spend attacks. Aiming at alleviating the propagation delay problem, this paper introduces proximity-aware extensions to the current Bitcoin protocol, named Master Node Based Clustering (MNBC). The ultimate purpose of the proposed protocol, that are based on how clusters are formulated and how nodes can define their membership, is to improve the information propagation delay in the Bitcoin network. In MNBC protocol, physical internet connectivity increases, as well as the number of hops between nodes, decreases through assigning nodes to be responsible for maintaining clusters based on physical internet proximity. We show, through simulations, that the proposed protocol defines better clustering structures that optimize the performance of the transaction propagation over the Bitcoin protocol. The evaluation of partition attacks in the MNBC protocol, as well as the Bitcoin network, was done in this paper. Evaluation results prove that even though the Bitcoin network is more resistant against the partitioning attack than the MNBC protocol, more resources are needed to be spent to split the network in the MNBC protocol, especially with a higher number of nodes.

Keywords: Bitcoin network, propagation delay, clustering, scalability

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Authors: Yue Hao

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COVID-19 vaccines not only protect individuals but society as a whole. In this case, having an understanding of the change and trend of vaccination conditions may shed some light on revising and making up-to-date policies regarding large-scale public health promotions and calls in order to lead and encourage the adoption of COVID-19 vaccines. However, vaccination status change over time and vary from place to place hidden patterns that were not fully explored in previous research. In our research, we took advantage of the spatial-temporal analytical methods in the domain of geographic information science and captured the spatial-temporal changes regarding COVID-19 vaccination status in the United States during 2020 and 2021. After conducting the emerging hot spots analysis on both the state level data of the US and county level data of California we found that: (1) at the macroscopic level, there is a continuously increasing trend of the vaccination rate in the US, but there is a variance on the spatial clusters at county level; (2) spatial hotspots and clusters with high vaccination amount over time were clustered around the west and east coast in regions like California and New York City where are densely populated with considerable economy conditions; (3) in terms of the growing trend of the daily vaccination among, Los Angeles County alone has very high statistics and dramatic increases over time. We hope that our findings can be valuable guidance for supporting future decision-making regarding vaccination policies as well as directing new research on relevant topics.

Keywords: COVID-19 vaccine, GIS, space time cube, spatial-temporal analysis

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Authors: Zeev Wiesman, Paula Berman, Nitzan Meiri, Charles Linder

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Supramolecular chemistry refers to the domain of chemistry beyond that of molecules and focuses on the chemical systems made up of a discrete number of assembled molecular sub units or components. Biodiesel components self arrangements is closely related/affect their physical properties in combustion systems and emission. Due to technological difficulties, knowledge regarding the molecular packing of FAMEs (biodiesel) in the liquid phase is limited. Spectral tools such as X-ray and NMR are known to provide evidences related to molecular structure organization. Recently, it was reported by our research group that using 1H Time Domain NMR methodology based on relaxation time and self diffusion coefficients, FAMEs clusters with different motilities can be accurately studied in the liquid phase. Head to head dimarization with quasi-smectic clusters organization, based on molecular motion analysis, was clearly demonstrated. These findings about the assembly/packing of the FAME components are directly associated with fluidity/viscosity of the biodiesel. Furthermore, these findings may provide information of micro/nano-particles that are formed in the delivery and injection system of various combustion systems (affected by thermodynamic conditions). Various relevant parameters to combustion such as: distillation/Liquid Gas phase transition, cetane number/ignition delay, shoot, oxidation/NOX emission maybe predicted. These data may open the window for further optimization of FAME/diesel mixture in terms of combustion and emission.

Keywords: supermolecular chemistry, FAMEs, liquid phase, fluidity, LF-NMR

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Authors: K. Yu Vlasova, M. A. Abakumov, H. Wishwarsao, M. Sokolsky, N. V. Nukolova, A. G. Majouga, Y. I. Golovin, N. L. Klyachko, A. V. Kabanov

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Introduction:Nowadays pharmaceutical medicine is aimed to create systems for combined therapy, diagnostic, drug delivery and controlled release of active molecules to target cells. Magnetic nanoparticles (MNPs) are used to achieve this aim. MNPs can be applied in molecular diagnostics, magnetic resonance imaging (T1/T2 contrast agents), drug delivery, hyperthermia and could improve therapeutic effect of drugs. The most common drug containers, containing MNPs, are liposomes, micelles and polymeric molecules bonded to the MNPs surface. Usually superparamagnetic nanoparticles are used (the general diameter is about 5-6 nm) and all effects of high frequency magnetic field (MF) application are based on Neel relaxation resulting in heating of surrounded media. In this work we try to develop a new method to improve drug release from MNPs under super low frequency MF. We suppose that under low frequency MF exposures the Brown’s relaxation dominates and MNPs rotation could occur leading to conformation changes and release of bioactive molecules immobilized on MNPs surface.The aim of this work was to synthesize different systems with active drug (biopolymers coated MNPs nanoclusters with immobilized enzymes and doxorubicin (Dox) loaded magnetic liposomes/micelles) and investigate the effect of super low frequency MF on these drug containers. Methods: We have synthesized MNPs of magnetite with magnetic core diameter 7-12 nm . The MNPs were coated with block-copolymer of polylysine and polyethylene glycol. Superoxide dismutase 1 (SOD1) was electrostatically adsorbed on the surface of the clusters. Liposomes were prepared as follow: MNPs, phosphatidylcholine and cholesterol were dispersed in chloroform, dried to get film and then dispersed in distillated water, sonicated. Dox was added to the solution, pH was adjusted to 7.4 and excess of drug was removed by centrifugation through 3 kDa filters. Results: Polylysine coated MNPs formed nanosized clusters (as observed by TEM) with intensity average diameter of 112±5 nm and zeta potential 12±3 mV. After low frequency AC MF exposure we observed change of immobilized enzyme activity and hydrodynamic size of clusters. We suppose that the biomolecules (enzymes) are released from the MNPs surface followed with additional aggregation of complexes at the MF in medium. Centrifugation of the nanosuspension after AC MF exposures resulted in increase of positive charge of clusters and change in enzyme concentration in comparison with control sample without MF, thus confirming desorption of negatively charged enzyme from the positively charged surface of MNPs. Dox loaded magnetic liposomes had average diameter of 160±8 nm and polydispersity index (PDI) 0.25±0.07. Liposomes were stable in DW and PBS at pH=7.4 at 370C during a week. After MF application (10 min of exposure, 50 Hz, 230 mT) diameter of liposomes raised to 190±10 nm and PDI was 0.38±0.05. We explain this by destroying and/or reorganization of lipid bilayer, that leads to changes in release of drug in comparison with control without MF exposure. Conclusion: A new application of low frequency AC MF for drug delivery and controlled drug release was shown. Investigation was supported by RSF-14-13-00731 grant, K1-2014-022 grant.

Keywords: magnetic nanoparticles, low frequency magnetic field, drug delivery, controlled drug release

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Authors: Harish Krishnamurthy, Anna Lafontant, Ren Yi

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Unidentified Flying Objects (UFOs) have been an interesting topic for most enthusiasts and hence people all over the United States report such findings online at the National UFO Report Center (NUFORC). Some of these reports are a hoax and among those that seem legitimate, our task is not to establish that these events confirm that they indeed are events related to flying objects from aliens in outer space. Rather, we intend to identify if the report was a hoax as was identified by the UFO database team with their existing curation criterion. However, the database provides a wealth of information that can be exploited to provide various analyses and insights such as social reporting, identifying real-time spatial events and much more. We perform analysis to localize these time-series geospatial events and correlate with known real-time events. This paper does not confirm any legitimacy of alien activity, but rather attempts to gather information from likely legitimate reports of UFOs by studying the online reports. These events happen in geospatial clusters and also are time-based. We look at cluster density and data visualization to search the space of various cluster realizations to decide best probable clusters that provide us information about the proximity of such activity. A random forest classifier is also presented that is used to identify true events and hoax events, using the best possible features available such as region, week, time-period and duration. Lastly, we show the performance of the scheme on various days and correlate with real-time events where one of the UFO reports strongly correlates to a missile test conducted in the United States.

Keywords: time-series clustering, feature extraction, hoax prediction, geospatial events

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Authors: Javed Mallick

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In metropolitan areas, rapid changes in land use and land cover (LULC) have ecological and environmental consequences. Saudi Arabia's cities have experienced tremendous urban growth since the 1990s, resulting in urban heat islands, groundwater depletion, air pollution, loss of ecosystem services, and so on. From 1990 to 2020, this study examines the variance and heterogeneity in land surface temperature (LST) caused by LULC changes in Abha-Khamis Mushyet, Saudi Arabia. LULC was mapped using the support vector machine (SVM). The mono-window algorithm was used to calculate the land surface temperature (LST). To identify LST clusters, the local indicator of spatial associations (LISA) model was applied to spatiotemporal LST maps. In addition, the parallel coordinate (PCP) method was used to investigate the relationship between LST clusters and urban biophysical variables as a proxy for LULC. According to LULC maps, urban areas increased by more than 330% between 1990 and 2018. Between 1990 and 2018, built-up areas had an 83.6% transitional probability. Furthermore, between 1990 and 2020, vegetation and agricultural land were converted into built-up areas at a rate of 17.9% and 21.8%, respectively. Uneven LULC changes in built-up areas result in more LST hotspots. LST hotspots were associated with high NDBI but not NDWI or NDVI. This study could assist policymakers in developing mitigation strategies for urban heat islands

Keywords: land use land cover mapping, land surface temperature, support vector machine, LISA model, parallel coordinate plot

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Authors: Salma El Hajjami, Jamal Malki, Alain Bouju, Mohammed Berrada

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With the expansion of machine learning and data mining in the context of Big Data analytics, the common problem that affects data is class imbalance. It refers to an imbalanced distribution of instances belonging to each class. This problem is present in many real world applications such as fraud detection, network intrusion detection, medical diagnostics, etc. In these cases, data instances labeled negatively are significantly more numerous than the instances labeled positively. When this difference is too large, the learning system may face difficulty when tackling this problem, since it is initially designed to work in relatively balanced class distribution scenarios. Another important problem, which usually accompanies these imbalanced data, is the overlapping instances between the two classes. It is commonly referred to as noise or overlapping data. In this article, we propose an approach called: One Side Behavioral Noise Reduction (OSBNR). This approach presents a way to deal with the problem of class imbalance in the presence of a high noise level. OSBNR is based on two steps. Firstly, a cluster analysis is applied to groups similar instances from the minority class into several behavior clusters. Secondly, we select and eliminate the instances of the majority class, considered as behavioral noise, which overlap with behavior clusters of the minority class. The results of experiments carried out on a representative public dataset confirm that the proposed approach is efficient for the treatment of class imbalances in the presence of noise.

Keywords: machine learning, imbalanced data, data mining, big data

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Authors: Nick Weir, Robert Stevens, Alan Hargreaves, Martin McGinnity, Chris Tinsley

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Hydrophobic materials have previously demonstrated the ability to elevate cell-cell interactions and promote the formation of neural networks whilst aligned nanofibers demonstrate the ability to induce extensive neurite outgrowth in an aligned manner. Hydrophobic materials typically elicit an immune response upon implantation and thus materials used for implantation are typically hydrophilic. Poly-L-lactic acid (PLLA) is a hydrophobic, non-immunogenic, FDA approved material that can be electrospun to form aligned nanofibers. Primary rat cortical neurons cultured for 10 days on aligned PLLA nanofibers formed 3D cell clusters, approximately 800 microns in diameter. Neurites that extended from these clusters were highly aligned due to the alignment of the nanofibers they were cultured upon and fasciculation was also evident. Plasma treatment of the PLLA nanofibers prior to seeding of cells significantly reduced the hydrophobicity and abolished the cluster formation and neurite fasciculation, whilst reducing the extent and directionality of neurite outgrowth; it is proposed that hydrophobicity induces the changes to cellular behaviors. Aligned PLLA nanofibers induced the formation of a structure that mimics the grey-white matter compartmentalization that is observed in vivo and thus represents a step forward in generating organoids or biomaterial-based implants. Upon implantation into the brain, the biomaterial architectures described here may provide a useful platform for both brain repair and brain remodeling initiatives.

Keywords: hydrophobicity, nanofibers, neurite fasciculation, neurite outgrowth, PLLA

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Authors: Vivek Vaishnav, Shamim Akhtar Ansari

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Teak (Tectona grandis L.f.) belonging to plant family Lamiaceae and the most commercialized timber species is endemic to South-Asia. The adaptive fitness of the species metapopulation was evaluated through its genetic differentiation and assessing the influence of geo-climatic conditions. 290 genotypes were sampled from 29 locations of its natural distribution and the genetic data was incorporated with geo-climatic parameters. Through Bayesian approach based analysis of 43 highly polymorphic ISSR markers, six homogeneous clusters (0.8% genetic variability) were identified. The six clusters were found with the various regimes of the temperature range, i.e., I - 9.10±1.35⁰C, II -6.35±0.21⁰C, III -12.21±0.43⁰C, IV - 10.8±1.06⁰C, V - 11.67±3.04⁰C, and VI - 12.35±0.21⁰C. The population had a very high percentage of LD (21.48%) among the amplified loci possibly due to experiencing restricted gene flow as well as co-adaptation and association of distant/diverse loci/alleles as a result of the stabilized climatic conditions and countless cycles of historical recombination events on a large geological timescale. The same possibly accounts for the narrow distribution of teak as a climax species in the tropical deciduous forests of the country. The regions of strong LD in teak genome significantly associated with climatic parameters also reflect that the species is tolerant to the wide regimes of the temperature range and may possibly withstand global warming and climate change in the coming millennium.

Keywords: Bayesian analysis, inter simple sequence repeat, linkage disequilibrium, marker-geoclimatic association

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Authors: Gysele Lima Ricci, Jose Miguel Rodriguez Anton

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Companies in the tourism sector need to achieve competitive advantages for their survival in the market. In this way, the models based on association, cooperation, complementarity, distribution, exchange and mutual assistance arise as a possibility of organizational development, taking as reference the concept of networks. Many companies seek to partner in local networks as clusters to act together and associate. The main objective of the present research is to identify the specificities of management and the practices of cooperation in the tourist destination of São Paulo - Brazil, and to propose a new management model with possible cluster of tourism. The empirical analysis was carried out in three phases. As a first phase, a research was made by the companies, associations and tourism organizations existing in São Paulo, analyzing the characteristics of their business. In the second phase, the management specificities and cooperation practice used in the tourist destination. And in the third phase, identifying the possible strengths and weaknesses that potential or potential tourist cluster could have, proposing the development of the management model of the same adapted to the needs of the companies, associations and organizations. As a main result, it has been identified that companies, associations and organizations could be looking for synergies with each other and collaborate through a Hiperred organizational structure, in which they share their knowledge, try to make the most of the collaboration and to benefit from three concepts: flexibility, learning and collaboration. Finally, it is concluded that, the proposed tourism cluster management model is viable for the development of tourism destinations because it makes it possible to strategically address agents which are responsible for public policies, as well as public and private companies and organizations in their strategies competitiveness and cooperation.

Keywords: cluster, management model, networks, tourism sector

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Authors: H. Beisch, J. Marx, S. Garlof, R. Shvets, I. I. Grygorchak, A. Kityk, B. Fiedler

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Carbon materials, especially three-dimensional carbon foams, show very high potential in the application as electrode material for energy storage systems such as batteries and supercapacitors with unique fast charging and discharging times. Regarding their high specific surface areas (SSA) high specific capacities can be reached. Globugraphite is a newly developed carbon foam with an interconnected globular carbon morphology. Especially, this foam has a statistically distributed hierarchical pore structure resulting from the manufacturing process based on sintered ceramic templates which are synthetized during a final chemical vapor deposition (CVD) process. For morphology characterization scanning electron (SEM) and transmission electron microscopy (TEM) is used. In addition, the SSA is carried out by nitrogen adsorption combined with the Brunauer–Emmett–Teller (BET) theory. Electrochemical measurements in organic and inorganic electrolyte provide high energy densities and power densities resulting from ion absorption by forming an electrochemical double layer. All values are summarized in a Ragone Diagram. Finally, power densities up to 833 W/kg and energy densities up to 48 Wh/kg could be achieved. The corresponding SSA is between 376 m²/g and 859 m²/g. For organic electrolyte a specific capacity of 71 F/g at a density of 20 mg/cm³ was achieved.

Keywords: BET, CVD process, electron microscopy, Ragone diagram

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Authors: Hubert Beisch, Janik Marx, Svenja Garlof, Roman Shvets, Ivan Grygorchak, Andriy Kityk, Bodo Fiedler

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Three-dimensional carbon materials can be used as electrode materials for energy storage systems such as batteries and supercapacitors. Fast charging and discharging times are realizable without reducing the performance due to aging processes. Furthermore high specific surface area (SSA) of three-dimensional carbon structures leads to high specific capacities. One newly developed carbon foam is Globugraphite. This interconnected globular carbon morphology with statistically distributed hierarchical pores is manufactured by a chemical vapor deposition (CVD) process from ceramic templates resulting from a sintering process. Via scanning electron (SEM) and transmission electron microscopy (TEM), the morphology is characterized. Moreover, the SSA was measured by the Brunauer–Emmett–Teller (BET) theory. Measurements of Globugraphite in an organic and inorganic electrolyte show high energy densities and power densities resulting from ion absorption by forming an electrochemical double layer. A comparison of the specific values is summarized in a Ragone diagram. Energy densities up to 48 Wh/kg and power densities to 833 W/kg could be achieved for an SSA from 376 m²/g to 859 m²/g. For organic electrolyte, a specific capacity of 100 F/g at a density of 20 mg/cm³ was achieved.

Keywords: BET, carbon foam, CVD process, electrochemical cell, Ragone diagram, SEM, TEM

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Authors: Li Wang, Dan Shu, Shiguang Pang, Lixiu Wang, Bing Xiang Yang, Qian Liu

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Background: Cancer is one of the most severe diseases in childhood; long-term treatment and its side effects significantly impact the patient's physical, psychological, social functioning and quality of life while also placing substantial physical and psychological burdens on caregivers and families. Family resilience is crucial for children with cancer, helping them cope better with the disease and supporting the family in facing challenges together. As a family-level variable, family resilience requires information from multiple family members. However, to our best knowledge, there is currently no research investigating family resilience from both the perspectives of pediatric cancer patients and their caregivers. Therefore, this study aims to investigate the family resilience and quality of life of pediatric cancer patients from a patient–caregiver dyadic perspective. Methods: A total of 149 dyads of patients diagnosed with pediatric cancer patients and their principal caregivers were recruited from oncology departments of 4 tertiary hospitals in Wuhan and Taiyuan, China. All participants completed questionnaires that identified their demographic and clinical characteristics as well as assessed their family resilience and quality of life for both the patients and their caregivers. K-means cluster analysis was used to identify different clusters of family resilience based on the reports from patients and caregivers. Multivariate logistic regression and linear regression are used to analyze the factors influencing family resilience and quality of life, as well as the relationship between the two. Results: Three clusters of family resilience were identified: a cluster of high family resilience (HR), a cluster of low family resilience (LR), and a cluster of discrepant family resilience (DR). Most (67.1%) families fell into the cluster with low resilience. Characteristics such as the types of caregivers perceived social support of the patient were different among the three clusters. Compared to the LR group, families where the mother is the caregiver and where the patient has high social support are more likely to be assigned to the HR. The quality of life for caregivers was consistently highest in the HR cluster and lowest in the LR cluster. The patient's quality of life is not related to family resilience. In the linear regression analysis of the patient's quality of life, patients who are the first-born have higher quality of life, while those living with their parents have lower quality of life. The participants' characteristics were not associated with the quality of life for caregivers. Conclusions: In most families, family resilience was low. Families with maternal caregivers and patients receiving high levels of social support are more inclined to be higher levels of family resilience. Family resilience was linked to the quality of life of caregivers of pediatric cancer patients. The clinical implications of this findings suggest that healthcare and social support organizations should prioritize and support the participation of mothers in caregiving responsibilities. Furthermore, they should assist families in accessing social support to enhance family resilience. This study also emphasizes the importance of promoting family resilience for enhancing family health and happiness, as well as improving the quality of life for caregivers.

Keywords: pediatric cancer, cluster analysis, family resilience, quality of life

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Authors: Yuriy A. Knirel

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Enteric bacteria Escherichia coli is the predominant facultative anaerobe of the colonic flora, and some specific serotypes are associated with enteritis, hemorrhagic colitis, and hemolytic uremic syndrome. Shigella spp. are human pathogens that cause diarrhea and bacillary dysentery (shigellosis). They are in effect E. coli with a specific mode of pathogenicity. Strains of Salmonella enterica are responsible for a food-borne infection (salmonellosis), and specific serotypes cause typhoid fever and paratyphoid fever. All these bacteria are closely related in respect to structure and genetics of the lipopolysaccharide, including the O-polysaccharide part (O‑antigen). Being exposed to the bacterial cell surface, the O antigen is subject to intense selection by the host immune system and bacteriophages giving rise to diverse O‑antigen forms and providing the basis for typing of bacteria. The O-antigen forms of many bacteria are unique, but some are structurally and genetically related to others. The sequenced O-antigen gene clusters between conserved galF and gnd genes were analyzed taking into account the O-antigen structures established by us and others for all S. enterica and Shigella and most E. coli O-serogroups. Multiple genetic mechanisms of diversification of the O-antigen forms, such as lateral gene transfer and mutations, were elucidated and are summarized in the present paper. They include acquisition or inactivation of genes for sugar synthesis or transfer or recombination of O-antigen gene clusters or their parts. The data obtained contribute to our understanding of the origins of the O‑antigen diversity, shed light on molecular evolutionary relationships between the O-antigens of enteric bacteria, and open a way for studies of the role of gene polymorphism in pathogenicity.

Keywords: enteric bacteria, O-antigen gene cluster, polysaccharide biosynthesis, polysaccharide structure

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Authors: Eder Amayuelas, Begoña Bazán, M. Karmele Urtiaga, Gotzone Barandika, María I. Arriortua

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Metal Organic Frameworks (MOFs) have attracted great interest in recent years, taking a lead role in the field of catalysis, drug delivery, sensors and absorption. In the past decade, promising results have been reported specifically in the field of adsorption, based on the topology and chemical features of this type of porous material. Thus, its application in industry and environment for the adsorption of pollutants is presented as a response to an increasingly important need. In this area, organic dyes are nowadays widely used in many industries including medicine, textile, leather, printing and plastics. The consequence of this fact is that dyes are present as emerging pollutants in soils and water where they remain for long periods of time due to their high stability, with a potential risk of toxicity in wildlife and in humans. On the other hand, the presence of iodine in soils, water and gas as a nuclear activity pollutant product or its extended use as a germicide is still a problem in many countries, which indicates the imperative need for its removal. In this context, this work presents the characterization as an adsorbent of the activated compound αMOP@Ei2-1 obtained from the already reported [Cu₂₄(m-BDC)₂₄(DMF)₂₀(H₂O)₄]•24DMF•40H₂O (MOP@Ei2-1), where m-BDC is the 1,3-benzenedicarboxylic ligand and DMF is N,N′-dimethylformamide. The structure of MOP@Ei2-1 consists of Cu24 clusters arranged in such a way that 12 paddle-wheels are connected through m-BDC ligands. The clusters exhibit an internal cavity where crystallization molecules of DMF and water are located. Adsorption of dyes and iodine as pollutant examples has been carried out, focusing attention on the kinetics of the rapid process.

Keywords: adsorption, organic dyes, iodine, metal organic frameworks

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Authors: Goksel Ezgi Guzey, Bihrat Onoz

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The scarcity of streamflow gauging stations and the increasing effects of global warming cause designing water management systems to be very difficult. This study is a significant contribution to assessing regional regression models for estimating streamflow. In this study, simulated meteorological data was related to the observed streamflow data from 1971 to 2020 for 33 stream gauging stations of the Euphrates-Tigris Basin. Ordinary least squares regression was used to predict flow for 2020-2100 with the simulated meteorological data. CORDEX- EURO and CORDEX-MENA domains were used with 0.11 and 0.22 grids, respectively, to estimate climate conditions under certain climate scenarios. Twelve meteorological variables simulated by two regional climate models, RCA4 and RegCM4, were used as independent variables in the ordinary least squares regression, where the observed streamflow was the dependent variable. The variability of streamflow was then calculated with 5-6 meteorological variables and watershed characteristics such as area and height prior to the application. Of the regression analysis of 31 stream gauging stations' data, the stations were subjected to a clustering analysis, which grouped the stations in two clusters in terms of their hydrometeorological properties. Two streamflow equations were found for the two clusters of stream gauging stations for every domain and every regional climate model, which increased the efficiency of streamflow estimation by a range of 10-15% for all the models. This study underlines the importance of homogeneity of a region in estimating streamflow not only in terms of the geographical location but also in terms of the meteorological characteristics of that region.

Keywords: hydrology, streamflow estimation, climate change, hydrologic modeling, HBV, hydropower

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Authors: Saravanan Govindaraju, Kyusik Yun

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The purpose of this study is to develop the chitosan doped curcumin gold cluster nanofiber for wound healing and skin cancer drug delivery applications. Chitosan is a typical marine polysaccharide composed of glucosamine and n-acetyl glucosamine biodegradable and biocompatible polymer. Curcumin is a natural bioactive molecule obtained from Curcuma longo, it mostly occurs in some Asian countries like India and China. It has naturally antioxidant, antimicrobial, wound healing and anticancer property. Due to this advantage, we prepared a combination of natural polymer chitosan with Curcumin and gold nanocluster nanofiber (CH-CUR-AuNCs nanofibers). The prepared nanofiber was characterized by using Fourier transform infrared spectroscopy (FT-IR), and scanning electron microscopy (SEM). Antibacterial studies were performed with E.coli and S.aureus. Antioxidant assay, drug release test, and cytotoxicity will be evaluated. Prepared nanofiber emits low intensity of red fluorescent. The FTIR confirm the presence of chitosan and Curcumin in the nanofiber. In vitro study clearly shows the antibacterial activity against the gram negative and gram positive bacteria. Particularly, synthesised nanofibers provide better antibacterial activity against gram negative than gram positive. Cytotoxicity study also provides better killing rate in cancer cell, biocompatible with normal cell. Prepared CH-CUR-AuNCs nanofibers provide the better killing rate to bacterial strains and cancer cells. Finally, prepared nanofiber can be possible to use for wound healing dressing, patch for skin cancer and other biomedical applications.

Keywords: curcumin, chitosan, gold clusters, nanofibers

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Authors: Beata Lachtara, Renata Szewczyk, Katarzyna Bielinska, Kinga Wieczorek, Jacek Osek

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Listeria monocytogenes is an important human and animal pathogen that causes foodborne outbreaks. The bacteria may be present in different types of food: cheese, raw vegetables, sliced meat products and vacuum-packed sausages, poultry, meat, fish. The most common method, which has been used for the investigation of genetic diversity of L. monocytogenes, is PFGE. This technique is reliable and reproducible and established as gold standard for typing of L. monocytogenes. The aim of the study was characterization by molecular serotyping and PFGE analysis of L. monocytogenes strains isolated from fresh fish and fish products in Poland. A total of 301 samples, including fresh fish (n = 129) and fish products (n = 172) were, collected between January 2014 and March 2016. The bacteria were detected using the ISO 11290-1 standard method. Molecular serotyping was performed with PCR. The isolates were tested with the PFGE method according to the protocol developed by the European Union Reference Laboratory for L. monocytogenes with some modifications. Based on the PFGE profiles, two dendrograms were generated for strains digested separately with two restriction enzymes: AscI and ApaI. Analysis of the fingerprint profiles was performed using Bionumerics software version 6.6 (Applied Maths, Belgium). The 95% of similarity was applied to differentiate the PFGE pulsotypes. The study revealed that 57 of 301 (18.9%) samples were positive for L. monocytogenes. The bacteria were identified in 29 (50.9%) ready-to-eat fish products and in 28 (49.1%) fresh fish. It was found that 40 (70.2%) strains were of serotype 1/2a, 14 (24.6%) 1/2b, two (4.3%) 4b and one (1.8%) 1/2c. Serotypes 1/2a, 1/2b, and 4b were presented with the same frequency in both categories of food, whereas serotype 1/2c was detected only in fresh fish. The PFGE analysis with AscI demonstrated 43 different pulsotypes; among them 33 (76.7%) were represented by only one strain. The remaining 10 profiles contained more than one isolate. Among them 8 pulsotypes comprised of two L. monocytogenes isolates, one profile of three isolates and one restriction type of 5 strains. In case of ApaI typing, the PFGE analysis showed 27 different pulsotypes including 17 (63.0%) types represented by only one strain. Ten (37.0%) clusters contained more than one strain among which four profiles covered two strains; three had three isolates, one with five strains, one with eight strains and one with ten isolates. It was observed that the isolates assigned to the same PFGE type were usually of the same serotype (1/2a or 1/2b). The majority of the clusters had strains of both sources (fresh fish and fish products) isolated at different time. Most of the strains grouped in one cluster of the AscI restriction was assigned to the same groups in ApaI investigation. In conclusion, PFGE used in the study showed a high genetic diversity among L. monocytogenes. The strains were grouped into varied clonal clusters, which may suggest different sources of contamination. The results demonstrated that 1/2a serotype was the most common among isolates from fresh fish and fish products in Poland.

Keywords: Listeria monocytogenes, molecular characteristic, PFGE, serotyping

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Authors: Shaima A. Al Mansoori

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Eco-cities have become part of the broader and universal discourse and embrace of sustainable communities. Given the ideals and ‘potential’ benefits of eco-cities for people, the environment and prosperity, hardly can an argument be made against the desirability of eco-cities. Yet, this paper posits that it is necessary for urban scholars, technocrats and policy makers to engage in discussions of the pragmatism of implementing the ideals of eco-cities, for example, from the political, budgetary, cultural and other dimensions. In the context of such discourse, this paper examines the feasibility of one of the cardinal principles and goals of eco-cities, which is the reduction or elimination of pollution through various creative and innovative initiatives, in the UAE. This paper contends and argues that, laudable and desirable as this goal is, it is a polylemma and, therefore, overly ambitious and practically unattainable in the UAE. The paper uses the mixed method research strategy, in which data is sourced from secondary and general sources through desktop research, from public records in governmental agencies, and from the conceptual academic and professional literature. Information from these sources will be used, first, to define and review pollution as a concept and multifaceted phenomenon with multidimensional impacts. Second, the paper will use society’s five goal clusters as a framework to identify key causes and impacts of pollution in the UAE. Third, the paper will identify and analyze specific public policies, programs and projects that make pollution in the UAE a polylemma. Fourth, the paper will argue that the phenomenal rates of population increase, urbanization, economic growth, consumerism and development in the UAE make pollution an inevitable product and burden that society must live with. This ‘reality’ makes the goal and desire of pollution-free cities pursuable but unattainable. The paper will conclude by identifying and advocating creative and innovative initiatives that can be taken by the various stakeholders in the country to reduce and mitigate pollution in the short- and long-term.

Keywords: goal clusters, pollution, polylemma, sustainable communities

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Authors: Nir Schreiber, Reuven Cohen, Simi Haber

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The Potts model has been widely explored in the literature for the last few decades. While many analytical and numerical results concern with the traditional two site interaction model in various geometries and dimensions, little is yet known about models where more than two spins simultaneously interact. We consider a ferromagnetic four site interaction Potts model on the square lattice (FFPS), where the four spins reside in the corners of an elementary square. Each spin can take an integer value 1,2,...,q. We write the partition function as a sum over clusters consisting of monochromatic faces. When the number of faces becomes large, tracing out spin configurations is equivalent to enumerating large lattice animals. It is known that the asymptotic number of animals with k faces is governed by λᵏ, with λ ≈ 4.0626. Based on this observation, systems with q < 4 and q > 4 exhibit a second and first order phase transitions, respectively. The transition nature of the q = 4 case is borderline. For any q, a critical giant component (GC) is formed. In the finite order case, GC is simple, while it is fractal when the transition is continuous. Using simple equilibrium arguments, we obtain a (zero order) bound on the transition point. It is claimed that this bound should apply for other lattices as well. Next, taking into account higher order sites contributions, the critical bound becomes tighter. Moreover, for q > 4, if corrections due to contributions from small clusters are negligible in the thermodynamic limit, the improved bound should be exact. The improved bound is used to relate the critical point to the finite correlation length. Our analytical predictions are confirmed by an extensive numerical study of FFPS, using the Wang-Landau method. In particular, the q=4 marginal case is supported by a very ambiguous pseudo-critical finite size behavior.

Keywords: entropic sampling, lattice animals, phase transitions, Potts model

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Authors: Bryan D. Llenarizas, Maria Carla F. Manzano

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The rapid growth of electricity demand has led to a pursuit of alternative energy sources with high power output and not harmful to the environment. The fuel cell is a device that generates electricity via chemical reactions between the fuel and oxidant. Fuel cells have been known for decades, but the development of high-power output and durability was still one of the drawbacks of this energy source. This study investigates the potential of layer-by-layer composite for fuel cell applications. A two-electrode electrochemical cell was used for the galvanostatic electrochemical deposition method to fabricate a Polypyrrole/rGO|Polypyrrole/ZnO layer-by-layer composite material for fuel cell applications. In the synthesis, the first layer comprised 0.1M pyrrole monomer and 1mg of rGO, while the second layer had 0.1M pyrrole monomer and variations of ZnO concentration ranging from 0.08M up to 0.12M. A constant current density of 8mA/cm² was applied for 1 hour in fabricating each layer. Scanning electron microscopy (SEM) for the fabricated LBL material shows a globular surface with white spots. These white spots are the ZnO particles confirmed by energy-dispersive X-ray spectroscopy, indicating a successful deposition of the second layer onto the first layer. The observed surface morphology was consistent for each variation of ZnO concentrations. AC measurements were conducted to obtain the AC resistance of the fabricated film. Results show a decrease in AC resistance as the concentration of ZnO increases.

Keywords: anode, composite material, electropolymerization, fuel cell, galvanostatic, polypyrrole

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Authors: Peng Hou

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Natural products produced from marine bacteria serve as an immense reservoir for anti-infective drugs and therapeutic agents. Nowadays, heterologous expression of gene clusters of interests has been widely adopted as an effective strategy for natural product discovery. Briefly, the heterologous expression flowchart would be: biosynthetic gene cluster identification, pathway construction and expression, and product detection. However, gene cluster capture using traditional Transformation-associated recombination (TAR) protocol is low-efficient (0.5% positive colony rate). To make things worse, most of these putative new natural products are only predicted by bioinformatics analysis such as antiSMASH, and their corresponding natural products biosynthetic pathways are either not expressed or expressed at very low levels under laboratory conditions. Those setbacks have inspired us to focus on seeking new technologies to efficiently edit and refractor of biosynthetic gene clusters. Recently, two cutting-edge techniques have attracted our attention - the CRISPR-Cas9 and Gibson Assembly. By now, we have tried to pretreat Brevibacillus laterosporus strain genomic DNA with CRISPR-Cas9 nucleases that specifically generated breaks near the gene cluster of interest. This trial resulted in an increase in the efficiency of gene cluster capture (9%). Moreover, using Gibson Assembly by adding/deleting certain operon and tailoring enzymes regardless of end compatibility, the silent construct (~80kb) has been successfully refactored into an active one, yielded a series of analogs expected. With the appearances of the novel molecular tools, we are confident to believe that development of a high throughput mature pipeline for DNA assembly, transformation, product isolation and identification would no longer be a daydream for marine natural product discovery.

Keywords: biosynthesis, CRISPR-Cas9, DNA assembly, refactor, TAR cloning

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Authors: Getachew Weldemichael, Sentayehu Alamerew, Leta Tulu, Gezahegn Berecha

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Coffee quality improvement program is becoming the focus of coffee research, as the world coffee consumption pattern shifted to high-quality coffee. However, there is limited information on the genetic variation of C. Arabica for quality improvement in potential specialty coffee growing areas of Ethiopia. Therefore, this experiment was conducted with the objectives of determining the magnitude of variation among 105 coffee accessions collected from east Wollega coffee growing areas and assessing correlations between the different coffee qualities attributes. It was conducted in RCRD with three replications. Data on green bean physical characters (shape and make, bean color and odor) and organoleptic cup quality traits (aromatic intensity, aromatic quality, acidity, astringency, bitterness, body, flavor, and overall standard of the liquor) were recorded. Analysis of variance, clustering, genetic divergence, principal component and correlation analysis was performed using SAS software. The result revealed that there were highly significant differences (P<0.01) among the accessions for all quality attributes except for odor and bitterness. Among the tested accessions, EW104 /09, EW101 /09, EW58/09, EW77/09, EW35/09, EW71/09, EW68/09, EW96 /09, EW83/09 and EW72/09 had the highest total coffee quality values (the sum of bean physical and cup quality attributes). These genotypes could serve as a source of genes for green bean physical characters and cup quality improvement in Arabica coffee. Furthermore, cluster analysis grouped the coffee accessions into five clusters with significant inter-cluster distances implying that there is moderate diversity among the accessions and crossing accessions from these divergent inter-clusters would result in hetrosis and recombinants in segregating generations. The principal component analysis revealed that the first three principal components with eigenvalues greater than unity accounted for 83.1% of the total variability due to the variation of nine quality attributes considered for PC analysis, indicating that all quality attributes equally contribute to a grouping of the accessions in different clusters. Organoleptic cup quality attributes showed positive and significant correlations both at the genotypic and phenotypic levels, demonstrating the possibility of simultaneous improvement of the traits. Path coefficient analysis revealed that acidity, flavor, and body had a high positive direct effect on overall cup quality, implying that these traits can be used as indirect criteria to improve overall coffee quality. Therefore, it was concluded that there is considerable variation among the accessions, which need to be properly conserved for future improvement of the coffee quality. However, the variability observed for quality attributes must be further verified using biochemical and molecular analysis.

Keywords: accessions, Coffea arabica, cluster analysis, correlation, principal component

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Authors: Manjula Weerasekera, Chris Sissons, Lisa Wong, Sally Anderson, Ann Holmes, Richard Cannon

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The aim of this study was to characterize bacterial population and yeasts in saliva by Polymerase chain reaction followed by denaturing gradient gel electrophoresis (PCR-DGGE) and measure yeast levels by culture. PCR-DGGE was performed to identify oral bacteria and yeasts in 24 saliva samples. DNA was extracted and used to generate DNA amplicons of the V2–V3 hypervariable region of the bacterial 16S rDNA gene using PCR. Further universal primers targeting the large subunit rDNA gene (25S-28S) of fungi were used to amplify yeasts present in human saliva. Resulting PCR products were subjected to denaturing gradient gel electrophoresis using Universal mutation detection system. DGGE bands were extracted and sequenced using Sanger method. A potential relationship was evaluated between groups of bacteria identified by cluster analysis of DGGE fingerprints with the yeast levels and with their diversity. Significant interpersonal variation of salivary microbiome was observed. Cluster and principal component analysis of the bacterial DGGE patterns yielded three significant major clusters, and outliers. Seventeen of the 24 (71%) saliva samples were yeast positive going up to 10³ cfu/mL. Predominately, C. albicans, and six other species of yeast were detected. The presence, amount and species of yeast showed no clear relationship to the bacterial clusters. Microbial community in saliva showed a significant variation between individuals. A lack of association between yeasts and the bacterial fingerprints in saliva suggests the significant ecological person-specific independence in highly complex oral biofilm systems under normal oral conditions.

Keywords: bacteria, denaturing gradient gel electrophoresis, oral biofilm, yeasts

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Authors: Vijay Kumar, Mack Moyo, Johannes Van Staden

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Lachenalia viridiflora is a critically endangered bulbous plant with high potential on the international floriculture market. In the present study, an efficient protocol for in vitro plantlet regeneration through somatic embryogenesis was developed. Embryogenic callus was established on Murashige and Skoog (MS) basal medium supplemented with various concentrations and combinations of picloram and thidiazuron (TDZ). A high number of SEs (28.5 ± 1.49) with at different developmental stages of somatic embryos (SEs: globular embryos, torpedo and cotyledon embryo with bipolar characteristics) was obtained on Murashige and Skoog (MS) (Murashige and Skoog 1962) medium with 2.5 μM picloram, and 1.0 μM TDZ. Histological and scanning electron microscopic (SEM) analysis confirmed the presence of somatic embryos. Mature somatic embryos germinated and developed into plantlets after 6 weeks on half/full strength MS medium. High plant regeneration frequency (91.11 %) was achieved on full-strength MS medium supplemented with 5 μM phloroglucinol (PG). Well-developed healthy plantlets were successfully acclimatized in the greenhouse with a survival rate of 80%. The result of this study is beneficial in the mass propagation of high-quality Lachenalia viridiflora clonal plants for the commercial horticultural market and also provides a platform for future genetic transformation studies on the plant.

Keywords: horticultural plant, Lachenalia viridiflora, phloroglucinol, somatic embryogenesis, thidiazuron

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Authors: Christopher Leung, Guillermo Becerril-Martinez

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Amyloidosis is a rare systemic disease where abnormal proteins invade various organs and impede their function. Occasionally, they can manifest in a solidary organ such as the heart, lung, and nervous systems; rarely do they manifest in the gallbladder. Diagnosis often requires biopsy of the affected area and histopathology shows deposition of abnormally folded globular proteins called amyloid proteins. This case presents a 69-year-old male with a 3-month history of RUQ pain, diarrhea and non-specific symptoms of tiredness, etc. On imaging, both his US and CT abdomen showed gallbladder wall thickening and pericholecystic fluid, which may represent acute cholecystitis with hypodense lesions around the gallbladder, possibly representing liver abscesses. Given his symptoms of abdominal pain and imaging findings, this gentleman eventually had a laparoscopic cholecystectomy showing a gangrenous gallbladder with a mass on the liver bed. On histopathology, it showed amorphous hyaline eosinophilic material, which Congo-stained confirmed amyloidosis. Amyloidosis explained his non-specific symptoms, he avoided further biopsy, and he was commenced immediately on Lenalidomide. Involvement of the gallbladder is extremely rare, with less than 30 cases around the world. Half of the cases are reported as primary amyloidosis. This case adds to the current literature regarding primary gallbladder amyloidosis. Importantly, this case highlights how laparoscopic cholecystectomy can help with the diagnosis of gallbladder amyloidosis.

Keywords: amyloidosis, cholecystitis, gangrenous cholecystitis, gallbladder, systemic amyloidosis

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Authors: M. Mohan, J. P. Roise, G. P. Catts

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Despite living in an era where conservation zones are de-facto the central element in any sustainable wildlife management strategy, we still find ourselves grappling with several pareto-optimal situations regarding resource allocation and area distribution for the same. In this paper, a multi-objective decision making (MODM) model is presented to answer the question of whether or not we can establish mutual relationships between these contradicting objectives. For our study, we considered a Red-cockaded woodpecker (Picoides borealis) habitat conservation scenario in the coastal plain of North Carolina, USA. Red-cockaded woodpecker (RCW) is a non-migratory territorial bird that excavates cavities in living pine trees for roosting and nesting. The RCW groups nest in an aggregation of cavity trees called ‘cluster’ and for our model we use the number of clusters to be established as a measure of evaluating the size of conservation zone required. The case study is formulated as a linear programming problem and the objective function optimises the Red-cockaded woodpecker clusters, carbon retention rate, biofuel, public safety and Net Present Value (NPV) of the forest. We studied the variation of individual objectives with respect to the amount of area available and plotted a two dimensional dynamic graph after establishing interrelations between the objectives. We further explore the concept of interdependency by integrating the MODM model with GIS, and derive a raster file representing carbon distribution from the existing forest dataset. Model results demonstrate the applicability of interdependency from both linear and spatial perspectives, and suggest that this approach holds immense potential for enhancing environmental investment decision making in future.

Keywords: conservation, interdependency, multi-objective decision making, red-cockaded woodpecker

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Authors: Getiye Dejenu Kibret, Daniel Demant, Andrew Hayen

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Introduction: In Ethiopia, more than half of newborn babies do not have access to Emergency Obstetric and Neonatal Care (EmONC) services. Understanding the effect of distance to health facilities on service use and neonatal survival is crucial to recommend policymakers and improve resource distribution. We aimed to investigate the effect of distance to health services on maternal service use and neonatal mortality. Methods: We implemented a data linkage method based on geographic coordinates and calculated straight-line (Euclidean) distances from the Ethiopian 2016 demographic and health survey clusters to the closest health facility. We computed the distance in ESRI ArcGIS Version 10.3 using the geographic coordinates of DHS clusters and health facilities. Generalised Structural Equation Modelling (GSEM) was used to estimate the effect of distance on neonatal mortality. Results: Poor geographic accessibility to health facilities affects maternal service usage and increases the risk of newborn mortality. For every ten kilometres (km) increase in distance to a health facility, the odds of neonatal mortality increased by 1.33% (95% CI: 1.06% to 1.67%). Distance also negatively affected antenatal care, facility delivery and postnatal counselling service use. Conclusions: A lack of geographical access to health facilities decreases the likelihood of newborns surviving their first month of life and affects health services use during pregnancy and immediately after birth. The study also showed that antenatal care use was positively associated with facility delivery service use and that both positively influenced postnatal care use, demonstrating the interconnectedness of the continuum of care for maternal and neonatal care services. Policymakers can leverage the findings from this study to improve accessibility barriers to health services.

Keywords: acessibility, distance, maternal health service, neonatal mortality

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Authors: Kasra Majbouri Yazdi, Adel Majbouri Yazdi, Saeid Khodayi, Jingyu Hou, Wanlei Zhou, Saeed Saedy

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Fake news and false information are big challenges of all types of media, especially social media. There is a lot of false information, fake likes, views and duplicated accounts as big social networks such as Facebook and Twitter admitted. Most information appearing on social media is doubtful and in some cases misleading. They need to be detected as soon as possible to avoid a negative impact on society. The dimensions of the fake news datasets are growing rapidly, so to obtain a better result of detecting false information with less computation time and complexity, the dimensions need to be reduced. One of the best techniques of reducing data size is using feature selection method. The aim of this technique is to choose a feature subset from the original set to improve the classification performance. In this paper, a feature selection method is proposed with the integration of K-means clustering and Support Vector Machine (SVM) approaches which work in four steps. First, the similarities between all features are calculated. Then, features are divided into several clusters. Next, the final feature set is selected from all clusters, and finally, fake news is classified based on the final feature subset using the SVM method. The proposed method was evaluated by comparing its performance with other state-of-the-art methods on several specific benchmark datasets and the outcome showed a better classification of false information for our work. The detection performance was improved in two aspects. On the one hand, the detection runtime process decreased, and on the other hand, the classification accuracy increased because of the elimination of redundant features and the reduction of datasets dimensions.

Keywords: clustering, fake news detection, feature selection, machine learning, social media, support vector machine

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Authors: Frodouard Minani

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Since last decade, wireless sensor networks (WSNs) have been used in many areas like health care, agriculture, defense, military, disaster hit areas and so on. Wireless Sensor Networks consist of a Base Station (BS) and more number of wireless sensors in order to monitor temperature, pressure, motion in different environment conditions. The key parameter that plays a major role in designing a protocol for Wireless Sensor Networks is energy efficiency which is a scarcest resource of sensor nodes and it determines the lifetime of sensor nodes. Maximizing sensor node’s lifetime is an important issue in the design of applications and protocols for Wireless Sensor Networks. Clustering sensor nodes mechanism is an effective topology control approach for helping to achieve the goal of this research. In this paper, the researcher presents an energy efficiency protocol to prolong the network lifetime based on Energy efficient clustering algorithm. The Low Energy Adaptive Clustering Hierarchy (LEACH) is a routing protocol for clusters which is used to lower the energy consumption and also to improve the lifetime of the Wireless Sensor Networks. Maximizing energy dissipation and network lifetime are important matters in the design of applications and protocols for wireless sensor networks. Proposed system is to maximize the lifetime of the Wireless Sensor Networks by choosing the farthest cluster head (CH) instead of the closest CH and forming the cluster by considering the following parameter metrics such as Node’s density, residual-energy and distance between clusters (inter-cluster distance). In this paper, comparisons between the proposed protocol and comparative protocols in different scenarios have been done and the simulation results showed that the proposed protocol performs well over other comparative protocols in various scenarios.

Keywords: base station, clustering algorithm, energy efficient, sensors, wireless sensor networks

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