Miracle-dz/UniFAR-FTUs huggingface dataset:
MICROBIAL COMMUNITY AND VIBRIO PARAHAEMOLYTICUS POPULATION DYNAMICS IN RELAYED OYSTERS

The CDC estimates that 45,000 people are sickened each year by foodborne Vibrio parahaemolyticus in the United States. Filter-feeding bivalve shellfish, such as oysters, are routinely inhabited by human pathogenic V. parahaemolyticus and there currently is not a contaminant management process that effectively reduces concentrations of V. parahaemolyticus in oysters. The transplanting of V. parahaemolyticus -laden oysters to an area with low concentrations or no V. parahaemolyticus, called oyster relay, is one reduction strategy that holds promise for treating live oysters. A key consideration for effective strategies to reduce Vibrio spp. in shellfish is the influence of microbiota in natural seawater. Our aim for this study was to identify taxa shifts in the microbial composition of oyster and water samples during relay that correlated with the reduction of V. parahaemolyticus. We hypothesize that changes in bacterial taxa within the oyster microbiome occur during relay and influence the reduction of V. parahaemolyticus in relayed oysters. Oysters with varying concentrations of V. parahaemolyticus were evident from relay experiments carried out in a local body of water with elevated salinity and low concentrations of V. parahaemolyticus over 4 consecutive years. Overall, V. parahaemolyticus levels were reduced during 14-day relay in 9 of the 14 monthly trials to target reduction levels (<100 V. parahaemolyticus>/g). Sequence analysis of the 16S rRNA gene from relayed oyster tissue and the associated water samples unveiled that the composition of oyster microbial communities shifts during relay. We determined that oyster and water taxa profiles are dissimilar while harvest and relay waters were similar in overall taxa composition, even though there was also evidence of some taxa differences that may have been influential in reducing V. parahaemolyticus concentrations during the 14-day relay. Oyster samples from relay experiments in years that successfully reduced V. parahaemolyticus concentrations had consistent, similar taxa patterns compared to different and inconsistent patterns for 2013 when relay was not successful. Interspecies competition experiments informed by these analyses suggested one potential mechanistic explanation (competition) for why relaying to higher salinity water reduces V. parahaemolyticus concentrations. Oyster microbiome competition may aid in developing a consistent approach for reducing V. parahaemolyticus in oysters to reduce the risk of illness for oyster consumers.
Plant hydraulic conductivity determines photosynthesis in rice under PEG-induced drought stress

Photosynthesis (A) plays a key role in maintaining plant carbon balance, but it is sensitive to drought. Both A and plant hydraulic conductivity (Kplant) decrease under water deficit. It is not clearly whether the declined Kplant is more related to root or leaf, whether the decreased A is related to Kplant and/or leaf hydraulic conductivity (Kleaf) and diffusive alone or both diffusive and metabolic impairments decreased A. Two drought-tolerant (DW) contrasting rice genotypes were used to explore the relationship of A, Kplant and Kleaf under PEG induced drought stress (PEG-DS). The results showed that photosynthesis related parameters of A, stomatal conductance (gs), transpiration rate (Tr), maximum Rubisco carboxylation rate (Vcmax), maximum electron transport rate (Jmax), carboxylation efficiency (CE), Kleaf, Kplant and xylem sap flow rate (XSFR) were all decreased significantly under PEG-DS. These decreases were more severe in DW-sensitive genotype IR64 than DW-tolerant genotype Hanyou-3. However, both intercellular CO2 concentration (Ci) and CO2 concentration inside chloroplasts (Cc) were prominently increased in IR64 rather than in Hanyou-3 under PEG-DS. In addition, both gs and gm (mesophyll conductance to CO2) were strongly positively correlated with A (R=0.98 & 0.71). Photosynthesis of both genotypes were increased with increasing Ci under each treatment. Furthermore, A and gs were significantly correlated with Kplant (R=0.94 & 0.96) but not with Kleaf, and Kplant was not related to Kleaf. Kplant rather than Kleaf determines photosynthesis in rice under drought conditions, which was mainly attributed to Kplant decreases the stomatal conductance and ultimately lead to decrease in photosynthesis.
Influencing Children: Limitations of the Computer-Human-Interactive Persuasive Systems in Developing Societies

: The phenomenon of product/business failure, as well as lack of environmental sustainability and learning limitations, is fast becoming a recurrent ‘disease’ for investors, designers, design sponsors and education policy makers in many developing countries with poor persuasiveness contributing a large quota to such failures. This has greatly hampered the education, poverty alleviation and developmental efforts of the governments of such societies. In a bid to curb this negative trend, children, who are major influencers in product purchase behaviours of adults, have been targeted specifically by persuasive designers, in an effort to both educate and adopt them as means of reaching the larger populace. However, most researches in current persuasive system designs are limited to the information communication/management technology or computerized environments. These systems are technology/internet-driven and many potential users, in reality, in the developing world, unlike the rest of the world is often made to believe, do not have open access to such systems. Unfortunately, the effectiveness of any persuasive system is dependent on its accessibility to its user(s). Technological backwardness (often concealed behind ostentatious self-deceptive facades) has led to the poor persuasiveness of local persuasive systems and products in the third worlds. Therefore, adopting a mixed method for establishing the factor(s) limiting the efficiency of the computer/electronic-human interaction persuasive systems (CHIPS) in South-West Nigeria (N=900), this study established the need to adopt more of the product/entity-human interaction persuasive system (PEHIPS) as an effective alternative for third world countries as, based on the study outcomes, the CHIPS proved less relatively effective in comparison to PEHIPS in rural regions. It however recommends the alternating adoption of a combination of both computerized and entity/product driven systems for the purpose of optimizing persuasive effectiveness in developing worlds.
Practical isogeometric shape optimization: parametrization by means of regularization

Shape optimization based on isogeometric analysis (IGA) has gained popularity in recent years. Performing shape optimization directly over parameters defining the computer-aided design (CAD) geometry, such as the control points of a spline parametrization, opens up the prospect of seamless integration of a shape optimization step into the CAD workflow. One of the challenges when using IGA for shape optimization is that of maintaining a valid geometry parametrization of the interior of the domain during an optimization process, as the shape of the boundary is altered by an optimization algorithm. Existing methods impose constraints on the Jacobian of the parametrization, to guarantee that the parametrization remains valid. The number of such validity constraints quickly becomes intractably large, especially when 3D shape optimization problems are considered. An alternative, and arguably simpler, approach is to formulate the isogeometric shape optimization problem in terms of both the boundary and the interior control points. To ensure a geometric parametrization of sufficient quality, a regularization term, such as the Winslow functional, is added to the objective function of the shape optimization problem. We illustrate the performance of these methods on the optimal design problem of electromagnetic reflectors and compare their performance. Both methods are implemented for multipatch geometries, using the IGA library G+Smo and the optimization library Ipopt. We find that the second approach performs comparably to a state-of-the-art method with respect to both the quality of the found solutions and computational time, while its performance in our experience is more robust for coarse discretizations.
Spatial patterns of tree and shrub biomass in a deciduous forest using leaf-off and leaf-on lidar

Understanding patterns of aboveground carbon storage across forest types is increasingly important as managers adapt to threats of global change. We combined field measures of aboveground biomass with lidar to model fine-scale biomass in deciduous forests located in two watersheds; one watershed was underlain by sandstone and the other by shale. We measured tree and shrub biomass across three topographic positions for both watersheds and analyzed biomass using mixed models. The watershed underlain by shale had 60% more aboveground biomass than the sandstone watershed. Although spatial patterns of biomass were different across watersheds, both had higher (between about 40% and 55%) biomass values at the toe-slope position than at the ridge-top position. To model fine-scale spatial patterns of biomass, we tested the effectiveness of leaf-on and leaf-off lidar combined with topographic metrics to develop a spatially explicit random forest model of tree and shrub biomass across both watersheds. Leaf-on variables were more important for modeling shrub biomass, while leaf-off variables were more effective at modeling tree biomass. Our model of tree and shrub biomass reflects the distribution of biomass across both watersheds at a fine scale and highlights the potential of abiotic factors such as topography and bedrock to affect carbon storage.
Diversity of Bioaerosols in Selected Rooms of Two Schools and Antibiotic Resistance of Isolated Staphylococcal Strains (Bydgoszcz, Poland): A Case Study

The present study is aimed at evaluating microbiological air pollution in libraries, cafeterias and selected classrooms of two schools in Bydgoszcz city, northern Poland and determining the antibiotic resistance of Staphylococcal strains isolated from the indoor air. One of the investigated schools (School A) is located in the very center of the city, in the vicinity of a park, among old houses and stone-lined streets, while the other (School B), among modern residential buildings, close to a street with heavy traffic. In each school, air samples were collected in the morning, always from all three sampling sites, using the MAS-100 sampler. Selective growth media were used for bacteria and mold isolation and quantifying analysis. The antibiotic resistance of the isolated mannitol-positive staphylococci was assessed using the disc diffusion method in accordance with EUCAST recommendations. The highest mean concentration of heterotrophic bacteria was recorded in the cafeterias: 884 CFU m−3 in School A and 1906 CFU m−3 in School B. Molds were the most abundant in the library and cafeteria in School B, where their average concentration exceeded 300 CFU m−3. Cladosporium and Penicillium species prevailed, while Fusarium, Acremonium and Aspergillus were less abundant. Airborne mannitol-positive staphylococci were recorded at low concentrations, ranging from 6 to 11 CFU m−3 on average. According to the taxonomic analysis, Staphylococcus aureus isolates were the most abundant in both schools, followed by S. xylosus, S. haemolyticus and S. saprophyticus. The antibiograms indicated that resistance to erythromycin was common in 62.5% of the isolated staphylococcal strains. Levofloxacin and gentamicin were the most effective antibiotics. No multidrug-resistant strains were identified.
Limited-Budget Formation Control for High-Order Linear Swarm Systems with Fix Topologies

This paper discusses limited-budget time-varying formation design and analysis problems for a high-order linear swarm system with a fixed communication topology. Firstly, the communication topology among agents is modeled as an undirected and connected graph, and a new formation control protocol with an energy integral term is proposed to realize formation control and to guarantee the practical energy assumption is less than the limited energy budget. Then, by the matrix inequality tool, sufficient conditions for limited-budget formation design and analysis are proposed, respectively, which are scalable and checkable since they are independent of the number of agents of a swarm system and can be transformed into linear matrix inequality constraints. Moreover, an explicit expression of the formation center function is given, which contains the formation function part and the cooperative state part and is not associated with the derivatives of the formation functions. Finally, a numerical simulation is shown to demonstrate the effectiveness of theoretical results.
Self‐Assembly of Mechanoplasmonic Bacterial Cellulose–Metal Nanoparticle Composites

Nanocomposites of metal nanoparticles (NPs) and bacterial nanocellulose (BC) enable fabrication of soft and biocompatible materials for optical, catalytic, electronic, and biomedical applications. Current BC–NP nanocomposites are typically prepared by in situ synthesis of the NPs or electrostatic adsorption of surface functionalized NPs, which limits possibilities to control and tune NP size, shape, concentration, and surface chemistry and influences the properties and performance of the materials. Here a self‐assembly strategy is described for fabrication of complex and well‐defined BC–NP composites using colloidal gold and silver NPs of different sizes, shapes, and concentrations. The self‐assembly process results in nanocomposites with distinct biophysical and optical properties. In addition to antibacterial materials and materials with excellent senor performance, materials with unique mechanoplasmonic properties are developed. The homogenous incorporation of plasmonic gold NPs in the BC enables extensive modulation of the optical properties by mechanical stimuli. Compression gives rise to near‐field coupling between adsorbed NPs, resulting in tunable spectral variations and enhanced broadband absorption that amplify both nonlinear optical and thermoplasmonic effects and enables novel biosensing strategies.
Network isomorphism?: A network perspective on the symbolic performance of purpose-oriented networks

Abstract While there has been increasing interest in understanding network performance in public and nonprofit sectors, the existing literature on network performance has primarily focused on the internal functioning of networks, paying less attention to the external environment. In this study, we address this gap by adopting a network domain perspective in combination with social network analysis technique to examine both internal and external stakeholder assessments of network’s symbolic performance. Examining a case where multiple networks exist in one county who all focused on the health domain, the study aims to test competing hypotheses built upon institutional theory and strategic management literature on the relationship between network isomorphism and networks’ symbolic performance. Our findings aim to contribute to both the public network literature as well as advance institutional theory within networked environments.
The Need Of Innovation Among Malaysian SMEs

Innovation is a concept that has received much attention in recent years. Innovation leads to the product and process improvement, assists organization to survive, to grow faster, to be more efficient, and ultimately to be more profitable than non-innovators. However, the innovation rate in Malaysia is not yet reaching the full potential. In addition, innovative behavior in Malaysia is still at the infancy stage, especially among SMEs in Malaysia. In order to boost the innovation rate, it is imperative to solve the challenges and issues faced by SMEs. Thus, the enablers of innovation performance are proposed to SMEs in this study. With the enablers proposed, it can lead to a greater innovation performance among SMEs and assist the country’s growth which eventually improve the global innovation index ranking. As such, organizational culture and organizational learning are proposed as potential enablers to improve innovation performance among SMEs. The study also proposed open innovation as a potential mediator with the above relationships. In a nutshell, the purpose of the present study is to propose a conceptual framework which can be utilized to boost the innovation among Malaysian SMEs.
Using N-dimensional Mutual Information to Measure Protein Multiple Residues Coevolution

Many computational tools have been developed to study amino acid co-evolution in proteins. Most of them, such as McLachlan-based substitution correlation and Mutual Information (MI), only focus on co-evolution of two amino acid residues. On the other hand, co-evolution information of multiple residues is useful to study protein structures and functions. Therefore, there is an urgent requirement for methods to identify multiple co-evolved residues. The n-dimensional Mutual Information (n DMI) method is introduced to identify co-evolution of multiple residues. This algorithm gains the co-evolution information of multiple residues from analysis of a matrix of MI values. The method was applied to G proteins. Results show that n DMI method is effective in identification of multiple co-evolved amino acids. Moreover, n DMI performs better in discovering functional important residues than methods focusing on pairwise co-evolved residues.
Exploring the Use of Decision Tree Methodology in Hydrology Using Crowdsourced Data

To fill the observations gap on ungauged streams, crowdsourced distributed hydrologic measurements were considered as a potential supplement for observational data networks. However, citizen science data come with uncertainty as they are provided by the general public. In order to investigate this uncertainty, a decision tree methodology was applied to evaluate existing citizen science data of stream stage based on the CrowdHydrology (CH) network. Quality control (QC) flags were developed and applied to CH sites, dividing Level 1 dataset (raw dataset) into Level 2 (flagged dataset) and Level 3 (processed dataset). Error estimates were calculated to determine uncertainty in the citizen science data. The results indicate that the decision tree could provide reliable QC for citizen science data and demonstrate how uncertainty can be quantified in the QC datasets.
Niche partitioning in similar, closely related sympatric bat species? : A mechanical approach.

Two sympatrically occurring bat species, Myotis myotis, Borkhausen 1797, and Myotis blythii, Tomes 1857 (Chiroptera, Vespertillionidae), share numerous similarities in morphology, roosting behaviour and echolocation and are often difficult to distinguish. However, despite these similarities, their foraging behaviour is noticeably different. Our aim was to examine the extent to which these different foraging strategies reflect morphological adaptation. We assessed whether the morphology of the wing, body and tail differed between M. myotis and M. blythii. In addition, in a laboratory experiment involving an obstacle course, we compared differences in manoeuvrability by relating them to our morphological measurements. The two species differed in their overall size, wing-tip shape and tail-tobody length ratio. The generally smaller-sized M. blythii performed better in the obstacle course and was therefore considered to be more manoeuvrable. Although differences in wing-tip shape were observed, we found the most important characteristic affecting manoeuvrability in both species to be the tail-tobody length ratio. Additionally, when we compared two bats with injured wing membranes with unharmed bats of the same species, we found no difference in manoeuvrability, even when the wing shape was asymmetric. We therefore postulate that morphometric differences between the two species in their overall size and, more importantly, in their tail-to-body length ratio are the main physical characteristics providing proof of adaptation to different foraging and feeding strategies.
Forest biomass stocks and dynamics across the subtropical Andes

Forest biomass plays an important role in the global carbon cycle. Therefore, understanding the factors that control forest biomass stocks and dynamics is a key challenge in the context of global change. We analyzed data from 60 forest plots in the subtropical Andes (22–27.5° S and 300–2300 m asl) to describe patterns and identify drivers of aboveground biomass (AGB) stocks and dynamics. We found that AGB stocks remained roughly constant with elevation due to compensating changes in basal area (which increased with elevation) and plot‐mean wood specific gravity (which decreased with elevation). AGB gain and loss rates both decreased with elevation and were explained mainly by temperature and rainfall (positive effects on both AGB gains and losses). AGB gain was also correlated with forest‐use history and weakly correlated with forest structure. Mean annual temperature and rainfall showed minor effects on AGB stocks and AGB change (gains minus losses) over recent decades. Although AGB change was only weakly correlated with climate variables, increases in AGB gains and losses with increasing rainfall—together with observed increases in rainfall in the subtropical Andes—suggest that these forests may become increasingly dynamic in the future.
An Analysis of the KDD99 and UNSW-NB15 Datasets for the Intrusion Detection System

The significant increase in technology development over the internet makes network security a crucial issue. An intrusion detection system (IDS) shall be introduced to protect the networks from various attacks. Even with the increased amount of works in the IDS research, there is a lack of studies that analyze the available IDS datasets. Therefore, this study presents a comprehensive analysis of the relevance of the features in the KDD99 and UNSW-NB15 datasets. Three methods were employed: a rough-set theory (RST), a back-propagation neural network (BPNN), and a discrete variant of the cuttlefish algorithm (D-CFA). First, the dependency ratio between the features and the classes was calculated, using the RST. Second, each feature in the datasets became an input for the BPNN, to measure their ability for a classification task concerning each class. Third, a feature-selection process was carried out over multiple runs, to indicate the frequency of the selection of each feature. From the result, it indicated that some features in the KDD99 dataset could be used to achieve a classification accuracy above 84%. Moreover, a few features in both datasets were found to give a high contribution to increasing the classification’s performance. These features were present in a combination of features that resulted in high accuracy; the features were also frequently selected during the feature selection process. The findings of this study are anticipated to help the cybersecurity academics in creating a lightweight and accurate IDS model with a smaller number of features for the developing technologies.