bluuebunny/crossref_metadata_2025 huggingface dataset:
Antimicrobial Paper Coatings Containing Microencapsulated Cymbopogon citratus Oil
Authors: Šumiga Boštjan , Šumiga Barbara , Ravnjak David , Boh Podgornik Bojana
Published: July 2019

Essential oils are environmentally friendly candidates for antimicrobial smart packaging systems. Encapsulation is needed to reduce their volatility and achieve controlled release. Within this study, the essential oil of Cymbopogon citratus (citronella oil) was microencapsulated and applied in pressure-sensitive antimicrobial functional coatings on papers for secondary packaging. Two microencapsulation methods were used: complex coacervation of gelatine with carboxymethylcellulose or with gum arabic, and in situ polymerization of melamine-formaldehyde prepolymers with a polyacrylic acid modifier. Minimum inhibitory concentrations of citronella oil microcapsules were determined for Bacillus subtilis (B. subtilis), Escherichia coli (B. subtilis), Pseudomonas aeruginosa (P. aeruginosa) and Saccharomyces cerevisiae (S. cerevisiae). Microcapsule suspensions were coated on papers for flexible packaging, 2 and 30 g/m2, and mechanically activated in the weight pulling test. A novel method on agar plates in sealed Petri dishes was developed to evaluate the antimicrobial activity of released citronella vapours on E. coli and S. cerevisiae. The results showed that both microencapsulation methods were successful and resulted in a container type single-core microcapsules. In situ microcapsule suspensions had better paper coating properties and were selected for industrial settings. The antimicrobial activity of 2 g/m2 coatings was not detected; however, the antimicrobial activity of 30 g/m2 partially activated coated papers was confirmed. The product enabled a prolonged use with the gradual release of citronella oil at multiple exposures of functional papers to pressure, e.g., by a human hand during product handling.
Investigation of Surfactant AOT Mediated Charging of PS Particles Dispersed in Aqueous Solutions
Authors: Cao Huiying , An Baichao , Wang Yong , Zhou Kun , Lu Naiyan
Published: July 2019

Nano/submicron particles can be activated by surfactants and aggregate at the air-water interface to generate and stabilize foams. Such systems have been applied extensively in the food, medicine, and cosmetic industries. Studying particle charging behavior in a particle/surfactant/water system is a fundamental way to understand the activation of the particle surface. This paper presents an investigation of the charging behavior of polystyrene (PS) particles dispersed in aqueous solutions of the surfactant sodium di-2-ethylhexylsulfosuccinate (AOT). The results showed that zeta potential of PS was related to the AOT concentration with two different concentration regions. Below the critical micelle concentration (CMC), the charging of PS particles was effected by AOT ions; while above the CMC, it came from both AOT ions and AOT micelles. This behavior was different from that observed for PS in aqueous salt solutions. Additionally, the particle concentration and size were found to affect the zeta potential differently in the two AOT concentration regions. By analyzing these results, the charging mechanism of the PS/AOT/water system was revealed to be preferential adsorption. In summary, the study disclosed the internal connection between the PS charging in aqueous AOT solution and the activation of PS particles, as well as their influence to foam formation and stability.
Glucose Oxidase Micropumps: Multi-Faceted Effects of Chemical Activity on Tracer Particles Near the Solid–Liquid Interface
Authors: Munteanu Raluca-Elena , Popescu Mihail N. , Gáspár Szilveszter
Published: July 2019

We report the development of glucose oxidase pumps characterized by small lateral dimensions (≈200 μ m). We studied the effects of the activity of the enzyme pump on silica particles (“tracers”) sedimented around the enzyme pump/patch. Once the activity of the pump was turned on (i.e., the glucose substrate was added to the solution), in-plane motion of the tracers away from the enzyme patch, as well as the emergence of an in-plane region around the patch which was depleted by tracers, was observed. The lateral extent of this depletion zone increased in time at a rate dependent both on the glucose concentration and on the areal density of the enzyme in the patch. We argue that, when the tracers were very near the wall, their motion and the emergence of the depletion zone were most likely the result of diffusiophoresis and drag by osmotic flows induced at the wall, rather than that of drag by a solutal buoyancy driven convective flow. We infer that, for the glucose oxidase enzymatic pumps, bulk (solutal buoyancy), as previously reported, as well as surface (osmotic) driven flows coexist and have to be explicitly accounted for. It seems plausible to assume that this is the case in general for enzyme pumps, and these complementary effects should be considered in the design of applications, e.g., stirring or sensing inside microfluidic systems, based on such pumps.
All-Inorganic Red-Light Emitting Diodes Based on Silicon Quantum Dots
Authors: Ghosh Batu , Shirahata Naoto
Published: July 2019

We report herein an all-inorganic quantum dot light emitting diode (QLED) where an optically active layer of crystalline silicon (Si) is mounted. The prototype Si-QLED has an inverted device architecture of ITO/ZnO/QD/WO3/Al multilayer, which was prepared by a facile solution process. The QLED shows a red electroluminescence, an external quantum efficiency (EQE) of 0.25%, and luminance of 1400 cd/m2. The device performance stability has been investigated when the device faces different humidity conditions without any encapsulation. The advantage of using all inorganic layers is reflected in stable EQE even after prolonged exposure to harsh conditions.
Living on the Edge: Variation in the Abundance and Demography of a Kelp Forest Epibiont
Authors: Arkema Katie K. , Samhouri Jameal F.
Published: July 2019

The ecology of an epibiont may depend not only on the dynamics of its biogenic habitat but also on microclimate variation generated within aggregations of its host, a process called physical ecosystem engineering. This study explored variation in the abundance and demography of Membranipora, a suspension-feeding bryozoan, within forests of giant kelp (Macrocystis pyrifera) off the coast of Santa Barbara, California, USA. First, we assessed differences in Membranipora abundance between the edge and interior of kelp forests. The occurrence of Membranipora on kelp blades and its percent cover on occupied blades were higher along forest edges than interiors. Second, we conducted observational studies and field experiments to understand spatial variation in substrate longevity, colony mortality, larval recruitment, and colony growth rates. A higher density of recruits and colonies occurred along forest edges than interiors, suggesting kelp acts like a sieve, whereby larvae settle to edge blades first. Moreover, growth rates along the edge were up to 45% higher than forest interiors. Reduced current speeds, combined with feeding by exterior colonies, may have lowered the uptake of suspended food particles by interior colonies. These results suggest that variation in Membranipora abundance is due in part to differences in colony growth between forest edges and interiors, and not solely the result of recruitment limitation. Our results highlight the importance of ecosystem engineers in influencing the ecological dynamics of epiphytic flora and fauna in marine systems.
From Targeting Somatic Mutations to Finding Inherited Cancer Predispositions: The Other Side of the Coin
Authors: Pujol Pascal , De La Motte Rouge Thibault , Penault-Llorca Frédérique
Published: July 2019

The expanding use of tumor genome analysis by next generation sequencing to drive target therapies has led to increased germline findings in genes predisposing to hereditary cancer. These putative germline findings obtained from theranostic analyses, such as BRCA1/2 gene testing, large panels, whole-exome, or whole-genome sequencing, need to be managed carefully and in an anticipated way with the patient. Before the genetic analysis of a tumor, specific information should be given to patients, who should be aware that the results may have extra-therapeutic medical issues for themselves and relatives. We previously published a list of 36 actionable genes predisposing to cancer for which informing the patient is recommended prior to pangenomic germline analysis because of available screening or preventive strategies. Here, we report clinical practice considerations and schemes for managing germline findings in tumor analyses, including written informed consent and a multidisciplinary approach involving an oncologist, molecular biologist/pathologist, and geneticist in case of germline findings. A somatic result showing a deleterious mutation in a known predisposing gene in a patient who has consented to this purpose should result in referral to a geneticist who is part of the multidisciplinary team. At any time of the somatic analysis process, the patient may have access to a geneticist consultation if additional information is required. This framework will optimally manage both personalized theranostic issues and specific preventive strategies for individuals and relatives; it will also simplify and accelerate the process of genetic testing.
Beyond the Maximum Storage Capacity Limit in Hopfield Recurrent Neural Networks
Authors: Gosti Giorgio , Folli Viola , Leonetti Marco , Ruocco Giancarlo
Published: July 2019

In a neural network, an autapse is a particular kind of synapse that links a neuron onto itself. Autapses are almost always not allowed neither in artificial nor in biological neural networks. Moreover, redundant or similar stored states tend to interact destructively. This paper shows how autapses together with stable state redundancy can improve the storage capacity of a recurrent neural network. Recent research shows how, in an N-node Hopfield neural network with autapses, the number of stored patterns (P) is not limited to the well known bound 0.14 N , as it is for networks without autapses. More precisely, it describes how, as the number of stored patterns increases well over the 0.14 N threshold, for P much greater than N, the retrieval error asymptotically approaches a value below the unit. Consequently, the reduction of retrieval errors allows a number of stored memories, which largely exceeds what was previously considered possible. Unfortunately, soon after, new results showed that, in the thermodynamic limit, given a network with autapses in this high-storage regime, the basin of attraction of the stored memories shrinks to a single state. This means that, for each stable state associated with a stored memory, even a single bit error in the initial pattern would lead the system to a stationary state associated with a different memory state. This thus limits the potential use of this kind of Hopfield network as an associative memory. This paper presents a strategy to overcome this limitation by improving the error correcting characteristics of the Hopfield neural network. The proposed strategy allows us to form what we call an absorbing-neighborhood of state surrounding each stored memory. An absorbing-neighborhood is a set defined by a Hamming distance surrounding a network state, which is an absorbing because, in the long-time limit, states inside it are absorbed by stable states in the set. We show that this strategy allows the network to store an exponential number of memory patterns, each surrounded with an absorbing-neighborhood with an exponentially growing size.
Investigation of Linear and Nonlinear Properties of a Heartbeat Time Series Using Multiscale Rényi Entropy
Authors: Jelinek Herbert , Cornforth David , Tarvainen Mika , Khalaf Kinda
Published: July 2019

The time series of interbeat intervals of the heart reveals much information about disease and disease progression. An area of intense research has been associated with cardiac autonomic neuropathy (CAN). In this work we have investigated the value of additional information derived from the magnitude, sign and acceleration of the RR intervals. When quantified using an entropy measure, these time series show statistically significant differences between disease classes of Normal, Early CAN and Definite CAN. In addition, pathophysiological characteristics of heartbeat dynamics provide information not only on the change in the system using the first difference but also the magnitude and direction of the change measured by the second difference (acceleration) with respect to sequence length. These additional measures provide disease categories to be discriminated and could prove useful for non-invasive diagnosis and understanding changes in heart rhythm associated with CAN.
Minimum Memory-Based Sign Adjustment in Signed Social Networks
Authors: Qi Mingze , Deng Hongzhong , Li Yong
Published: July 2019

In social networks comprised of positive (P) and negative (N) symmetric relations, individuals (nodes) will, under the stress of structural balance, alter their relations (links or edges) with their neighbours, either from positive to negative or vice versa. In the real world, individuals can only observe the influence of their adjustments upon the local balance of the network and take this into account when adjusting their relationships. Sometime, their local adjustments may only respond to their immediate neighbourhoods, or centre upon the most important neighbour. To study whether limited memory affects the convergence of signed social networks, we introduce a signed social network model, propose random and minimum memory-based sign adjustment rules, and analyze and compare the impacts of an initial ratio of positive links, rewire probability, network size, neighbor number, and randomness upon structural balance under these rules. The results show that, with an increase of the rewiring probability of the generated network and neighbour number, it is more likely for the networks to globally balance under the minimum memory-based adjustment. While the Newmann-Watts small world model (NW) network becomes dense, the counter-intuitive phenomena emerges that the network will be driven to a global balance, even under the minimum memory-based local sign adjustment, no matter the network size and initial ratio of positive links. This can help to manage and control huge networks with imited resources.
Anomalies Detection and Proactive Defence of Routers Based on Multiple Information Learning
Authors: Li Teng , Ma Jianfeng , Shen Yulong , Pei Qingqi
Published: July 2019

Routers are of great importance in the network that forward the data among the communication devices. If an attack attempts to intercept the information or make the network paralyzed, it can launch an attack towards the router and realize the suspicious goal. Therefore, protecting router security has great importance. However, router systems are notoriously difficult to understand or diagnose for their inaccessibility and heterogeneity. A common way of gaining access to the router system and detecting the anomaly behaviors is to inspect the router syslogs or monitor the packets of information flowing to the routers. These approaches just diagnose the routers from one aspect but do not correlate multiple logs. In this paper, we propose an approach to detect the anomalies and faults of the routers with multiple information learning. First, we do the offline learning to transform the benign or corrupted user actions into the syslogs. Then, we construct the log correlation among different events. During the detection phase, we calculate the distance between the event and the cluster to decide if it is an anomalous event and we use the attack chain to predict the potential threat. We applied our approach in a university network which contains Huawei, Cisco and Dlink routers for three months. We aligned our experiment with former work as a baseline for comparison. Our approach obtained 89.6% accuracy in detecting the attacks, which is 5.1% higher than the former work. The results show that our approach performs in limited time as well as memory usages and has high detection and low false positives.
Machine-Assisted Learning in Highly-Interdisciplinary Media Fields: A Multimedia Guide on Modern Art
Authors: Chatzara Elena , Kotsakis Rigas , Tsipas Nikolaos , Vrysis Lazaros , Dimoulas Charalampos
Published: July 2019

Art and technology have always been very tightly intertwined, presenting strong influences on each other. On the other hand, technological evolution led to today’s digital media landscape, elaborating mediated communication tools, thus providing new creative means of expression (i.e., new-media art). Rich-media interaction can expedite the whole process into an augmented schooling experience though art cannot be easily enclosed in classical teaching procedures. The current work focuses on the deployment of a modern-art web-guide, aiming at enhancing traditional approaches with machine-assisted blended-learning. In this perspective, “machine” has a two-folded goal: to offer highly-interdisciplinary multimedia services for both in-class demonstration and self-training support, and to crowdsource users’ feedback, as to train artificial intelligence systems on painting movements semantics. The paper presents the implementation of the “Istoriart” website through the main phases of Analysis, Design, Development, and Evaluation, while also answering typical questions regarding its impact on the targeted audience. Hence, elaborating on this constructive case study, initial hypotheses on the multidisciplinary usefulness, and contribution of the new digital services are put into test and verified.
Optimized Proportional-Integral-Derivative Controller for Upper Limb Rehabilitation Robot
Authors: Joyo M. Kamran , Raza Yarooq , Ahmed S. Faiz , Billah M. M. , Kadir Kushsairy , Naidu Kanendra , Ali Athar , Mohd Yusof Zukhairi
Published: July 2019

This paper proposes a nature inspired, meta-heuristic optimization technique to tune a proportional-integral-derivative (PID) controller for a robotic arm exoskeleton RAX-1. The RAX-1 is a two-degrees-of-freedom (2-DOFs) upper limb rehabilitation robotic system comprising two joints to facilitate shoulder joint movements. The conventional tuning of PID controllers using Ziegler-Nichols produces large overshoots which is not desirable for rehabilitation applications. To address this issue, nature inspired algorithms have recently been proposed to improve the performance of PID controllers. In this study, a 2-DOF PID control system is optimized offline using particle swarm optimization (PSO) and artificial bee colony (ABC). To validate the effectiveness of the proposed ABC-PID method, several simulations were carried out comparing the ABC-PID controller with the PSO-PID and a classical PID controller tuned using the Zeigler-Nichols method. Various investigations, such as determining system performance with respect to maximum overshoot, rise and settling time and using maximum sensitivity function under disturbance, were carried out. The results of the investigations show that the ABC-PID is more robust and outperforms other tuning techniques, and demonstrate the effective response of the proposed technique for a robotic manipulator. Furthermore, the ABC-PID controller is implemented on the hardware setup of RAX-1 and the response during exercise showed minute overshoot with lower rise and settling times compared to PSO and Zeigler-Nichols-based controllers.
Unsupervised Single-Image Super-Resolution with Multi-Gram Loss
Authors: Shi Yong , Li Biao , Wang Bo , Qi Zhiquan , Liu Jiabin
Published: July 2019

Recently, supervised deep super-resolution (SR) networks have achieved great success in both accuracy and texture generation. However, most methods train in the dataset with a fixed kernel (such as bicubic) between high-resolution images and their low-resolution counterparts. In real-life applications, pictures are always disturbed with additional artifacts, e.g., non-ideal point-spread function in old film photos, and compression loss in cellphone photos. How to generate a satisfactory SR image from the specific prior single low-resolution (LR) image is still a challenging issue. In this paper, we propose a novel unsupervised method named unsupervised single-image SR with multi-gram loss (UMGSR) to overcome the dilemma. There are two significant contributions in this paper: (a) we design a new architecture for extracting more information from limited inputs by combining the local residual block and two-step global residual learning; (b) we introduce the multi-gram loss for SR task to effectively generate better image details. Experimental comparison shows that our unsupervised method in normal conditions can attain better visual results than other supervised SR methods.
Improving Optical Performance of Ultraviolet Light-Emitting Diodes by Incorporating Boron Nitride Nanoparticles
Authors: Yan Caiman , Zhao Qiliang , Li Jiasheng , Ding Xinrui , Tang Yong , Li Zongtao
Published: July 2019

Ultraviolet light-emitting diodes (UVLED) are a new type of device in the LED development; however, the radiant efficacy of UVLEDs is still too low to satisfy the requirements of applications. In this study, boron nitride nanoparticles (BN NPs) are incorporated into the UVLED’s silicone encapsulation to improve the optical output power. This BN NPs-based package shows an increase in optical flux of 8.1% compared with silicone-only encapsulation when the BN NP concentration is optimized at 0.025 wt%. By analyzing the BN NP film, adding the BN NPs into silicone leads to a decrease in transmittance but an increase in haze. Haze and transmittance has an excellent negative correlation with increasing BN concentration under 365 nm. The moderate BN NP concentration maximizes the scattering performance from haze while maintaining high transmittance. Therefore, this enhanced light output is attributed to scattering that reduces optical losses from total internal reflection at the silicone–air interface. By using the new BN-based structure in green and red quantum dot devices, an increase radiant flux of the device is observed, 9.9% for green LED and 11.4% for red LED. This indicates that BN NPs have potential prospects in the application of UV LEDs used as excitation sources for quantum dots.
Wireless Power and Data Transmission System of Submarine Cable-Inspecting Robot Fish and Its Time-Sharing Multiplexing Method
Authors: Chen Guodong , Sun Yue , Huang Junxin , Zhou Boda , Meng Fanchao , Tang Chunsen
Published: July 2019

In this paper, a hybrid system topology with one-way wireless charging function and the function of the bi-directional data communication is proposed for the problem of electric energy replenishment and data transmission faced by robot fish in the implementation of autonomous submarine cable inspection. Three working modes of the system and the time-sharing multiplexing method are studied. In the power transmission mode, high-efficiency wireless charging is realized by utilizing the transmission characteristics of a series–series (SS)-type resonant network which involves series resonant networks in both the primary side and the secondary side. In the alignment detection and handshake communication mode, the charging platform distance recognition and the handshake signal transmission are implemented through a series–parallel (SP)-type resonant network based on the ASK (amplitude shift keying) modulation method. In the high-speed data transmission mode, the reverse (secondary to primary) high-speed transmission of the inspection data is achieved through a SP-type resonant network based on the OFDM (orthogonal frequency division multiplexing) modulation method. The three modes share the same coupled coils via a reconfigurable resonant network. The working principle of the system is expounded, the system characteristics under each working mode are analyzed, and the time-division multiplexing control strategy is given. The rationality and effectiveness of the scheme are verified by experiments.
Optimal Current Balance Control of Three-Level Inverter under Grid Voltage Unbalance: An Adaptive Dynamic Programming Approach
Authors: Yu Yunjun , Wang Zhongyang , Wan Xiaofeng
Published: July 2019

When the grid voltage is unbalanced, the positive and negative sequence components in the grid voltage cause grid current to be disordered. Under current balance control, proportional integral (PI) closed-loop control will increase the grid currents instantaneously, which affects the safety and reliability of the inverter operation, and PI parameters are difficult to select without the complete system mathematical model. This paper introduces an adaptive dynamic programming (ADP) approach to solve this problem. The best state feedback controller for the system is obtained by driving the ADP by the value iteration ( V I ) algorithm without the need for an accurate mathematical model. In the simulations, the ADP approach can improve the dynamic performance of the system, the current increase can be suppressed when the grid voltage is unbalanced, and the harmonic rate of output currents is reduced.
Flexibility Potential of Space Heating Demand Response in Buildings for District Heating Systems
Authors: Romanchenko Dmytro , Nyholm Emil , Odenberger Mikael , Johnsson Filip
Published: July 2019

Using an integrated demand-supply optimization model, this work investigates the potential for flexible space heating demand, i.e., demand response (DR), in buildings, as well as its effects on the heating demand and the operation of a district heating (DH) system. The work applies a building stock description, including both residential and non-residential buildings, and employs a representation of the current DH system of the city of Gothenburg, Sweden as a case study. The results indicate that space heating DR in buildings can have a significant impact on the cost-optimal heat supply of the city by smoothing variations in the system heat demand. DR implemented via indoor temperature deviations of as little as +1 °C can smoothen the short-term (daily) fluctuations in the system heating demand by up to 18% over a period of 1 year. The smoothening of the demand reduces the cost of heat generation, in that the heat supply and number of full-load hours of base-load heat generation units increase, while the number of starts for the peaking units decreases by more than 80%. DR through temperature deviations of +3 °C confers diminishing returns in terms of its effects on the heat demand, as compared to the DR via +1 °C.
A Modulated Model Predictive Current Controller for Interior Permanent-Magnet Synchronous Motors
Authors: Agustin Crestian Almazan , Yu Jen-te , Lin Cheng-Kai , Fu Xiang-Yong
Published: July 2019

Model predictive current controllers (MPCCs) are widely applied in motor drive control and operations. To date, however, the presence of large current errors in conventional predictive current control remains a significant predicament, due to harmonic distortions and current ripples. Naturally, noticeable current estimation inaccuracies lead to poor performance. To improve the above situation, a modulated model predictive current controller (MMPCC) is proposed for interior permanent-magnet synchronous motors (IPMSMs) in this paper. Two successive voltage vectors will be applied in a sampling period to greatly boost the number of candidate switching modes from seven to thirteen. A cost function, which is defined as the quadratic sum of current prediction errors, is employed to find an optimal switching mode and an optimized duty ratio to be applied in the next sampling period, such that the cost value is minimal. The effectiveness of the proposed method is verified through eight experiments using a TMS320F28379D microcontroller, and performance comparisons are made against an existing MPCC. In terms of quantitative improvements made to the MPCC, the proposed MMPCC reduces its current ripple and total harmonic distortion (THD) by, on average, 27.17% and 21.84%, respectively.
A Q-Cube Framework of Reinforcement Learning Algorithm for Continuous Double Auction among Microgrids
Authors: Wang Ning , Xu Weisheng , Shao Weihui , Xu Zhiyu
Published: July 2019

Decision-making of microgrids in the condition of a dynamic uncertain bidding environment has always been a significant subject of interest in the context of energy markets. The emerging application of reinforcement learning algorithms in energy markets provides solutions to this problem. In this paper, we investigate the potential of applying a Q-learning algorithm into a continuous double auction mechanism. By choosing a global supply and demand relationship as states and considering both bidding price and quantity as actions, a new Q-learning architecture is proposed to better reflect personalized bidding preferences and response to real-time market conditions. The application of battery energy storage system performs an alternative form of demand response by exerting potential capacity. A Q-cube framework is designed to describe the Q-value distribution iteration. Results from a case study on 14 microgrids in Guizhou Province, China indicate that the proposed Q-cube framework is capable of making rational bidding decisions and raising the microgrids’ profits.
High Resolution Maps of Climatological Parameters for Analyzing the Impacts of Climatic Changes on Swiss Forests
Authors: Zischg Andreas Paul , Gubelmann Päivi , Frehner Monika , Huber Barbara
Published: July 2019

Assessing the impacts of climatic changes on forests requires the analysis of actual climatology within the forested area. In mountainous areas, climatological indices vary markedly with the micro-relief, i.e., with altitude, slope, and aspect. Consequently, when modelling potential shifts of altitudinal belts in mountainous areas due to climatic changes, maps with a high spatial resolution of the underlying climatological indices are fundamental. Here we present a set of maps of climatological indices with a spatial resolution of 25 by 25 m. The presented dataset consists of maps of the following parameters: average daily temperature high and low in January, April, July, and October as well as of the year; seasonal and annual thermal continentality; first and last freezing day; frost-free vegetation period; relative air humidity; solar radiation; and foehn conditions. The parameters represented in the maps have been selected in a knowledge engineering approach. The maps show the climatology of the periods 1961–1990 and 1981–2010. The data can be used for statistical analyses of forest climatology, for developing tree distribution models, and for assessing the impacts of climatic changes on Swiss forests.
Drivers of Household Decision-Making on Land-Use Transformation: An Example of Woodlot Establishment in Masindi District, Uganda
Authors: Ahimbisibwe Vianny , Auch Eckhard , Groeneveld Jürgen , Tumwebaze Susan Balaba , Berger Uta
Published: July 2019

Land use transformation at the farm level is attributed to household decision-making, reflected by the behavior and activities of smallholder farmers. Unfortunately, household decision-making in local communities and its determinants are site-specific and hardly understood. This study uses multistage purposive selection of households as a unit for the analysis to investigate the transformation from pure agriculture to farm forest mosaics, especially through woodlot establishment. We use key informants, household surveys, and observations to obtain data on decision-making amongst 84 farm households in Nyantonzi parish, Masindi district, Uganda, as an example. Specifically, the study addresses four research questions. Firstly, what is the current status of gender-based decision-making at the household level? Secondly, is decision making within farm households individualistic or collective? Thirdly, which factors are considered to select annual, perennial and tree-crop farm management regimes? Fourthly, what determinants influence the decision-making process and the likelihood of woodlot establishment? A multilevel analysis comprising parametric statistical models and binary logistic regression is applied to assess difference in household natural, physical, human, and social capital, highlight gender roles, and obtain factors associated to selection of crops and determinants of woodlot establishment at the farm level, respectively. Results reveal that gender based decision-making is clearly disaggregated on the basis of husbands and wives and it is individualistic, mostly dominated by husbands with lower participation by wives and other family members. Households consider various factors before making any decisions, e.g., market prices for both annual and perennial crops, food consumption for annual crops, ease of management, and yields from the previous season for the tree-crop management regimes. The likelihood for woodlot establishment is positively influenced by the willingness and intention of households to establish woodlots and relative age of household head. However, knowledge of land use Policies, Laws, and Regulations (PLRs) in relation to tree planting and harvesting and access to non-farm income reduce the likelihood of woodlot establishment. Here, we recommend that current and future forest land restoration initiatives focus on reducing the gender gap and increase women’s participation in decision making, provide market information platforms on wood products, and include woodlot farmers in social organization. Current PLRs on tree tenure should be improved and clearly communicated by using the existing communication assets and social gatherings as channels of change and influence for decision-making.
The Dehesas of Extremadura, Spain: A Potential for Socio-Economic Development Based on Agritourism Activities
Authors: Sánchez-Martín José-Manuel , Blas-Morato Rocío , Rengifo-Gallego Juan-Ignacio
Published: July 2019

Dehesas form an agroforestry system which is highly developed in Extremadura as they occupy over 1,000,000 hectares. This is an extensive production system based on exploitation by stockbreeding with certain complements of agricultural and extractive products. It is however underexploited for activities other than agrolivestock production. As a result this research starts from the hypothesis that greater socio-economic development is possible in areas near this type of ecosystem if we consider that it is extremely attractive to tourism, at least in some of its forms. Complementing agrolivestock exploitation with tourist exploitation means that it is necessary to be familiar with the situation of the current availability of accommodation. In order to do so we analyse the main parameters characterising rural accommodation in Extremadura, Spain, the results of which reflect low occupancy for a large part of the year and consequently seasonal variation is high. This fact contrasts with the huge potential of dehesas for agritourism. In order to carry out this study we resort to the use of spatial statistics, in particular the grouping analysis. In its configuration we consider the location of the rural accommodation and its proximity to areas of dehesas made up of holm oaks (Quercus ilex) and cork oaks (Quecus suber) together with protected natural spaces, basing ourselves also on proximity to livestock trails and natural swimming pools. The results lead to the creation of 5 homogeneous groups of which 3 correspond to accommodation establishments capable of setting up agritourism and agriecotourism initiatives; this affects 45% of the establishments. However, no current initiatives of this type exist despite the fact that the National Reference Centre for Agritourism is located in Extremadura. From this can be inferred the need for implementing tourist policies to encourage the generating of tourist products specifically intended to exploit the potential of the dehesa as a complement to the current availability of rural accommodation.
The Role of Woodlots in Forest Regeneration outside Protected Areas: Lessons from Tanzania
Authors: Kimambo Niwaeli E. , Naughton-Treves Lisa
Published: July 2019

Promoting forest regeneration outside protected forests is an urgent challenge in densely settled, biodiverse areas like the East African Rift. Regenerating forests entails managing complex processes of ecological recovery as well as understanding the needs and motivations of local land users. Here, we evaluate pathways for attaining native tree regeneration across variable site conditions. We investigate two common strategies for attaining native tree regeneration—setting aside land for forest regeneration (‘Protect and Wait’) and native tree planting (‘Native Tree Planting’)—and a possible third, smallholder exotic tree-planting (‘Woodlots’). We measured native seedling regeneration patterns for each of the three strategies, all underway at a single site in Southern Tanzania. We also used historical aerial photograph analysis and interviews with smallholder farmers to understand past and present land use. Our results show that forest regeneration has been arrested for decades on land under ‘Protect and Wait’, and seedling survival appears to be limited under ‘Native Tree Planting’. In contrast, we found saplings of 28 native species growing spontaneously within pine, eucalyptus, and cypress woodlots planted <400 m from native forest boundaries. Interviews showed that the citizens most likely to plant woodlots near the protected forest were those who owned additional land parcels elsewhere. Some saw woodlots as a means to avoid losing crops to wildlife at the forest edge. Our findings suggest: (1) Simply setting aside land for regeneration does not guarantee forest regrowth, even if it is adjacent to natural forest, (2) native seedlings will be more likely to survive if planted near shade trees, and (3) smallholders’ woodlots could hasten native tree regeneration at forest park edges if farmers have incentives to protect the native tree seedlings in their woodlots and they can find land elsewhere to plant food crops.
A Comprehensive Assessment of Bioactive Metabolites, Antioxidant and Antiproliferative Activities of Cyclocarya paliurus (Batal.) Iljinskaja Leaves
Authors: Zhou Mingming , Chen Pei , Lin Yuan , Fang Shengzuo , Shang Xulan
Published: July 2019

Cyclocarya paliurus (Batal.) Iljinskaja is an indigenous and multifunction tree species in China, but it is mainly used in pharmaceutical and nutraceutical ingredients. To make a comprehensive evaluation on its bioactive metabolites, antioxidant and antitumor potentials of C. paliurus leaves, the leaf samples were collected from 15 geographic locations (natural populations) throughout its distribution areas. High-performance liquid chromatography (HPLC) and colorimetric methods were used to detect the contents of bioactive metabolites. The antioxidant activity was evaluated by 2,2′-diphenyl-1-picrylhydrazyl (DPPH), 2,2-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) and reducing power assays. The antiproliferative activity on different cancer cell types was evaluated by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. Contents of bioactive metabolites, and antioxidant and antiproliferative activities in the extracts were significantly affected by solvent and population. In most cases, the contents of flavonoids and triterpenoids, and the antioxidant and antiproliferative activities in the ethanol extracts were higher than the water extracts. The best scavenging capacity of DPPH (IC50 = 0.34 mg/mL) and ABTS (IC50 = 0.50 mg/mL) radical occurred in the ethanol extracts of S15 and S7 population respectively, while the strongest reducing power (EC50 = 0.71 mg/mL) was achieved in the ethanol extracts of S14 population. The antiproliferation effects of C. paliurus extracts on cancer cells varied with different cell types. The HeLa cell was the most sensitive to C. paliurus extracts, and their IC50 values of the ethanol extracts varied from 0.13 to 0.42 mg/mL among C. paliurus populations. Redundancy analysis showed that total polyphenol had the greatest contribution to the antioxidant activity, but total flavonoid was mostly responsible for the antiproliferation effects. These results would provide important scientific evidences not only for developing C. paliurus as a potent antioxidant and antitumor reagent, but also for obtaining the higher yield of bioactive compounds in the C. paliurus plantation.
Reutilization of Food Waste: One-Step Extration, Purification and Characterization of Ovalbumin from Salted Egg White by Aqueous Two-Phase Flotation
Authors: Jiang Bin , Na Jiaxin , Wang Lele , Li Dongmei , Liu Chunhong , Feng Zhibiao
Published: July 2019

For the purpose of reducing pollution and the reutilization of salted egg whites, which are byproducts of the manufacturing process of salted egg yolks and normally treated as waste, an aqueous two-phase flotation (ATPF) composed of polyethylene glycols (PEG 1000) and (NH4)2SO4 was applied to develop a simple, inexpensive and efficient process for the separation of ovalbumin (OVA) from salted egg whites. The effects of the concentration of PEG, the concentration of (NH4)2SO4, the flow rate and the flotation time on the flotation efficiency (Y) and purity (P) of OVA were investigated. A response surface method (RSM) experiment was carried out on the basis of a single-factor experiment. An efficient separation was achieved using ATPF containing 5 mL of 80% PEG 1000 (w/w), 28 mL of 28% (NH4)2SO4 (w/w), 35 mL/min of the flow rate and 30 min of the flotation time, while 2 mL of the salted egg white solution (salted eggs white (v): water (v) = 1:4) was loaded. Under the optimal conditions, Y and P of OVA could reach 82.15 ± 0.24% and 92.98 ± 0.68%, respectively. The purified OVA was characterized by sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE), reverse phase high-performance liquid chromatography (RP-HPLC), liquid chromatography-nano electrospray ionisation mass spectrometry (Nano LC-ESI-MS/MS), ultraviolet spectrum (UV), fluorescence spectrum (FL) and fourier transform infrared spectroscopy (FT-IR). The results indicated that the purity of OVA obtained by ATPF was satisfactory and there was no obvious difference in the structure of the OVA separated by ATPF and the standard. The results of the functional properties revealed no significant differences between OVA obtained by ATPF and the standard in oil binding capacity, viscosity, emulsibility and foam capacity.
Assessment of Virgin Olive Oil Adulteration by a Rapid Luminescent Method
Authors: González-Domínguez Raúl , Sayago Ana , Morales María Teresa , Fernández-Recamales Ángeles
Published: July 2019

The adulteration of virgin olive oil with hazelnut oil is a common fraud in the food industry, which makes mandatory the development of accurate methods to guarantee the authenticity and traceability of virgin olive oil. In this work, we demonstrate the potential of a rapid luminescent method to characterize edible oils and to detect adulterations among them. A regression model based on five luminescent frequencies related to minor oil components was designed and validated, providing excellent performance for the detection of virgin olive oil adulteration.
Investigation of Precise Molecular Mechanistic Action of Tobacco-Associated Carcinogen ‘NNK’ Induced Carcinogenesis: A System Biology Approach
Authors: Anukriti  , Dhasmana Anupam , Uniyal Swati , Somvanshi Pallavi , Bhardwaj Uma , Gupta Meenu , Haque Shafiul , Lohani Mohtashim , Kumar Dhruv , Ruokolainen Janne , Kesari Kavindra Kumar
Published: July 2019

Cancer is the second deadliest disease listed by the WHO. One of the major causes of cancer disease is tobacco and consumption possibly due to its main component, 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK). A plethora of studies have been conducted in the past aiming to decipher the association of NNK with other diseases. However, it is strongly linked with cancer development. Despite these studies, a clear molecular mechanism and the impact of NNK on various system-level networks is not known. In the present study, system biology tools were employed to understand the key regulatory mechanisms and the perturbations that will happen in the cellular processes due to NNK. To investigate the system level influence of the carcinogen, NNK rewired protein–protein interaction network (PPIN) was generated from 544 reported proteins drawn out from 1317 articles retrieved from PubMed. The noise was removed from PPIN by the method of modulation. Gene ontology (GO) enrichment was performed on the seed proteins extracted from various modules to find the most affected pathways by the genes/proteins. For the modulation, Molecular COmplex DEtection (MCODE) was used to generate 19 modules containing 115 seed proteins. Further, scrutiny of the targeted biomolecules was done by the graph theory and molecular docking. GO enrichment analysis revealed that mostly cell cycle regulatory proteins were affected by NNK.
Geological and Cultural Heritage: Dissemination Experiences in Tuscany
Authors: La Felice Sonia , Abebe Tsegaye , Aquino Andrea , Landi Simone , Lezzerini Marco , Principe Claudia
Published: July 2019

We report on some recent experiences of scientific dissemination activities on geomaterials carried out by a network of scientific organizations in Tuscany (Italy). The primary message we want to disseminate is that even the most “insignificant” rock (e.g., those constituting the bar or kitchen counter-tops) stores in their interior very useful information beyond the beautiful colors and their aesthetic appearance. These rocks can tell stories of very old geological periods on how they were formed. Their structures, texture and shape, as well as their chemistry and mineralogy provide clues to the reconstruction of geological events. Moreover, the rocks used in urban architecture and monuments are an inexhaustible archive containing a lot of historical and economic information on the development of a city and its surrounding area. The role of geologists, in this context, is to provide to the public, in clear and engaging language, the tools necessary to solve the puzzle (i.e., identify the most important types of rocks and rock-forming minerals, know their physico-chemical properties, their textures and structures and discover the environments in which they formed). A specific objective of this work is to stimulate an exchange between various research organizations (universities, public research institutions, museums, associations, etc.) and the civil society.
Mapping the Solastalgia Literature: A Scoping Review Study
Authors: Galway Lindsay P. , Beery Thomas , Jones-Casey Kelsey , Tasala Kirsti
Published: July 2019

Solastalgia is a relatively new concept for understanding the links between human and ecosystem health, specifically, the cumulative impacts of climatic and environmental change on mental, emotional, and spiritual health. Given the speed and scale of climate change alongside biodiversity loss, pollution, deforestation, unbridled resource extraction, and other environmental challenges, more and more people will experience solastalgia. This study reviewed 15 years of scholarly literature on solastalgia using a scoping review process. Our goal was to advance conceptual clarity, synthesize the literature, and identify priorities for future research. Four specific questions guided the review process: (1) How is solastalgia conceptualized and applied in the literature?; (2) How is solastalgia experienced and measured in the literature?; (3) How is ‘place’ understood in the solastalgia literature?; and (4) Does the current body of literature on solastalgia engage with Indigenous worldviews and experiences? Overall, we find there is a need for additional research employing diverse methodologies, across a greater diversity of people and places, and conducted in collaboration with affected populations and potential knowledge, alongside greater attention to the practical implications and applications of solastalgia research. We also call for continued efforts to advance conceptual clarity and theoretical foundations. Key outcomes of this study include our use of the landscape construct in relation to solastalgia and a call to better understand Indigenous peoples’ lived experiences of landscape transformation and degradation in the context of historical traumas.