Miracle-dz/UniFAR-FTUs huggingface dataset:
Chapter 10 Sustainable Management of Insect-Resistant Crops

Sustainability is a goal-oriented process that advances based on new knowledge. We discuss factors relevant to insect-resistant crops and sustainability: adoption patterns, insecticide use patterns and their influence on humans, biological control, areawide effects, and evolution of populations resistant to the transgenic crop. Genetically engineered insect-resistant crops were introduced at a time when insecticide options and use patterns were changing. Management of lepidopteran and coleopteran pests has been achieved through constitutive expression of proteins derived from the crystalline spore and the vegetative stage of various strains of Bacillus thuringiensis. Management to aphid-transmitted viruses has been achieved through expression of viral coat proteins. Adoption patterns have been rapid where use is allowed. Areawide reductions in pest populations have occurred in cotton and maize in multiple parts of the world, enabled eradication programs, and conferred significant economic benefits to crops that are not transgenic. Insecticide use has decreased dramatically in cotton, leading to improved biological control, reductions in pesticide poisonings, and changes in species composition that achieve pest status. Pro-active resistance management programs, the first to be deployed in all of agriculture, has slowed but not stopped the evolution of resistant populations. Five insect pest species have evolved resistance. Future constructs may provide induced or tissue-specific expression, or use RNAi to deliver protection from S.J. Fleischer ( ) Department of Entomology, The Pennsylvania State University, University Park, State College, PA, USA e-mail: Shelby.fleischer@gmail.com W.D. Hutchison Department of Entomology, University of Minnesota, Minneapolis, MN, USA e-mail: Hutch002@umn.edu S.E. Naranjo USDA-ARS, Arid-Land Agricultural Research Center, Maricopa, AZ, USA e-mail: Steve.naranjo@ars.usda. gov A. Ricroch et al. (eds.), Plant Biotechnology: Experience and Future Prospects, DOI 10.1007/978-3-319-06892-3__10, © Springer International Publishing Switzerland 2014 115 116 S.J. Fleischer et al. insect pests. Constructs that alter plant metabolism, to achieve drought tolerance, nitrogen-utilization, or biomass conversion efficiency, may also affect insect populations and communities. Sustainable management of insect-resistant transgenic crops requires consideration of regional effects of both densities and genetics of mobile target insect populations. The underlying assumption of IPM, that multiple and diverse management tactics are more sustainable, continues to be highly relevant, and necessary, to maintain the utility of transgenic crops, to manage the wider community of species relevant to agroecosystems, and to enable agriculture to adapt to change.
Effects of pre-consultation lists on the communicative behavior of children with cancer and their caregivers

This cross-sectional study present effects of pre-consultation lists on caregivers' and children's communicative behavior. Thirty-two dyads caregiver-child took part in this research, divided in three groups concerning the study design: Baseline 1, Intervention phase, and Baseline 2. Children and caregivers were individually interviewed before consultations on pediatric cancer treatment, in order to list doubts, expectations, and estimated issues to the medical visit. These themes were written down on a sheet of paper, attached to the child´s medical record cover, and would then be used as a memo in the following consultation. Results show that pre-consultation lists produced no effects on children's behavior, however the procedure was associated to specific doubts discussed by caregivers regarding dietary recommendations, coping with side effects, child development, biological aspects of cancer, and school activities. This study presents a low cost procedure that may contribute to tailor communication in pediatric settings.
Waves Interacting on an Annulus, with a Fibonacci style resonance

Building on a DatH report by Ken Monks, we investigate the existence of equilibria in dynamical systems governing the (complex-valued) amplitudes of waves. The waves interact with a Fibonacci-style resonance; that is, there is a recursive structure. Using the Numerical Algebraic Geometry software Bertini, we attempt to nd the equilibria of the the system, and subsequently classify by stability.
FACTORS RESPONSIBLE FOR THE HIGH FREQUENCY OF WEST NILE NEUROINVASIVE DISEASE IN RECENT URBAN OUTBREAKS

SIMONA MARIA RUŢĂ and COSTIN CERNESCU “St. Nicolau” Institute of Virology, 285, Sos Mihai Bravu, Bucharest 030304, Romania E-mail: simonaruta@b.astral. ro and cernescu@valhalla.racai. ro Received August 29, 2007 A computerized search of the Medline database from January 1997 to August 2006 for all human West Nile Virus (WNV) outbreaks in European countries and United States was performed using specific key words. Also unpublished aspects present in ArboNet reports were reviewed (www.cdc.gov/WestNile). Three European and five North American urban outbreaks were identified. Detailed clinical descriptions were available for many of these outbreaks. The predominance of WN neurological disease (WNND) was reflected in hospital based surveillance reports. Analysis of surveillance data from WNV urban outbreaks suggests a direct correlation between the number of target susceptible population and frequency of WNND. We explain the higher rate of WNND in the context of urban epidemics by amplification of WNV in human-mosquito-human cycle without previous amplification in a sylvatic cycle by the ornithophilic mosquitoes. WNV can be inter-human transmitted by mosquito vectors (Culex pipiens). At each homologous host passage virus acquires an increased human tropism which favours a higher viremic titer and neurovirulence. Key words: West Nile Virus; WN neurological disease; Urban outbreaks.
ENERGY AWARE SECURITY ALGORITHM DECISION METHOD FOR INTERNET OF THINGS USING SSL/TLS FOR WIRELESS NETWORK

The Internet of Things (IoT) is an ever evolving infrastructure of physical objects and Internet-enabled devices and systems featuring IP addresses for connectivity. Physical objects consist of home appliances, electronic gadgets, machinery, healthcare items, wearable devices and anything that could be connected to the Internet. Each type of connection requires particular types of security service. Security algorithms in user devices are fixed by default and selected based on preferences. This limitation causes energy waste since a user might be using all services in an algorithm, even those the user does not need. In order to counter this problem, we propose an energy aware security service selection method that saves energy by selecting only particular types of security service required by a given connection. In this paper, we compared the energy consumption of each communication to provide integrity, authentication, and confidentiality in Secure Sockets Layer/Transport Layer Security (SSL/TLS) with our proposed method. The experimental results demonstrate the validity of our proposed method. Our proposed method saved 54.94% energy for integrity and 74.52% for authentication.
Arch ī um Ateneo Arch um Ateneo

Augmented Reality (AR) is a technology that allows the superimposition of virtual objects onto the real world environment. Various fields, such as education, medicine, and architecture, have started adapting AR technology. However, developing AR applications, along with their contents, requires a specific skillset, which limits the number of AR-based applications that can be developed. Various authoring tools are available for desktop systems to ease the development of AR applications and content, yet only few attempts have been made to develop these kinds of tools for mobile systems. This paper describes a mobile application that allows users to author content for AR viewing using 2D images. Furthermore, the tool allows users to produce and to edit AR content on the spot. After the application was developed, a usability test was conducted with eight teachers in order to assess the difficulty of using the application. The user testing showed that the application developed was generally easy to use, and that further addition of features can improve the application.
Matchings in k‐partite k‐uniform hypergraphs

For k≥3 and ϵ>0 , let H be a k ‐partite k ‐graph with parts V1,…,Vk each of size n , where n is sufficiently large. Assume that for each i∈[k] , every (k−1) ‐set in ∏j∈[k]\{i}Vj lies in at least ai edges, and a1≥a2≥⋯≥ak . We show that if a1,a2≥ϵn , then H contains a matching of size min{n−1,∑i∈[k]ai} . In particular, H contains a matching of size n−1 if each crossing (k−1) ‐set lies in at least ⌈n/k⌉ edges, or each crossing (k−1) ‐set lies in at least ⌊n/k⌋ edges and n≡1modk . This special case answers a question of Rödl and Ruciński and was independently obtained by Lu, Wang, and Yu. The proof of Lu, Wang, and Yu closely follows the approach of Han by using the absorbing method and considering an extremal case. In contrast, our result is more general and its proof is thus more involved: it uses a more complex absorbing method and deals with two extremal cases.
Cerebrovascular Spasm Following Subarachnoid Haemorrhage: Is Sildenafil Promising?

Some recent research studies suggest Sildenafil can be an option for management of CVS. Mechanism of Sildenafil action is that it inhibits phosphodiesterase 5 (responsible for cGMP breakdown) resulting in accumulation of cGMP and subsequent protein kinas activation with decreasing calcium levels and smooth muscles relaxation. Other animal studies are showing sildenafil effects on CVS: reversal of CVS, improving angiogenesis, improving neurological outcome, decreasing endothelin 1 (vasoconstrictor) [2].
Assessment of Heavy Metals, pH, Organic Matter and Organic Carbon in Roadside Soils in Makurdi Metropolis, Benue State, Nigeria

Roadside soil samples were collected from four sites (heavy traffic area (Wurukum); industrial site (Gboko road); residential area (Federal Lowcost) and FederalMedicalCenter(Wadata) representing different activities across the Benue Metropolis. At each of the sample site, roadside soils were collected at different distance from the edge of the main road (2, 10, 30, 40 and 60 meters). In each of the distance, roadside soil were collected at three depth of 0 -1 cm, 2 -4 cmand 4 - 6 cm for the determination of pH, organic matter, organic carbon, Cu, Cd, Fe, Pb, As, Mn, Zn, Cd and Ni. pH, electrical conductivity (EC), organic matter and organic carbon were determined using standard procedures, while heavy metals were determined using Perkin-Elmer Analyst 300 Atomic Absorption spectroscopy (AAS). Zinc was observed to show the higher levels in all the sampling sites, such higher level can be related back to the wear-and-tear of vehicle components as a result of the stop-start traffic patterns and brake pads. The concentrations of all the metals in the four sampling sites decreased exponentially with distance from the edge of the road and dropped to the minimum levels at about 60 meters. Similarly, mean concentrations of Cu, Fe, Pb, As, Mn, Zn, Cd and Ni were significantly higher around the industrial area (Gboko road) and heavy traffic (Wurunkum) areas than other sampling areas followed an increasing trend with the increase in depth. The vertical movement of all the metals, exhibited predominant association with soil pH and organic carbon. From the results of this study, the pH of the roadside soils from all the sampling points ranged from 4.56 to 7.71, which enhances increased of heavy metals down the soil profiles. Organic carbon content ranged of 0.27% to 5.44% across all the sampling points appears to increase the mobility of all the metals to a depth6 cm. The values of the heavy metals suggest that automobiles and traffic activities are a major source of these metals in the roadside soil within the study area. Also, with the exception of Pb, Fe and Cd, the levels of Cu, As, Mn, Zn and Ni in the present study were lower as compared with results found by other researcher in various countries worldwide.
Fungi as a Biotransformation Tool in Patchouli (Pogostemon patchouli Pellet) Essential Oil

Five and half month old crop was harvested, sprayed with fifteen combinations of five fungi isolated from the rhizosphere of patchouli and incubated for five days. The essential oil was extracted by hydrodistillation and analysed by Gas Chromatography. The components of patchouli oil were identified by Gas chromatography/Mass Spectrometry (GC/MS). Twenty compounds were identified with Patchouli alcohol as the major component followed by α bulnesene. The oil content was in the range 1-1.65 %( v/w) on fresh weight basis. Treatment T2 (Aspergillus terreus) was found to be statistically superior with high patchouli alcohol (58.72±0.39) and low amount of other sesquiterpenes (trans-caryophyllene (2.21±0.05), Guaiene (9.89±0.43), α-Patchoulene (2.56±0.04) and α-Bulnesene (8.43±0.8). This indicated an enzymatic bioconversion of precursor molecules to patchouli alcohol by the fungi.
Lactobacillus and Bifidobacteria Probiotic Strains Improve Glycemic and Inflammation Profiles in Obesity Model in Mice

Introduction. The use of probiotics demonstrate efficacy against obesity and metabolic syndrome (MetS). Detection effective probiotic strains for hyperglycemia and immunity associated with is important task. The aim of the study was to evaluate an influence of Lactobacillus casei IMV B-7280 separately and composition L. casei IMV B-7280 / Bifidobacterium animalis VKB / B. animalis VKL on the levels of blood glucose and immunity in obese mice. Meterials and methods. Obesity was induced by fat-enriched diet (FED) in male BALB/c mice. Obese mice were transferred to standard diet and received per os probiotic strains daily during 10 days. We measured tumor necrosis factor-a (TNF-a) in blood serum using enzyme-linked immunosorbent assay and functional activity of peritoneal exudate macrophages (PEMs). Glucose levels in blood was defined with glucometer. Results. We ascertained that all probiotic strains induced reducing mice weight and visceral fat, normalization of TNF-a production and functional activity of PEMs. Treatment with L. casei IMV B-7280 was associated with decreasing blood glucose levels. No normalization of glucose and TNF-a levels in obese mice, transferred to standard diet without probiotic treatment, although we revealed decreasing their weight and visceral fat and partial recover of functional activity of PEMs. Conclusions. Probiotic strain L. casei IMV B-7280 (separately) and composition L. casei IMV B-7280 / B. animalis VKB / B. animalis VKL can re-equilibrate metabolic and inflammation indices in mouse obesity model. L. casei IMV B-7280 alone was more efficient in decreasing glucose levels than composition of strains.
Using Vine Copulas to Generate Representative System States for Machine Learning

The increasing uncertainty that surrounds electricity system operation renders security assessment a highly challenging task; the range of possible operating states expands, rendering traditional approaches based on heuristic practices and ad hoc analysis obsolete. In turn, machine learning can be used to construct surrogate models approximating the system's security boundary in the region of operation. To this end, past system history can be useful for generating anticipated system states suitable for training. However, inferring the underlying data model, to allow high-density sampling, is problematic due to the large number of variables, their complex marginal probability distributions and the nonlinear dependence structure they exhibit. In this paper, we adopt the C-Vine pair-copula decomposition scheme; clustering and principal component transformation stages are introduced, followed by a truncation to the pairwise dependency modeling, enabling efficient fitting and sampling of large datasets. Using measurements from the French grid, we show that a machine learning training database sampled from the proposed method can produce binary security classifiers with superior predictive capability compared to other approaches.
Hypercementosis: a challenge for endodontic therapy

Introduction and objective: The purpose of this study was to describe through literature review, the morphological characteristics of teeth with hypercementosis that are relevant to endodontic practice. Literature review: The pathologic deposition of cement increases proportionally as the patient’s age increases. Genetic factors seem to be related to hypercementosis occurrence in young patients. Based on literature, it is possible to notice a lack of scientific studies which guide the endodontist for treating teeth with hypercementosis, since the cement deposition lead to the length increase of the cementum canal, and consequently, to the increase of the distance from CDC junction to apical root end. Conclusion: Thus, it is clinically relevant to correlate the morphology of teeth with hypercementosis with the specific aspects of endodontic therapy, aiming to establish the limits of root canal treatment in cases of hypercementosis.
Cardiovascular disease determinants: Burden and knowledge among women in a rural community of Delhi

Background: Cardiovascular diseases (CVDs) are becoming major health burden in developing countries such as India. Rural women are reported to have high CVD-related mortality rates and are less likely to receive appropriate treatment. Objective: To assess knowledge, practices, and burden of CVD-related risk factors among women in a rural area of Delhi. Materials and Methods: A cross-sectional study was conducted at Pooth Khurd village, a rural pocket situated in northwest district of Delhi through house-to-house survey by two investigators. A total of 100 women above 18 years of age and resident of the village were included in the study using systematic random sampling technique. A pretested interview schedule, containing items to assess knowledge and practices regarding CVDs and risk factors based on various validated tools, was used. Fischer’s exact and Pearson’s correlation tests were applied; tests were two sided with p-value below 0.05 considered significant. Results: Poor CVD knowledge was seen among study participants with less than half of subjects identifying family history (24%), tobacco and alcohol intake (48%, 47%), and so forth as risk factors for CVDs. High burden of risk factors, such as high salt intake (35%), inadequate physical activity (77%), and raised blood sugar (5%), and poor health-seeking behavior were observed. Conclusion: This study reflects poor knowledge and relatively high burden of CVD risk factors among rural women. Poor knowledge is predictive of high CVD risk in community settings.
An LSTM-CRF Based Approach to Token-Level Metaphor Detection

Automatic processing of figurative languages is gaining popularity in NLP community for their ubiquitous nature and increasing volume. In this era of web 2.0, automatic analysis of sarcasm and metaphors is important for their extensive usage. Metaphors are a part of figurative language that compares different concepts, often on a cognitive level. Many approaches have been proposed for automatic detection of metaphors, even using sequential models or neural networks. In this paper, we propose a method for detection of metaphors at the token level using a hybrid model of Bidirectional-LSTM and CRF. We used fewer features, as compared to the previous state-of-the-art sequential model. On experimentation with VUAMC, our method obtained an F-score of 0.674.
Do the dependency conflicts in my project matter?

Intensive dependencies of a Java project on third-party libraries can easily lead to the presence of multiple library or class versions on its classpath. When this happens, JVM will load one version and shadows the others. Dependency conflict (DC) issues occur when the loaded version fails to cover a required feature (e.g., method) referenced by the project, thus causing runtime exceptions. However, the warnings of duplicate classes or libraries detected by existing build tools such as Maven can be benign since not all instances of duplication will induce runtime exceptions, and hence are often ignored by developers. In this paper, we conducted an empirical study on real-world DC issues collected from large open source projects. We studied the manifestation and fixing patterns of DC issues. Based on our findings, we designed Decca, an automated detection tool that assesses DC issues' severity and filters out the benign ones. Our evaluation results on 30 projects show that Decca achieves a precision of 0.923 and recall of 0.766 in detecting high-severity DC issues. Decca also detected new DC issues in these projects. Subsequently, 20 DC bug reports were filed, and 11 of them were confirmed by developers. Issues in 6 reports were fixed with our suggested patches.
Streaming Graph Partitioning: An Experimental Study

Graph partitioning is an essential yet challenging task for massive graph analysis in distributed computing. Common graph partitioning methods scan the complete graph to obtain structural characteristics offline, before partitioning. However, the emerging need for low-latency, continuous graph analysis led to the development of online partitioning methods. Online methods ingest edges or vertices as a stream, making partitioning decisions on the fly based on partial knowledge of the graph. Prior studies have compared offline graph partitioning techniques across different systems. Yet, little effort has been put into investigating the characteristics of online graph partitioning strategies. In this work, we describe and categorize online graph partitioning techniques based on their assumptions, objectives and costs. Furthermore, we employ an experimental comparison across different applications and datasets, using a unified distributed runtime based on Apache Flink. Our experimental results showcase that model-dependent online partitioning techniques such as low-cut algorithms offer better performance for communication-intensive applications such as bulk synchronous iterative algorithms, albeit higher partitioning costs. Otherwise, model-agnostic techniques trade off data locality for lower partitioning costs and balanced workloads which is beneficial when executing data-parallel single-pass graph algorithms.
Multimodal Neural Machine Translation for Low-resource Language Pairs using Synthetic Data

In this paper, we investigate the effectiveness of training a multimodal neural machine translation (MNMT) system with image features for a low-resource language pair, Hindi and English, using synthetic data. A three-way parallel corpus which contains bilingual texts and corresponding images is required to train a MNMT system with image features. However, such a corpus is not available for low resource language pairs. To address this, we developed both a synthetic training dataset and a manually curated development/test dataset for Hindi based on an existing English-image parallel corpus. We used these datasets to build our image description translation system by adopting state-of-the-art MNMT models. Our results show that it is possible to train a MNMT system for low-resource language pairs through the use of synthetic data and that such a system can benefit from image features.