Miracle-dz/UniFAR-FTUs huggingface dataset:
Heterologous Packaging Signals on Segment 4, but Not Segment 6 or Segment 8, Limit Influenza A Virus Reassortment

ABSTRACT Influenza A virus (IAV) RNA packaging signals serve to direct the incorporation of IAV gene segments into virus particles, and this process is thought to be mediated by segment-segment interactions. These packaging signals are segment and strain specific, and as such, they have the potential to impact reassortment outcomes between different IAV strains. Our study aimed to quantify the impact of packaging signal mismatch on IAV reassortment using the human seasonal influenza A/Panama/2007/99 (H3N2) and pandemic influenza A/Netherlands/602/2009 (H1N1) viruses. Focusing on the three most divergent segments, we constructed pairs of viruses that encoded identical proteins but differed in the packaging signal regions on a single segment. We then evaluated the frequency with which segments carrying homologous versus heterologous packaging signals were incorporated into reassortant progeny viruses. We found that, when segment 4 (HA) of coinfecting parental viruses was modified, there was a significant preference for the segment containing matched packaging signals relative to the background of the virus. This preference was apparent even when the homologous HA constituted a minority of the HA segment population available in the cell for packaging. Conversely, when segment 6 (NA) or segment 8 (NS) carried modified packaging signals, there was no significant preference for homologous packaging signals. These data suggest that movement of NA and NS segments between the human H3N2 and H1N1 lineages is unlikely to be restricted by packaging signal mismatch, while movement of the HA segment would be more constrained. Our results indicate that the importance of packaging signals in IAV reassortment is segment dependent. IMPORTANCE Influenza A viruses (IAVs) can exchange genes through reassortment. This process contributes to both the highly diverse population of IAVs found in nature and the formation of novel epidemic and pandemic IAV strains. Our study sought to determine the extent to which IAV packaging signal divergence impacts reassortment between seasonal IAVs. Our knowledge in this area is lacking, and insight into the factors that influence IAV reassortment will inform and strengthen ongoing public health efforts to anticipate the emergence of new viruses. We found that the packaging signals on the HA segment, but not the NA or NS segments, restricted IAV reassortment. Thus, the packaging signals of the HA segment could be an important factor in determining the likelihood that two IAV strains of public health interest will undergo reassortment.
Genetic regulation of Corynebacterium glutamicum metabolism

Physiological, biochemical and genetic studies of Corynebacterium glutamicum, a workhorse of white biotechnology used for amino acid production, led to a waste knowledge mainly about amino acid biosynthetic pathways and the central carbon metabolism of this bacterium. Spurred by the availability of the genome sequence and of genome-based experimental methods such as DNA microarray analysis, research on genetic regulation came into focus. Recent progress on mechanisms of genetic regulation of the carbon, nitrogen, sulfur and phosphorus metabolism in C. glutamicum will be discussed.
Accuracy improvement in sensor localization system utilizing heterogeneous wireless technologies

Sensor localization is one of the big problems when building large scale indoor sensor networks because GPS (Global Positioning System) is unavailable in indoor environments. We are developing ZigLoc, a sensor localization system using WiFi APs (access points) as references, which requires no additional infrastructure [1,2]. In ZigLoc, a sensor node measures RSS (received signal strength) of WiFi AP signals using a ZigBee (IEEE 802.15.4) module. Location of a sensor node is then estimated using fingerprints collected for a WiFi localization system. However, ZigLoc exhibits low accuracy due to the RSS offset derived by ZigBee and WiFi modules. The RSS offset is mainly caused by the channel bandwidth difference. In this paper, we present a differential fingerprinting method to improve localization accuracy. Our key idea is that we focus on RSS difference between WiFi APs. RSS difference between APs should be the same when we measure RSS using either ZigBee or WiFi modules. Differential fingerprinting only relies on RSS difference in fingerprint similarity calculation. We conducted experimental evaluations in a practical environment. The experimental evaluations reveal that ZigLoc accuracy was improved by approximately 26 % using the differential fingerprinting method.
Understanding farmers' perceptions and adaptations to climate change and variability: The case of the Limpopo Basin, South Africa

"Climate change is expected to have serious environmental, economic, and social impacts on South Africa. In particular, rural farmers, whose livelihoods depend on the use of natural resources, are likely to bear the brunt of adverse impacts. The extent to which these impacts are felt depends in large part on the extent of adaptation in response to climate change. This research uses a “bottom-up” approach, which seeks to gain insights from the farmers themselves based on a farm household survey. Farm-level data were collected from 794 households in the Limpopo River Basin of South Africa for the farming season 2004–2005. The study examines how farmer perceptions correspond with climate data recorded at meteorological stations in the Limpopo River Basin and analyzes farmers' adaptation responses to climate change and variability. A Heckman probit model and a multinomial logit (MNL) model are used to examine the determinants of adaptation to climate change and variability. The statistical analysis of the climate data shows that temperature has increased over the years. Rainfall is characterized by large interannual variability, with the previous three years being very dry. Indeed, the analysis shows that farmers' perceptions of climate change are in line with the climatic data records. However, only approximately half of the farmers have adjusted their farming practices to account for the impacts of climate change. Lack of access to credit was cited by respondents as the main factor inhibiting adaptation. The results of the multinomial logit and Heckman probit models highlighted that household size, farming experience, wealth, access to credit, access to water, tenure rights, off-farm activities, and access to extension are the main factors that enhance adaptive capacity. Thus, the government should design policies aimed at improving these factors. " from authors' abstract
Evaluation of a complex intervention (Engager) for prisoners with common mental health problems, near to and after release: study protocol for a randomised controlled trial

Introduction The ‘Engager’ programme is a ‘through-the-gate’ intervention designed to support prisoners with common mental health problems as they transition from prison back into the community. The trial will evaluate the clinical and cost-effectiveness of the Engager intervention. Methods and analysis The study is a parallel two-group randomised controlled trial with 1:1 individual allocation to either: (a) the Engager intervention plus standard care (intervention group) or (b) standard care alone (control group) across two investigation centres (South West and North West of England). Two hundred and eighty prisoners meeting eligibility criteria will take part. Engager is a person-centred complex intervention delivered by practitioners and aimed at addressing offenders’ mental health and social care needs. It comprises one-to-one support for participants prior to release from prison and for up to 20 weeks postrelease. The primary outcome is change in psychological distress measured by the Clinical Outcomes in Routine Evaluation-Outcome Measure at 6 months postrelease. Secondary outcomes include: assessment of subjective met/unmet need, drug and alcohol use, health-related quality of life and well-being-related quality of life measured at 3, 6 and 12 months postrelease; change in objective social domains, drug and alcohol dependence, service utilisation and perceived helpfulness of services and change in psychological constructs related to desistence at 6 and 12 months postrelease; and recidivism at 12 months postrelease. A process evaluation will assess fidelity of intervention delivery, test hypothesised mechanisms of action and look for unintended consequences. An economic evaluation will estimate the cost-effectiveness. Ethics and dissemination This study has been approved by the Wales Research Ethics Committee 3 (ref: 15/WA/0314) and the National Offender Management Service (ref: 2015–283). Findings will be disseminated to commissioners, clinicians and service users via papers and presentations. Trial registration number ISRCTN11707331; Pre-results.
Increase in water resistance of paperboard by coating with poly(lactide)

Poly(lactide) (PLA)‐coated paperboards (PB) were prepared, and the effect of coating for improving water resistance of paperboard used for corrugated box liners was tested. Surface of paperboards became smoother through PLA coating, and their thickness and weight of coating increased depending on the concentration of the coating solution. Tensile strength of paperboard decreased, while elongation at break (E) increased after PLA coating. All water barrier properties tested, such as water vapour permeability (WVP), water absorptiveness (WA) and contact angle (CA) of water drop, indicated that water resistance of paperboard was improved through surface coating with PLA. WVP decreased from 4.8 to 25.5 times, and WA decreased from 11.9 to 17.9 times depending on the PLA concentration. The increase in water resistance of PLA‐coated paperboards was due to the hydrophobicity of PLA, which was proven through CA measurement. CA determined by both static and dynamic methods demonstrated the increase in initial CA of PLA‐coated paperboards, indicating an increased hydrophobicity of surface. All test results indicated that the optimum concentration of coating solution for improving water resistance of paperboard was 3 w/v % of PLA soulution. Copyright © 2007 John Wiley & Sons, Ltd.
Activity Monitoring and Heart Rate Variability as Indicators of Fall Risk: Proof-of-Concept for Application of Wearable Sensors in the Acute Care Setting.

Growing concern for falls in acute care settings could be addressed with objective evaluation of fall risk. The current proof-of-concept study evaluated the feasibility of using a chest-worn sensor during hospitalization to determine fall risk. Physical activity and heart rate variability (HRV) of 31 volunteers admitted to a 29-bed adult inpatient unit were recorded using a single chest-worn sensor. Sensor data during the first 24-hour recording were analyzed. Participants were stratified using the Hendrich II fall risk assessment into high and low fall risk groups. Univariate analysis revealed age, daytime activity, nighttime side lying posture, and HRV were significantly different between groups. Results suggest feasibility of wearable technology to consciously monitor physical activity, sleep postures, and HRV as potential markers of fall risk in the acute care setting. Further study is warranted to confirm the results and examine the efficacy of the proposed wearable technology to manage falls in hospitals. [Journal of Gerontological Nursing, 43(7), 53-62. ].
Paraphrase and Textual Entailment Generation in Czech

Paraphrase and textual entailment generation can support natural language processing (NLP) tasks that simulate text understanding, e.g., text summarization, plagiarism detection, or question answering. A paraphrase, i.e., a sentence with the same meaning, conveys a certain piece of information with new words and new syntactic structures. Textual entailment, i.e., an inference that humans will judge most likely true, can employ real-world knowledge in order to make some implicit information explicit. Paraphrases can also be seen as mutual entailments. We present a new system that generates paraphrases and textual entailments from a given text in the Czech language. First, the process is rule-based, i.e., the system analyzes the input text, produces its inner representation, transforms it according to transformation rules, and generates new sentences. Second, the generated sentences are ranked according to a statistical model and only the best ones are output. The decision whether a paraphrase or textual entailment is correct or not is left to humans. For this purpose we designed an annotation game based on a conversation between a detective (the human player) and his assistant (the system). The result of such annotation is a collection of annotated pairs text–hypothesis. Currently, the system and the game are intended to collect data in the Czech language. However, the idea can be applied for other languages. So far, we have collected 3,321 H–T pairs. From these pairs, 1,563 were judged correct (47.06 %), 1,238 (37.28 %) were judged incorrect entailments, and 520 (15.66 %) were judged non-sense or unknown.
Timing and context of dolphin clicks during and after mine simulator detection and marking in the open ocean

ABSTRACT Two dolphins carrying cameras swam in the ocean as they searched for and marked mine simulators – buried, proud or moored. As the animals swam ahead of a boat they searched the ocean. Cameras on their harness recorded continuous sound and video. Once a target was detected, the dolphins received a marker to take to the simulator's location. During search and detection, dolphins made almost continuous trains of varying interval clicks. During the marking phase, shorter click trains were interrupted by periods of silence. As the dolphins marked simulators, they often produced victory squeals – pulse bursts that vary in duration, peak frequency and amplitude. Victory squeals were produced on 72% of marks. Sometimes after marking, or at other times during their long swims, the dolphins produced click packets. Packets typically consisted of two to 10 clicks with inter-click intervals of 7-117 ms followed by a silence of 223-983 ms. Click packets appeared unrelated with searching or marking. We suggest that the packets were used to improve signal to noise ratios for locating a boat or other distant object. Victory squeals produced when marking the targets suggest to us that the dolphins know when they have succeeded in this multipart task. Summary: Dolphins wore cameras so we could hear them and watch them mark mine simulators. We observed rhythmic click trains, victory squeals, and click packets with their behavioral context.
Blood Lead Levels and Risk Factors for Lead Exposure in a Pediatric Population in Ho Chi Minh City, Vietnam

Although lead recycling activities are a known risk factor for elevated blood levels in South East Asia, little is known regarding the prevalence of and risk factors for elevated blood lead levels (BLL) among the general pediatric population in Vietnam. This study is a cross-sectional evaluation of 311 children from Children’s Hospital #2 in Ho Chi Minh City, Vietnam. Capillary blood lead testing was performed using the LeadCare II. Mean BLLs were 4.97 μg/dL (Standard Deviation (SD) 5.50), with 7% of the participants having levels greater than 10 μg/dL. Living in Bing Duong province (OR 2.7, 95% CI 1.4–5.6.1) or the Dong Nai province (OR 2.3, 95% CI 1.0–5.1) and having an age greater than 12 months (OR 6.0, 95% CI 3.1–11.8) were associated with higher BLLs. The prevalence of elevated BLLs in Vietnam is consistent with other SE Asian countries. Mean BLLs in Ho Chi Minh City are markedly less than those seen in a separate study of children living near lead recycling activities. Additional evaluation is necessary to better detail potential risk factors if screening is to be implemented within Vietnam.
Finding Expert Authors in Financial Forum Using Deep Learning Methods

The modern stock market is a popular place to increase wealth and generate income, but the fundamental problem of when to buy or sell shares, or which stocks to buy has not been solved. It is very common among investors to have professional financial advisers, but what is the best resource to support the decisions these people make? Investment banks, such as Goldman Sachs, Lehman Brothers, and Salomon Brothers have dominated the world of financial advice for decades. However, due to the popularity of the Internet and financial social networks, such as StockTwits and Seeking Alpha, investors around the world have a new opportunity to gather and share their experiences. This raises new questions: is the information these users provide trustworthy? How can we find the experts? In this paper, we seek to determine if neural network models can help us find the experts in a set of StockTwits tweets. We applied two neural network models - doc2vec and convolutional neural networks - to find top authors in StockTwits based on their messages. Our results showed that a convolutional neural network is the best model to predict such top authors in this data set.
An invasive foundation species enhances multifunctionality in a coastal ecosystem

Significance The accelerating loss of coastal foundation species impairs the delivery of vital ecosystem services on which nearly half the human population depends. Recognizing how loss of habitat-forming species such as seagrasses and oysters can be offset is therefore essential. This paper demonstrates that in areas where native foundation species are absent, nonnative habitat formers can amplify the production of diverse ecosystem functions that underpin provisioning of services to humans, such as food production. Our findings suggest that in areas where native foundation species have been lost, invasive habitat formers may be considered as a tool to enhance multiple ecosystem functions. While invasive species often threaten biodiversity and human well-being, their potential to enhance functioning by offsetting the loss of native habitat has rarely been considered. We manipulated the abundance of the nonnative, habitat-forming seaweed Gracilaria vermiculophylla in large plots (25 m2) on southeastern US intertidal landscapes to assess impacts on multiple ecosystem functions underlying coastal ecosystem services. We document that in the absence of native habitat formers, this invasion has an overall positive, density-dependent impact across a diverse set of ecosystem processes (e.g., abundance and richness of nursery taxa, flow attenuation). Manipulation of invader abundance revealed both thresholds and saturations in the provisioning of ecosystem functions. Taken together, these findings call into question the focus of traditional invasion research and management that assumes negative effects of nonnatives, and emphasize the need to consider context-dependence and integrative measurements when assessing the impact of an invader, including density dependence, multifunctionality, and the status of native habitat formers. This work supports discussion of the idea that where native foundation species have been lost, invasive habitat formers may be considered as sources of valuable ecosystem functions.
Towards Multiple Kernel Principal Component Analysis for Integrative Analysis of Tumor Samples

Abstract Personalized treatment of patients based on tissue-specific cancer subtypes has strongly increased the efficacy of the chosen therapies. Even though the amount of data measured for cancer patients has increased over the last years, most cancer subtypes are still diagnosed based on individual data sources (e.g. gene expression data). We propose an unsupervised data integration method based on kernel principal component analysis. Principal component analysis is one of the most widely used techniques in data analysis. Unfortunately, the straightforward multiple kernel extension of this method leads to the use of only one of the input matrices, which does not fit the goal of gaining information from all data sources. Therefore, we present a scoring function to determine the impact of each input matrix. The approach enables visualizing the integrated data and subsequent clustering for cancer subtype identification. Due to the nature of the method, no hyperparameters have to be set. We apply the methodology to five different cancer data sets and demonstrate its advantages in terms of results and usability.
Location information aided beam allocation algorithm in mmWave massive MIMO systems

Millimeter wave (mmWave) band exhibits large bandwidth availability and meets the demands for high data rate of the fifth generation cellular networks (5G). However, mmWave signals suffer from severe path loss. Beamforming technology provides high array gain to overcome this limitation. Before data connection procedure, mmWave base stations (BSs) need to search for the suitable serving beams aiming at user equipments (UEs). This searching process is typically completed in the initial access procedure and causes fatal delays. Therefore, a reasonable beam allocation algorithm (BAA) is essential to speed up initial access procedure. In this paper, a support vector machine based beam allocation algorithm (SVM-BAA) is proposed, which utilizes location information and absorbs the thought of supervised learning. It constructs a SVM multi-classifier by using location information as features and serving beams as classes. When new UEs attempt to get access to mmWave BSs, their serving beams are allocated according to the decision results of SVM multi-classifier. Simulation results show that the proposed SVM-BAA can reduce the initial access delay compared with existing methods when there's enough previous location information.
Supporting exploratory code search with differencing and visualization

Searching and reusing online code has become a common practice in software development. Two important characteristics of online code have not been carefully considered in current tool support. First, many pieces of online code are largely similar but subtly different. Second, several pieces of code may form complex relations through their differences. These two characteristics make it difficult to properly rank online code to a search query and reduce the efficiency of examining search results. In this paper, we present an exploratory online code search approach that explicitly takes into account the above two characteristics of online code. Given a list of methods returned for a search query, our approach uses clone detection and code differencing techniques to analyze both commonalities and differences among the methods in the search results. It then produces an exploration graph that visualizes the method differences and the relationships of methods through their differences. The exploration graph allows developers to explore search results in a structured view of different method groups present in the search results, and turns implicit code differences into visual cues to help developers navigate the search results. We implement our approach in a web-based tool called CodeNuance. We conduct experiments to evaluate the effectiveness of our CodeNuance tool for search results examination, compared with ranked-list and code-clustering based search results examination. We also compare the performance and user behavior differences in using our tool and other exploratory code search tools.