Miracle-dz/UniFAR-FTUs huggingface dataset:
Wired and Wireless Network Cooperation for Wide-Area Quick Disaster Recovery

It is a significant challenge for telecommunication network operators to immediately restore communication services in the disaster area. To quickly recover telecommunication services in the affected area, this paper proposes a wired and wireless network cooperation system. When the wired communication for leaf nodes of optical tree networks is disrupted, surviving leaf nodes relay packets to and from these nodes via wireless bypass routes. The advantages of the proposed method are promptness and high-throughput, which is achieved with single-hop wireless bypass routes backhauled by wired networks. The optimal routes for wireless links are calculated to maximize the expected throughput by solving a binary integer programming problem. The proposed system is cost effective, because it can be deployed with minimum additional functions for leaf nodes of optical networks. To overcome the limitation of the proposed approach that the distribution of leaf nodes is determined by the demand distribution, additional recovery nodes can be deployed to improve the expected throughput. The numerical simulations including a medium access control level simulation conducting carrier sense multiple access with collision avoidance behavior showed that the proposed method can achieve a higher throughput than an existing bypass routing method, irrespective of the topology of the wired networks.
Dataflow representation of data analyses: Toward a platform for collaborative data science

Data science plays an increasingly important role in solving today's scientific and social challenges. To promote progress toward a cure for multiple sclerosis, the Accelerated Cure Project has created an open repository of biological and survey data on patients with multiple sclerosis. Similar large-scale repositories are being created in other domains. As the open, data-driven model of science proliferates, the research community faces a growing need for a cloud platform for collaborative data science. Such a platform should facilitate collaboration between domain experts and data scientists and possess artificial intelligence capabilities for organizing, recommending, and manipulating data analyses. In this paper, we present some foundational technologies motivated by this vision. Our system automatically extracts a high-level dataflow graph from a data analysis. This graph describes how data flows through an analysis pipeline, including which statistical methods are used and how they fit together. The system requires no special annotations from the data analyst and consumes analyses written in Python using standard tools, such as Scikit-learn and Statsmodels. In this paper, we explain how our system works and how it fits into our larger vision for a collaborative data science platform.
Characterization of metabolic responses to healthy diets and association with blood pressure: application to the Optimal Macronutrient Intake Trial for Heart Health (OmniHeart), a randomized controlled study.

Background Interindividual variation in the response to diet is common, but the underlying mechanism for such variation is unclear. Objective The objective of this study was to use a metabolic profiling approach to identify a panel of urinary metabolites representing individuals demonstrating typical (homogeneous) metabolic responses to healthy diets, and subsequently to define the association of these metabolites with improvement of risk factors for cardiovascular diseases (CVDs). Design 24-h urine samples from 158 participants with pre-hypertension and stage 1 hypertension, collected at baseline and following the consumption of a carbohydrate-rich, a protein-rich, and a monounsaturated fat-rich healthy diet (6 wk/diet) in a randomized, crossover study, were analyzed by proton (1H) nuclear magnetic resonance (NMR) spectroscopy. Urinary metabolite profiles were interrogated to identify typical and variable responses to each diet. We quantified the differences in absolute excretion of metabolites, distinguishing between dietary comparisons within the typical response groups, and established their associations with CVD risk factors using linear regression. Results Globally all 3 diets induced a similar pattern of change in the urinary metabolic profiles for the majority of participants (60.1%). Diet-dependent metabolic variation was not significantly associated with total cholesterol or low-density lipoprotein (LDL) cholesterol concentration. However, blood pressure (BP) was found to be significantly associated with 6 urinary metabolites reflecting dietary intake [proline-betaine (inverse), carnitine (direct)], gut microbial co-metabolites [hippurate (direct), 4-cresyl sulfate (inverse), phenylacetylglutamine (inverse)], and tryptophan metabolism [N-methyl-2-pyridone-5-carboxamide (inverse)]. A dampened clinical response was observed in some individuals with variable metabolic responses, which could be attributed to nonadherence to diet (≤25.3%), variation in gut microbiome activity (7.6%), or a combination of both (7.0%). Conclusions These data indicate interindividual variations in BP in response to dietary change and highlight the potential influence of the gut microbiome in mediating this relation. This approach provides a framework for stratification of individuals undergoing dietary management. The original OmniHeart intervention study and the metabolomics study were registered at www.clinicaltrials. gov as NCT00051350 and NCT03369535, respectively.
Learning to Attend, Copy, and Generate for Session-Based Query Suggestion

Users try to articulate their complex information needs during search sessions by reformulating their queries. To make this process more effective, search engines provide related queries to help users in specifying the information need in their search process. In this paper, we propose a customized sequence-to-sequence model for session-based query suggestion. In our model, we employ a query-aware attention mechanism to capture the structure of the session context. is enables us to control the scope of the session from which we infer the suggested next query, which helps not only handle the noisy data but also automatically detect session boundaries. Furthermore, we observe that, based on the user query reformulation behavior, within a single session a large portion of query terms is retained from the previously submitted queries and consists of mostly infrequent or unseen terms that are usually not included in the vocabulary. We therefore empower the decoder of our model to access the source words from the session context during decoding by incorporating a copy mechanism. Moreover, we propose evaluation metrics to assess the quality of the generative models for query suggestion. We conduct an extensive set of experiments and analysis. e results suggest that our model outperforms the baselines both in terms of the generating queries and scoring candidate queries for the task of query suggestion.
5-2-1-0 Activity and Nutrition Challenge for Elementary Students

Obesity prevention in youth is a health priority, and teaching healthy habits toward this end is one of a school nurse’s many responsibilities. A school nurse developed and implemented a school-wide, 2-week-long Activity and Nutrition Challenge (ANC) using the evidence-based 5-2-1-0 initiative to prevent and fight childhood obesity. Despite minimal promotion, nearly half of the students at two elementary schools participated and earned points by following the guidelines in the ANC. The amount of chocolate milk consumed by students dropped significantly during the ANC, showing that the healthy behavior of choosing beverages without added sugar had been positively impacted. Anecdotal evidence suggested positive changes in other healthy behaviors as well. This ANC was a new way for a school nurse to teach healthy habits to a large group of children in a short period of time, with limited extra work, and with promising results.
Contributions of paraecologists and parataxonomists to research, conservation, and social development

Citizen science has been gaining momentum in the United States and Europe, where citizens are literate and often interested in science. However, in developing countries, which have a dire need for environmental data, such programs are slow to emerge, despite the large and untapped human resources in close proximity to areas of high biodiversity and poorly known floras and faunas. Thus, we propose that the parataxonomist and paraecologist approach, which originates from citizen‐based science, is well suited to rural areas in developing countries. Being a paraecologist or a parataxonomist is a vocation and entails full‐time employment underpinned by extensive training, whereas citizen science involves the temporary engagement of volunteers. Both approaches have their merits depending on the context and objectives of the research. We examined 4 ongoing paraecologist or parataxonomist programs in Costa Rica, India, Papua New Guinea, and southern Africa and compared their origins, long‐term objectives, implementation strategies, activities, key challenges, achievements, and implications for resident communities. The programs supported ongoing research on biodiversity assessment, monitoring, and management, and participants engaged in non‐academic capacity development in these fields. The programs in Southern Africa related to specific projects, whereas the programs in Costa Rica, India, and Papua New Guinea were designed for the long term, provided sufficient funding was available. The main focus of the paraecologists’ and parataxonomists’ activities ranged from collection and processing of specimens (Costa Rica and Papua New Guinea) or of socioeconomic and natural science data (India and Southern Africa) to communication between scientists and residents (India and Southern Africa). As members of both the local land user and research communities, paraecologists and parataxonomists can greatly improve the flow of biodiversity information to all users, from local stakeholders to international academia.
Automated 3D bioassembly of micro-tissues for biofabrication of hybrid tissue engineered constructs

Bottom-up biofabrication approaches combining micro-tissue fabrication techniques with extrusion-based 3D printing of thermoplastic polymer scaffolds are emerging strategies in tissue engineering. These biofabrication strategies support native self-assembly mechanisms observed in developmental stages of tissue or organoid growth as well as promoting cell–cell interactions and cell differentiation capacity. Few technologies have been developed to automate the precise assembly of micro-tissues or tissue modules into structural scaffolds. We describe an automated 3D bioassembly platform capable of fabricating simple hybrid constructs via a two-step bottom-up bioassembly strategy, as well as complex hybrid hierarchical constructs via a multistep bottom-up bioassembly strategy. The bioassembly system consisted of a fluidic-based singularisation and injection module incorporated into a commercial 3D bioprinter. The singularisation module delivers individual micro-tissues to an injection module, for insertion into precise locations within a 3D plotted scaffold. To demonstrate applicability for cartilage tissue engineering, human chondrocytes were isolated and micro-tissues of 1 mm diameter were generated utilising a high throughput 96-well plate format. Micro-tissues were singularised with an efficiency of 96.0 ± 5.1%. There was no significant difference in size, shape or viability of micro-tissues before and after automated singularisation and injection. A layer-by-layer approach or aforementioned bottom-up bioassembly strategy was employed to fabricate a bilayered construct by alternatively 3D plotting a thermoplastic (PEGT/PBT) polymer scaffold and inserting pre-differentiated chondrogenic micro-tissues or cell-laden gelatin-based (GelMA) hydrogel micro-spheres, both formed via high-throughput fabrication techniques. No significant difference in viability between the construct assembled utilising the automated bioassembly system and manually assembled construct was observed. Bioassembly of pre-differentiated micro-tissues as well as chondrocyte-laden hydrogel micro-spheres demonstrated the flexibility of the platform while supporting tissue fusion, long-term cell viability, and deposition of cartilage-specific extracellular matrix proteins. This technology provides an automated and scalable pathway for bioassembly of both simple and complex 3D tissue constructs of clinically relevant shape and size, with demonstrated capability to facilitate direct spatial organisation and hierarchical 3D assembly of micro-tissue modules, ranging from biomaterial free cell pellets to cell-laden hydrogel formulations.
PHASTER: a better, faster version of the PHAST phage search tool

PHASTER (PHAge Search Tool – Enhanced Release) is a significant upgrade to the popular PHAST web server for the rapid identification and annotation of prophage sequences within bacterial genomes and plasmids. Although the steps in the phage identification pipeline in PHASTER remain largely the same as in the original PHAST, numerous software improvements and significant hardware enhancements have now made PHASTER faster, more efficient, more visually appealing and much more user friendly. In particular, PHASTER is now 4.3× faster than PHAST when analyzing a typical bacterial genome. More specifically, software optimizations have made the backend of PHASTER 2.7X faster than PHAST, while the addition of 80 CPUs to the PHASTER compute cluster are responsible for the remaining speed-up. PHASTER can now process a typical bacterial genome in 3 min from the raw sequence alone, or in 1.5 min when given a pre-annotated GenBank file. A number of other optimizations have also been implemented, including automated algorithms to reduce the size and redundancy of PHASTER's databases, improvements in handling multiple (metagenomic) queries and higher user traffic, along with the ability to perform automated look-ups against 14 000 previously PHAST/PHASTER annotated bacterial genomes (which can lead to complete phage annotations in seconds as opposed to minutes). PHASTER's web interface has also been entirely rewritten. A new graphical genome browser has been added, gene/genome visualization tools have been improved, and the graphical interface is now more modern, robust and user-friendly. PHASTER is available online at www.phaster. ca.
RAPD Analysis of Lignin Content for 21 Ramie Varieties

An optional reaction system suitable for the assay and usage of RAPD in ramie was established.The program with fine repoduciblity and high reliability was effectively used for RAPD analysis in ramie genetics and breeding.Genomic DNA of 21 ramie varieties of different lignin content were amplified by RAPD from 150 arbitrary 10 base primers.The results showed that all 85 bands were identified.The polymorphic bands accounted for 80% of the total amplified bands.By drawing ploygenetic relationship through cluster of bands,the experimented accession could be divided among 3 types and 8 groups.
A modified dual current mode control method with an adaptive current bandwidth

In this paper, a new adaptive dual current mode control method (ADCMC) is presented, being a result of the modification of existing dual current mode control (DCMC) by introducing an adaptive current bandwidth. The ADCMC offers several important advantages over DCMC, such as no peak‐to‐average error in the inductor current, better transient response of current loop, and improved line regulation. A detailed analysis of the proposed ADCMC is performed for three types of DC–DC power electronics converters: buck, boost, and non‐inverting buck–boost converter. The performances of the ADCMC are tested with simulations and experiments. The obtained results confirm the analysis and validity of the proposed ADCMC method. Copyright © 2015 John Wiley & Sons, Ltd.
Assessing Acid–Base Status in Circulatory Failure: Relationship Between Arterial and Peripheral Venous Blood Gas Measurements in Hypovolemic Shock

Background and Objectives: In severe circulatory failure agreement between arterial and mixed venous or central venous values is poor; venous values are more reflective of tissue acid–base imbalance. No prior study has examined the relationship between peripheral venous blood gas (VBG) values and arterial blood gas (ABG) values in hemodynamic compromise. The objective of this study was to examine the correlation between hemodynamic parameters, specifically systolic blood pressure (SBP) and the arterial–peripheral venous (A-PV) difference for all commonly used acid–base parameters (pH, Pco 2, and bicarbonate). Design, Setting, Participants, and Measurements: Data were obtained prospectively from adult patients with trauma. When an ABG was obtained for clinical purposes, a VBG was drawn as soon as possible. Patients were excluded if the ABG and VBG were drawn >10 minutes apart. Results: The correlations between A-PV pH, A-PV Pco 2, and A-PV bicarbonate and SBP were not statistically significant (P = .55, .17, and .09, respectively). Although patients with hypotension had a lower mean arterial and peripheral venous pH and bicarbonate compared to hemodynamically stable patients, mean A-PV differences for pH and Pco 2 were not statistically different (P = .24 and .16, respectively) between hypotensive and normotensive groups. Conclusions: In hypovolemic shock, the peripheral VBG does not demonstrate a higher CO2 concentration and lower pH compared to arterial blood. Therefore, the peripheral VBG is not a surrogate for the tissue acid–base status in hypovolemic shock, likely due to peripheral vasoconstriction and central shunting of blood to essential organs. This contrasts with the selective venous respiratory acidosis previously demonstrated in central venous and mixed venous measurements in circulatory failure, which is more reflective of acid–base imbalance at the tissue level than arterial blood. Further work needs to be done to better define the relationship between ABG and both central and peripheral VBG values in various types of shock.
Super-Resolving Very Low-Resolution Face Images with Supplementary Attributes

Given a tiny face image, existing face hallucination methods aim at super-resolving its high-resolution (HR) counterpart by learning a mapping from an exemplar dataset. Since a low-resolution (LR) input patch may correspond to many HR candidate patches, this ambiguity may lead to distorted HR facial details and wrong attributes such as gender reversal. An LR input contains low-frequency facial components of its HR version while its residual face image, defined as the difference between the HR ground-truth and interpolated LR images, contains the missing high-frequency facial details. We demonstrate that supplementing residual images or feature maps with additional facial attribute information can significantly reduce the ambiguity in face super-resolution. To explore this idea, we develop an attribute-embedded upsampling network, which consists of an upsampling network and a discriminative network. The upsampling network is composed of an autoencoder with skip-connections, which incorporates facial attribute vectors into the residual features of LR inputs at the bottleneck of the autoencoder and deconvolutional layers used for upsampling. The discriminative network is designed to examine whether super-resolved faces contain the desired attributes or not and then its loss is used for updating the upsampling network. In this manner, we can super-resolve tiny (16Ã—16 pixels) unaligned face images with a large upscaling factor of 8Ã— while reducing the uncertainty of one-to-many mappings remarkably. By conducting extensive evaluations on a large-scale dataset, we demonstrate that our method achieves superior face hallucination results and outperforms the state-of-the-art.
Maternal reproductive health: Expression patterns of antioxidant enzyme selenoproteins of post-implantation embryos conceived by ethanol-treated murine mothers supplemented with α-tocopherol

Objective: To investigate if the protective effect of α-tocopherol against the impact of ethanol on brain morphogenesis involved the activity of the selenoproteins phospholipid hydroperoxide glutathione peroxidase (PHGPx; GPx4) and selenoprotein P (SelPP) that have roles against oxidative stress. Methods: Forty female mice were randomly assigned into natural control (CON), positive control (ETOH), low-, medium-, and high-α-tocopherol-supplemented-ethanol groups (LTOC, MTOC, HTOC, respectively). CON received drinking water without ethanol while ETOH, LTOC, MTOC and HTOC groups received 20% ethanol in drinking water. The supplemented groups were given respective dosages of α-tocopherol, 0.410, 0.819, and 1.640 mg/g body weight, at day 14 before mating onwards to the day 9 of gestation. At 10.5 ED of gestation (1 100 h), the pregnant females were sacrificed by cervical dislocation and the embryos were harvested. Total RNA were extracted, cDNA synthesis and qRT-PCR analyses were carried out. Results: The level of expression of PHGPx in the positive control was significantly lower than that of the natural control. Among the three α-tocopherol-supplemented groups, only the medium dose-group was significantly higher than the positive control. The level of expression of SelPP in the positive control was significantly lower than those of the natural control, the low- and medium-dose-tocopherol supplemented groups. In the high dose-α-tocopherol supplemented group, the level of expression was not significantly different from the positive control but significantly lower than the natural control. Conclusions: The activity of the selenoproteins PHGPx and SelPP are involved in the internetwork of antioxidative enzymes with vitamin E when given up to a medium dose only and is one of the possible pathways of shielding embryonic development against the impact of ethanol on brain morphogenesis. This study strengthens the impact of dietary α-tocopherol and Selenium supplement during the critical period of pregnancy.