Miracle-dz/UniFAR-FTUs huggingface dataset:
A Robust Indoor/Outdoor Navigation Filter Fusing Data from Vision and Magneto-Inertial Measurement Unit

Visual-inertial Navigation Systems (VINS) are nowadays used for robotic or augmented reality applications. They aim to compute the motion of the robot or the pedestrian in an environment that is unknown and does not have specific localization infrastructure. Because of the low quality of inertial sensors that can be used reasonably for these two applications, state of the art VINS rely heavily on the visual information to correct at high frequency the drift of inertial sensors integration. These methods struggle when environment does not provide usable visual features, such than in low-light of texture-less areas. In the last few years, some work have been focused on using an array of magnetometers to exploit opportunistic stationary magnetic disturbances available indoor in order to deduce a velocity. This led to Magneto-inertial Dead-reckoning (MI-DR) systems that show interesting performance in their nominal conditions, even if they can be defeated when the local magnetic gradient is too low, for example outdoor. We propose in this work to fuse the information from a monocular camera with the MI-DR technique to increase the robustness of both traditional VINS and MI-DR itself. We use an inverse square root filter inspired by the MSCKF algorithm and describe its structure thoroughly in this paper. We show navigation results on a real dataset captured by a sensor fusing a commercial-grade camera with our custom MIMU (Magneto-inertial Measurment Unit) sensor. The fused estimate demonstrates higher robustness compared to pure VINS estimate, specially in areas where vision is non informative. These results could ultimately increase the working domain of mobile augmented reality systems.
Development of a novel dengue virus serotype‐specific multiplex real‐time reverse transcription–polymerase chain reaction assay for blood screening

Dengue fever is caused by four related RNA viruses of the genus Flavivirus, dengue virus (DENV)‐1, ‐2, ‐3, and ‐4, which are transmitted to humans by mosquitoes. Although DENV is not endemic in Japan, an autochthonous dengue outbreak occurred in 2014. Several transfusion‐transmitted cases have also been reported after the use of blood and plasma products in DENV‐endemic countries. The aim of this study was to develop a novel multiplex reverse transcription–polymerase chain reaction (RT‐PCR) assay for DENV blood screening.
Text Mining Genotype-Phenotype Relationships from Biomedical Literature for Database Curation and Precision Medicine

The practice of precision medicine will ultimately require databases of genes and mutations for healthcare providers to reference in order to understand the clinical implications of each patient’s genetic makeup. Although the highest quality databases require manual curation, text mining tools can facilitate the curation process, increasing accuracy, coverage, and productivity. However, to date there are no available text mining tools that offer high-accuracy performance for extracting such triplets from biomedical literature. In this paper we propose a high-performance machine learning approach to automate the extraction of disease-gene-variant triplets from biomedical literature. Our approach is unique because we identify the genes and protein products associated with each mutation from not just the local text content, but from a global context as well (from the Internet and from all literature in PubMed). Our approach also incorporates protein sequence validation and disease association using a novel text-mining-based machine learning approach. We extract disease-gene-variant triplets from all abstracts in PubMed related to a set of ten important diseases (breast cancer, prostate cancer, pancreatic cancer, lung cancer, acute myeloid leukemia, Alzheimer’s disease, hemochromatosis, age-related macular degeneration (AMD), diabetes mellitus, and cystic fibrosis). We then evaluate our approach in two ways: (1) a direct comparison with the state of the art using benchmark datasets; (2) a validation study comparing the results of our approach with entries in a popular human-curated database (UniProt) for each of the previously mentioned diseases. In the benchmark comparison, our full approach achieves a 28% improvement in F1-measure (from 0.62 to 0.79) over the state-of-the-art results. For the validation study with UniProt Knowledgebase (KB), we present a thorough analysis of the results and errors. Across all diseases, our approach returned 272 triplets (disease-gene-variant) that overlapped with entries in UniProt and 5,384 triplets without overlap in UniProt. Analysis of the overlapping triplets and of a stratified sample of the non-overlapping triplets revealed accuracies of 93% and 80% for the respective categories (cumulative accuracy, 77%). We conclude that our process represents an important and broadly applicable improvement to the state of the art for curation of disease-gene-variant relationships.
fitplc - an R package to fit hydraulic vulnerability curves

We describe a toolkit to fit hydraulic vulnerability curves, such as the percent loss of xylem hydraulic conductivity ('PLC curves') as a function of the water potential. The toolkit is implemented as an R package, and is thus free to use and open source. The package fits the Weibull or sigmoidal function to measurements of PLC, conductance or conductivity, at corresponding leaf or stem water potentials. From the fitted curve, estimates of Px (the water potential at which x% conductivity is lost, e.g. the P50), and slope parameter (Sx) are provided together with confidence intervals (CI) around the fitted line. The CIs are estimated with the bootstrap. We also demonstrate the advantages of using mixed-effects models in situations where multiple individuals are measured on a species, as compared to the more traditional approach of fitting curves separately and averaging the parameters. We demonstrate the use of the new package with example data on seven species measured with two different techniques.
IFN‐γ targets macrophage‐mediated immune responses toward Staphylococcus aureus

Infections, especially with Staphylococcus aureus (SA), commonly cause morbidity and mortality in patients with chronic granulomatous disease (CGD), a condition characterized by a defective phagocyte oxidase. IFN‐γ reduces the frequency and consequences of infection in CGD by mechanisms that remain unknown. As IFN‐γ promotes bacterial killing, efferocytosis of effete polymorphonuclear neutrophils (PMN), and cytokine production in macrophages—the same macrophage effector functions that are impaired in response to SA—we hypothesized that IFN‐γ may reverse these defects and thereby, augment macrophage control of SA during infection. IFN‐γ primed activation of the NADPH oxidase in a time‐dependent manner, enhanced killing of ingested SA independent of any effects on phagocytosis, and increased binding of SA‐laden neutrophils (PMN‐SA) to macrophages. However, IFN‐γ did not increase the percentage of apoptotic PMN or PMN‐SA internalized by macrophages. Under conditions in which viable SA were eliminated, PMN‐SA primed the inflammasome for subsequent activation by silica but did not induce IL‐1β production by macrophages. IFN‐γ enhanced IL‐6 production in response to SA or PMN‐SA but did not increase inflammasome activation in response to either agonist. In summary, IFN‐γ augmented direct killing of SA by macrophages, promoted engagement of PMN‐SA, and enhanced macrophage‐mediated cytokine responses that could collectively augment control of SA infection. Together, these findings support the hypothesis that IFN‐γ improves responsiveness of macrophages to SA and provides insights into the mechanism of the clinical benefits of IFN‐γ.
Effect of Different Flaw Sizes and Surface Treatment on Biaxial Flexural Strength of Feldspathic Porcelain

Background and Objectives: Porcelain restorations are often ground for recontouring and occlusal adjustments. This removes the surface glaze layer and causes flaws that can grow in wet environments due to stress corrosion cracking and decrease the strength of porcelain and subsequently the longevity and clinical service of restoration. The aim of this study was to assess the effect of flaw size and surface treatments on biaxial flexural strength of feldspathic porcelain. Materials and Methods: Eighty feldspathic porcelain discs were fabricated, polished (P2000) and divided into two series (n=40) each with four subgroups (n=10); three subgroups in each series were centrally indented by means of a Vickers hardness tester under a load of either 9.8 N (A series) or 29.4 N (B series) and were then subjected to no surface treatment (subgroups 2 and 6), polishing (subgroups 3 and 7) or polishing plus silane plus resin (subgroups 4 and 8). Ten specimens in each series were not indented as controls (subgroups 1 and 5). Biaxial flexural strength of the discs was tested after water storage for 48 hours and the data were analyzed by two-way ANOVA and Tukey’s HSD test. Results: Both control subgroups revealed significantly higher strength than other subgroups (P<0.05) but there was no significant difference among other subgroups (P>0.05). The mean flexural strength of indented subgroups in B series was significantly lower than that in the same subgroups in A series (P<0.05). Conclusion: Presence and size of flaws affect the flexural strength of porcelain. Within the limitations of this study, none of the surface treatments could strengthen the cracked ceramic.
Multiple Sequence Alignment Based on a Suffix Tree and Center-Star Strategy: A Linear Method for Multiple Nucleotide Sequence Alignment on Spark Parallel Framework

Multiple sequence alignment (MSA) is an essential prerequisite and dominant method to deduce the biological facts from a set of molecular biological sequences. It refers to a series of algorithmic solutions for the alignment of evolutionarily related sequences while taking into account evolutionary events such as mutations, insertions, deletions, and rearrangements under certain conditions. These methods can be applied to DNA, RNA, or protein sequences. In this work, we take advantage of a center-star strategy to reduce the MSA problem to pairwise alignments, and we use a suffix tree to match identical substrings between two pairwise sequences. Multiple sequence alignment based on a suffix tree and center-star strategy (MASC) can accomplish MSA in O(mn), which is linear time complexity, where m is the number of sequences and n is the average length of sequences. Furthermore, we execute our method on the Spark-distributed parallel framework to deal with ever-increasing massive data sets. Our method is significantly faster than previous techniques, with no loss in accuracy for highly similar nucleotide sequences like homologous sequences, which we experimentally demonstrate. Comparing with mainstream MSA tools (e.g., MAFFT), MASC could finish the alignment of 67,200 sequences, longer than 10,000 bps, in 9 minutes, which takes MAFFT >3.5 days.
CP-consensus: a Blockchain Protocol Based on Synchronous Timestamps of Compass Satellite

Bitcoin, the first decentralized cryptocurrency, achieves great success but also encounters many challenges. In this paper, we mainly focus on Bitcoin’s five challenges: low network synchronization; poor throughput; high information propagation delay; vulnerabilities to fork-based attacks and consumption of a large amount of computational power to maintain the blockchain. To address these challenges, we present the CP-consensus, a blockchain protocol based on synchronous timestamps of the Compass satellite. Firstly, CP-consensus provides a quasi-synchronous network for nodes. Specifically, nodes synchronously begin or end in each phase. Secondly, the block propagation delay is significantly reduced by adopting cachenodes. Moreover, the block verification delay is significantly reduced since it is limited only by the size of block-header. Thirdly, CP-consensus has a high throughput with a larger block size since that the block size does not influence the consistency of CP-consensus. Fourthly, CP-consensus resists fork-based attacks and consumes a small amount of computational power. Finally, parameters setting and the security of CP-consensus are discussed.
Polygenic Risk Score for Alzheimer's Disease: Implications for Memory Performance and Hippocampal Volumes in Early Life.

OBJECTIVE Alzheimer's disease is a heritable neurodegenerative disorder in which early-life precursors may manifest in cognition and brain structure. The authors evaluate this possibility by examining, in youths, associations among polygenic risk score for Alzheimer's disease, cognitive abilities, and hippocampal volume. METHOD Participants were children 6-14 years of age in two Brazilian cities, constituting the discovery (N=364) and replication samples (N=352). As an additional replication, data from a Canadian sample (N=1,029), with distinct tasks, MRI protocol, and genetic risk, were included. Cognitive tests quantified memory and executive function. Reading and writing abilities were assessed by standardized tests. Hippocampal volumes were derived from the Multiple Automatically Generated Templates (MAGeT) multi-atlas segmentation brain algorithm. Genetic risk for Alzheimer's disease was quantified using summary statistics from the International Genomics of Alzheimer's Project. RESULTS Analyses showed that for the Brazilian discovery sample, each one-unit increase in z-score for Alzheimer's polygenic risk score significantly predicted a 0.185 decrement in z-score for immediate recall and a 0.282 decrement for delayed recall. Findings were similar for the Brazilian replication sample (immediate and delayed recall, β=-0.259 and β=-0.232, both significant). Quantile regressions showed lower hippocampal volumes bilaterally for individuals with high polygenic risk scores. Associations fell short of significance for the Canadian sample. CONCLUSIONS Genetic risk for Alzheimer's disease may affect early-life cognition and hippocampal volumes, as shown in two independent samples. These data support previous evidence that some forms of late-life dementia may represent developmental conditions with roots in childhood. This result may vary depending on a sample's genetic risk and may be specific to some types of memory tasks.
Plasma progesterone, luteinizing hormone concentrations, and granulosa cell responsiveness in heat-stressed hens.

Plasma progesterone and luteinizing hormone (LH) profiles were obtained during the first ovulatory cycle of heat-stressed (HS, 35 C; n = 24) and unstressed (US, 17 to 27 C; n = 24) hens using 30-min sampling intervals beginning approximately 6 h prior to ovulation. Progesterone levels from HS hens were lower from 6 h [. 07 +/- . 01 (SE) versus 1.66 +/- . 25 ng/mL; P = . 008] to predicted ovulation (.06 +/- .006 versus .70 +/- .18 ng/mL; P = .07). Likewise, LH levels from HS hens were lower from 6 h (1.55 +/- .16 versus 3.86 +/- .34 ng/mL; P = .007) to predicted ovulation (1.63 +/- .18 versus 2.50 +/- .27 ng/mL; P = .01). Eggs from HS hens were more often laid early (less than 24 h) than eggs from US hens (71.42 versus 13.33%, respectively; P = .01), but US hens more often laid eggs of a normal oviposition interval length (24 to 26 h) compared with HS hens (73.34 versus 14.29%; P = .0005). The percentage of delayed eggs (greater than 26 h) was not different (US, 14.29 versus HS, 13.37%; P = .75) between the two treatment groups. Basal production of progesterone by dispersed granulosa cells from US hens was 97.62 +/- 16.01 ng/mL. Challenge by LH increased this to 417.50 +/- 53.38 ng/mL (P = .0001). In contrast, basal progesterone secretion by cells from HS hens was 40.25 +/- 6.60 ng/mL (P = .0001) and LH challenge failed to increase progesterone production. (ABSTRACT TRUNCATED AT 250 WORDS)
Efficacy of rasagiline for the treatment of Parkinson’s disease: an updated meta-analysis

Abstract Objective: Rasagiline is a second-generation potent selective inhibitor of monoamine oxidase-B. The aim of the study was to analyze the effectiveness of rasagiline in treatment of Parkinson’s disease (PD), both as monotherapy and combination therapy. Methods: Medline, Cochrane, EMBASE, and Google Scholar databases were searched until 9 March 2016 using the keywords: Rasagiline, Azilect, Parkinson’s disease. Randomized controlled trials of patients with PD who were randomized to treatment with rasagiline or placebo were included. Outcomes were unified Parkinson’s disease rating scale (UPDRS) and the three subscales. Results: Ten studies fulfilled the inclusion criteria and 2709 patients were evaluated. The overall analysis revealed a significant improvement in change of total UPDRS scores in 1 mg/day and 2 mg/day rasagiline groups compared to placebo. Significant improvement in Part I (Mentation) of UPDRS scores was observed in 1 mg/day, but not in 2 mg/day rasagiline treatment group. Part II (ADL) and Part III (Motor) subscales significantly improved with both doses of rasagiline. Both monotherapy and combination therapy significantly improved total UPDRS scores. Conclusions: Our results confirm the efficacy of rasagiline in PD. Further studies are required to establish the optimal dose of rasagiline, as well as to determine its effectiveness in different combination therapy protocols. KEY MESSAGES Rasagiline treatment was associated with significant improvement of UPDRS scores and the scores of the subscales. Both monotherapy and combination therapy significantly improved total UPDRS scores. Effect of rasagiline on total UPDRS scores was not dose-dependent.
Contrast coding in the primary visual cortex depends on temporal contexts

Contrast response function in the primary visual cortex (V1) has long been described as following a sigmoid curve. However, this is mainly based on measuring neural responses to drifting contrast grating in a stable stimulation, a model that does not consider the effects of motion or length of stimulus presentation. During natural viewing, the visual system can obtain sufficient information for identifying the shapes defined by contrast from a single glance; acquiring greater knowledge of the neuronal response properties to contrast in such a short timescale is necessary to understand the underlying mechanisms. We investigated responses of cat V1 neurons to contrast presented by static grating for 40 ms without pause compared to drifting grating presented continuously for 2000 ms. The neuronal response to transiently presented contrast could be well described by a linear function. Further examination of the effects of motion and presentation duration on contrast responses demonstrated that motion increased response sensitivity in the low‐contrast range, while brief presentation increased response sensitivity in the high‐contrast range. Motion and prolonged presentation (adaptation) together resulted in an asymptotic sigmoid curve with a saturation response in the high‐contrast range. These results suggest that motion mainly enhance the neural response sensitivity to low‐contrast objects, while short and rapid presentation mainly enhance the neural sensitivity to high‐contrast stimulus. Our findings indicate that multiple factors influence the properties of contrast response functions, suggesting that V1 neuron contrast coding is flexible and depends on the temporal contexts.
Producing megakaryocytes from a human peripheral blood source

Cultured megakaryocytes could prove useful in the study of human diseases, but it is difficult to produce sufficient numbers for study. We describe and evaluate the use of an expansion process to develop mature megakaryocytes from peripheral blood–derived human hematopoietic stem and progenitor cells (HSPCs).
This Paper Is Included in the Proceedings of the 12th Usenix Symposium on Operating Systems Design and Implementation (osdi '16). Diamond: Automating Data Management and Storage for Wide-area, Reactive Applications Diamond: Automating Data Management and Storage for Wide-area, Reactive Applications

Users of today's popular wide-area apps (e.g., Twitter, Google Docs, and Words with Friends) must no longer save and reload when updating shared data; instead, these applications are reactive, providing the illusion of continuous synchronization across mobile devices and the cloud. Achieving this illusion poses a complex distributed data management problem for programmers. This paper presents the first reactive data management service, called Diamond, which provides persistent cloud storage, reliable synchronization between storage and mobile devices , and automated execution of application code in response to shared data updates. We demonstrate that Diamond greatly simplifies the design of reactive applications , strengthens distributed data sharing guarantees, and supports automated reactivity with low performance overhead.
Nanoindentation and VSM of Silver Nanowires Synthesized by Microwave-Polyol Process

Nanoindentation and VSM of Silver Nanowires Synthesized by Microwave-Polyol Process In the present research paper, silver nanowires have been synthesized by the polyol process in ethylene glycol as a reducing agent, polyvinylpyrrolidone as a stabilizer, using microwave technique. After synthesis 5 mm thick pallets of silver nanowires are prepared by making a paste in isopropyl alcohol and using polyvinylidene difluoride as a binder and then these pallets have been used for nanoindentation measurements. Hardness, reduced modulus, stiffness, contact height and contact area have been measured using nanoindenter. Magnetic properties of silver nanowires have been studied using vibrating sample magnetometer reveals absence of ferromagnetic impurities.
Dynamically Switching between Synergistic Workflows for Crowdsourcing

To ensure quality results from unreliable crowdsourced workers, task designers often construct complex workflows and aggregate worker responses from redundant runs. Frequently, they experiment with several alternative workflows to accomplish the task, and eventually deploy the one that achieves the best performance during early trials. Surprisingly, this seemingly natural design paradigm does not achieve the full potential of crowdsourcing. In particular, using a single workflow (even the best) to accomplish a task is suboptimal. We show that alternative workflows can compose synergistically to yield much higher quality output. We formalize the insight with a novel probabilistic graphical model. Based on this model, we design and implement AGENTHUNT, a POMDP-based controller that dynamically switches between these workflows to achieve higher returns on investment. Additionally, we design offline and online methods for learning model parameters. Live experiments on Amazon Mechanical Turk demonstrate the superiority of AGENTHUNT for the task of generating NLP training data, yielding up to 50% error reduction and greater net utility compared to previous methods.
Kallikrein-related peptidase 14 is the second KLK protease targeted by the serpin vaspin

Abstract Kallikrein-related peptidases KLK5, KLK7 and KLK14 are important proteases in skin desquamation and aberrant KLK activity is associated with inflammatory skin diseases such as Netherton syndrome but also with various serious forms of cancer. Previously, we have identified KLK7 as the first protease target of vaspin (Serpin A12). Here, we report KLK14 as a second KLK protease to be inhibited by vaspin. In conclusion, vaspin represents a multi-specific serpin targeting the kallikrein proteases KLK7 and KLK14, with distinct exosites regulating recognition of these target proteases and opposing effects of heparin binding on the inhibition reaction.