Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Detectability on Estimates of Geographic Range Size in Bignonieae

Abstract: Extinction risk has not been evaluated for 96% of all described plant species. Given that the Global Strategy for Plant Conservation proposes preliminary conservation assessments of all described plant species by 2010, herbarium specimens (i.e., primary occurrence data) are increasingly being used to infer threat components from estimates of geographic range size. Nevertheless, estimates of range size based on herbarium data may be inaccurate due to collection bias associated with interspecific variation in detectability. We used data on 377 species of Bignonieae to test the hypothesis that there is a positive relationship between detectability and estimates of geographic range size derived from herbarium specimens. This relationship is expected if the proportion of the true geographic range size of a species that is documented by herbarium specimens is given by the product of the true geographic range size and the detectability of the species, assuming no relationship between true geographic range size and detectability. We developed 4 measures of detectability that can be estimated from herbarium data and examined the relationship between detectability and 2 types of estimates of geographic range size: area of occupancy and extent of occurrence. Our results from regressing estimates of extent of occurrence and area of occupancy on detectability across genera provided no support for this hypothesis. The same was true for regressions of estimated extent of occurrence on detectability across species within genera. Nevertheless, regressions of estimated area of occupancy on detectability across species within genera provided partial support for our hypothesis. We considered 3 possible explanations for this mixed outcome: violation of the assumption of no relationship between true geographic range size and detectability; the relationships between estimated geographic range size and detectability may be an artifact of a negative relationship between estimated area of occupancy and the sampling variance of detectability; detectability may have had 2 opposite effects on estimated species range sizes: one determines the proportion of the true range of a species documented by herbarium specimens and the other determines the distribution of true range size for the species actually observed with herbarium data. Our findings should help improve understanding of the potential biases incurred with the use of herbarium data.
Apaf-1 and caspase-9 do not act as tumor suppressors in myc-induced lymphomagenesis or mouse embryo fibroblast transformation

Based on experiments with cultured fibroblasts, the apoptosis regulators caspase-9 and Apaf-1 are hypothesized to function as tumor suppressors. To investigate their in vivo role in lymphomagenesis, an IgH enhancer-driven c-myc transgene was crossed onto Apaf-1−/− and caspase-9−/− mice. Due to perinatal lethality, Eμ-myc transgenic Apaf-1−/− or caspase-9−/− fetal liver cells were used to reconstitute lethally irradiated recipient mice. Surprisingly, no differences were seen in rate, incidence, or severity of lymphoma with loss of Apaf-1 or caspase-9, and Apaf-1 was not a critical determinant of anticancer drug sensitivity of c-myc–induced lymphomas. Moreover, loss of Apaf-1 did not promote oncogene-induced transformation of mouse embryo fibroblasts. Thus, Apaf-1 and caspase-9 do not suppress c-myc–induced lymphomagenesis and embryo fibroblast transformation.
Species Identification of Mycobacteria by PCR-Restriction Fragment Length Polymorphism of therpoB Gene

ABSTRACT PCR-restriction fragment length polymorphism analysis (PRA) using the novel region of the rpoB gene was developed for rapid and precise identification of mycobacteria to the species level. A total of 50 mycobacterial reference strains and 3 related bacterial strains were used to amplify the 360-bp region of rpoB, and the amplified DNAs were subsequently digested with restriction enzymes such as MspI and HaeIII. The results from this study clearly show that most of the mycobacterial species were easily differentiated at the species level by this PRA method. In addition, species with several subtypes, such as Mycobacterium gordonae, M. kansasii, M. celatum, andM. fortuitum, were also differentiated by this PRA method. Subsequently, an algorithm was constructed based on the results, and a blinded test was carried out with more than 260 clinical isolates that had been identified on the basis of conventional tests. Comparison of these two sets of results clearly indicates that this new PRA method based on the rpoB gene is more simple, more rapid, and more accurate than conventional procedures for differentiating mycobacterial species.
Nanotechnology in dentistry: prevention, diagnosis, and therapy

Nanotechnology has rapidly expanded into all areas of science; it offers significant alternative ways to solve scientific and medical questions and problems. In dentistry, nanotechnology has been exploited in the development of restorative materials with some significant success. This review discusses nanointerfaces that could compromise the longevity of dental restorations, and how nanotechnolgy has been employed to modify them for providing long-term successful restorations. It also focuses on some challenging areas in dentistry, eg, oral biofilm and cancers, and how nanotechnology overcomes these challenges. The recent advances in nanodentistry and innovations in oral health-related diagnostic, preventive, and therapeutic methods required to maintain and obtain perfect oral health, have been discussed. The recent advances in nanotechnology could hold promise in bringing a paradigm shift in dental field. Although there are numerous complex therapies being developed to treat many diseases, their clinical use requires careful consideration of the expense of synthesis and implementation.
12-Mo Intervention of Physical Exercise Improved Work Ability, Especially in Subjects with Low Baseline Work Ability

Objectives: This study’s objective was to assess the effects of a 12-month physical exercise intervention on work ability (WAI) and cardiorespiratory fitness (CRF) in healthy working adults. Methods: The study group had 371 participants, of which 338 (212 women and 126 men) were allocated in the exercise group and 33 (17 women and 16 men) in the control group. The exercise group underwent a 12-month exercise program followed by a 12-month follow-up. WAI and CRF were evaluated at baseline, and at 4, 8, 12, and 24 study months, in both exercise and control groups. The exercise group was divided into subgroups according to baseline WAI classifications (poor/moderate, good, excellent). Results: During the 12-month exercise intervention, the exercise group increased their leisure-time physical activity by 71% (p = 0.016) and improved the mean WAI by 3% and CRF by 7% (p < 0.0001, in both), while WAI and CRF decreased in the control group (ANCOVA using age, sex and BMI as covariates, for WAI, p = 0.013 and for CRF, p = 0.008). The changes in WAI and CRF between the exercise group and control group were significantly different during the intervention (baseline vs. 12-months, p = 0.028 and p = 0.007) and after the follow-up (p = 0.001 and p = 0.040), respectively. A light positive correlation between the changes in WAI and in CRF (r = 0.19, p < 0.01) existed. WAI improvement was the highest (13%, p < 0.0001) in the subgroup having poor/moderate WAI at baseline (ANCOVA, p < 0.001). Conclusions: The improvement of WAI associated with CRF. These results suggest that a physical exercise intervention may improve work ability.
Characterization of a Strong Dominant phytochrome AMutation Unique to Phytochrome A Signal Propagation1

Here, we report the isolation and characterization of a strong dominant-negative phytochrome A(phyA) mutation (phyA-300D) in Arabidopsis. This mutation carries a single amino acid substitution at residue 631, from valine to methionine (V631M), in the core region within the C-terminal half of PHYA. This PHYA core region contains two protein-interactive motifs, PAS1 and PAS2. Val-631 is located within the PAS1 motif. The phyA-V631M mutant protein is photochemically active and accumulates to a level similar to wild type in dark-grown seedlings. Overexpression of PHYA-V631M in a wild-type background results in a dominant-negative interference with endogenous wild-type phyA, whereas PHYA-V631M in aphyA null mutant background is inactive. To investigate the specificity of this mutation within the phytochrome family, the corresponding amino acid substitution (V664M) was created in the PHYTOCHROME B (PHYB) polypeptide. We found that the phyB-V664M mutant protein is physiologically active in phyB mutant and causes no interfering effect in a wild-type background. Together, our results reveal a unique feature in phyA signal propagation through the C-terminal core region.
On-Chip Immunoelectrophoresis of Extracellular Vesicles Released from Human Breast Cancer Cells

Extracellular vesicles (EVs) including exosomes and microvesicles have attracted considerable attention in the fields of cell biology and medicine. For a better understanding of EVs and further exploration of their applications, the development of analytical methods for biological nanovesicles has been required. In particular, considering the heterogeneity of EVs, methods capable of measuring individual vesicles are desired. Here, we report that on-chip immunoelectrophoresis can provide a useful method for the differential protein expression profiling of individual EVs. Electrophoresis experiments were performed on EVs collected from the culture supernatant of MDA-MB-231 human breast cancer cells using a measurement platform comprising a microcapillary electrophoresis chip and a laser dark-field microimaging system. The zeta potential distribution of EVs that reacted with an anti-human CD63 (exosome and microvesicle marker) antibody showed a marked positive shift as compared with that for the normal immunoglobulin G (IgG) isotype control. Thus, on-chip immunoelectrophoresis could sensitively detect the over-expression of CD63 glycoproteins on EVs. Moreover, to explore the applicability of on-chip immunoelectrophoresis to cancer diagnosis, EVs collected from the blood of a mouse tumor model were analyzed by this method. By comparing the zeta potential distributions of EVs after their immunochemical reaction with normal IgG, and the anti-human CD63 and anti-human CD44 (cancer stem cell marker) antibodies, EVs of tumor origin circulating in blood were differentially detected in the real sample. The result indicates that the present method is potentially applicable to liquid biopsy, a promising approach to the low-invasive diagnosis of cancer.
Realising epitaxial growth of GaN on (001) diamond

By an extensive investigation of the principal growth parameters on the deposition process, we realized the epitaxial growth of crystalline wurtzite GaN thin films on single crystal (001) diamond substrates by metal organic chemical vapor deposition. From the influence of pressure, V/III ratio, and temperature, it was deduced that the growth process is determined by the mass-transport of gallium precursor material toward the substrate. The highest temperature yielded an improved epitaxial relationship between grown layer and substrate. X ray diffraction (XRD) pole figure analysis established the presence of two domains of epitaxial layers, namely (0001) 〈 101− 0〉 GaN∥ (001)[110] diamond and (0001) 〈 101− 0〉 GaN∥ (001) [11−0] diamond, which are 90∘ rotated with respect to each other. The presence of these domains is explained by the occurrence of areas of (2×1) and (1×2) surface reconstruction of the diamond substrate. When applying highly misoriented diamond substrates toward the [110] diamond direction, .
Comparison of Science and Non-science Major Students’ Awareness of Bacterial Resistance and their Hygiene Practices

For years, people have been overusing antibacterial products, resulting in bacteria that are insusceptible to antibacterial products. This is due to misconceptions that surround antibacterial products. Studies have shown that many people aren’t aware of the dangers of antibacterial products, and expect a prescription of antibiotics upon doctor visits even in cases where antibiotics do not help. A common misconception, held by many, is the belief that antibacterial hand-washing products are more effective than normal hand-washing products. Similarly, many believe that antibacterial products are more effective when used in large amounts. However, studies reveal that these conceptions are faulty. Other studies show that education, especially science education, can help students understand more about hand hygiene. However, studies do not concentrate on students’ awareness of bacterial resistance, which is something I would like to test: Does the differing education provided to a science major and non-science major students affect their awareness of antibacterial resistance? This study tests whether biological science students are in fact more knowledge and, therefore, less likely to overuse antibacterial products. The results of the observational study and student survey reveal some surprising anomalies: while science majors are more likely to have heard about the dangers of microbial resistance, neither group frequently uses antibacterial products in recreational settings or in biology labs.
Learning about objects through action - initial steps towards artificial cognition

Within the field of Neuro Robotics we are driven primarily by the desire to understand how humans and animals live and grow and solve every day's problems. To this aim we adopted a "learn by doing" approach by building artificial systems, e.g. robots that not only look like human beings but also represent a model of some brain process. They should, ideally, behave and interact like human beings (being situated). The main emphasis in robotics has been on systems that act as a reaction to an external stimulus (e.g. tracking, reaching), rather than as a result of an internal drive to explore or "understand" the environment. We think it is now appropriate to try to move from acting, in the sense explained above, to "understanding". As a starting point we addressed the problem of learning about the effects and consequences of self-generated actions. How does the robot learn how to pull an object toward itself or to push it away? How does the robot learn that spherical objects roll while a cube only slides if pushed? Interacting with objects is important because it implicitly explores object representation, event understanding, and can provide definition of object-hood that could not be grasped with a mere passive observation of the world. Further, learning to understand what one's own body can do is an essential step toward learning by imitation. In this view two actions are similar not only if their kinematics and dynamics are similar but rather if the effects on the external world are the same. Along this line of research we discuss some recent experiments performed at the AI-Lab at MIT and at the LIRA-Lab at the University of Genova on COG and Babybot respectively. We show how the humanoid robots can learn how to poke and prod objects to obtain a consistently repeatable effect (e.g. sliding in a given direction), to help visual segmentation, and to interpret a poking action performed by a human manipulator.
Active Learning with Model Selection in Linear Regression

Optimally designing the location of training input points (active learning) and choosing the best model (model selection) are two important components of supervised learning and have been studied extensively. However, these two issues seem to have been investigated separately as two independent problems. If training input points and models are simultaneously optimized, the generalization performance would be further improved. In this paper, we propose a new approach called ensemble active learning for solving the problems of active learning and model selection at the same time. We demonstrate by numerical experiments that the proposed method compares favorably with alternative approaches such as iteratively performing active learning and model selection in a sequential manner.
A Voronoi-Based Hybrid Motion Planner for Rigid Bodies

We present a hybrid path planning algorithm for rigid bodies translating and rotating in a 3D workspace. Our approach generates a Voronoi roadmap in the workspace and combines it with “bridges” computed by a randomized path planner with Voronoi-biased sampling. The Voronoi roadmap is computed from a discrete approximation to the generalized Voronoi diagram (GVD) of the workspace, which is generated using graphics hardware. By this use of the GVD, portions of the path can be generated without random sampling, substantially reducing the number of random samples needed for the full query. The planner has been implemented and tested on a number of benchmarks. Some preliminary comparisons with a randomized motion planner indicate that our planner performs more than an order of magnitude faster in several challenging scenarios.
Speedup and performance improvement of ICA-based robot audition by parallel and resampling-based block-wise processing

This paper describes a speedup and performance improvement of multi-channel semi-blind ICA (MCSB-ICA) with parallel and resampling-based block-wise processing. MCSB-ICA is an integrated method of sound source separation that accomplishes blind source separation, blind dereverberation, and echo cancellation. This method enables robots to separate user's speech signals from observed signals including the robot's own speech, other speech and their reverberations without a priori information. The main problem when MCSB-ICA is applied to robot audition is its high computational cost. We tackle this by multi-threading programming, and the two main issues are 1) the design of parallel processing and 2) incremental implementation. These are solved by a) multiple-stack-based parallel implementation, and b) resampling-based overlaps and block-wise separation. The experimental results proved that our method reduced the real-time factor to less than 0.5 with an eight-core CPU, and it improves the performance of automatic speech recognition by 2–10 points compared with the single-stack-based parallel implementation without the resampling technique.
Recovery of Degraded Areas in Vale do Paraíba, São Paulo, Brazil: Performance Indicators

The aim of restoration is recompose a new vegetation structure in order to obtain benefits such as the containment of bank erosion, reestablishment of a hydric and nutrient regime, and increase the diversity of species. The present paper evaluated the development of the vegetation introduced as ciliar forest around a mining lagoon through establishing indicators based on the vegetation structure, physic-chemical characteristics of the soil and the water. Results show that the indicators of vegetation, like dying of species and the covering of top were classified as negative factors. Regarding vegetation development, it was considered positive when individuals out of inundation points were analyzed. According to soil indicators, chemical factor pH acid suggests intoxication by aluminum, iron and manganese impeding development of the vegetation in the local. Topographic factor also caused erosion and dying/extinction of species localized in declining points and carried nutrients to the inundation point and finally to the sand mining pool.
Capacitive measuring method of the air-film thickness of aerostatic bearing

Aerostatic bearing is one of the essential and basic technologies of ultra-precision engineering, and air film vibration is one of the main factors affecting machining accuracy. This paper proposed a capacitive measuring method of the air-film thickness of aerostatic bearing, which took the restrictor and the working face as the two plates of the capacitive sensor, and the capacitive changed along with the changes of the air film thickness. After measuring the capacitance of the restrictor and the working face, the air film thickness was then calculated. The mathematical model between the capacitance and the air film thickness with concave restrictor was established. The experiments of aerostatic bearing film thickness measurement showed that compare to the inductor sensor, the capacitance measurement get an average error of 0.28 μm. The research of this paper provides a new method for air film thickness measuring of aerostatic bearings.
1 Full-Field Optical Coherence Microscopy

Optical coherence tomography (OCT) is a well-established optical imaging technique with micrometer-scale resolution. OCT is based on low-coherence interferometry to measure the amplitude of light backscattered by the sample being imaged [1-4]. The most significant impact of OCT is in ophthalmology for in situ examination of the pathologic changes of the retina [5-8] and measurement of the dimensions of the anterior chamber of the eye [9, 10]. OCT has also been established in a variety of other biomedical applications [11] and for material characterization [12, 13].
Fast confidential search for bio-medical data using Bloom filters and Homomorphic Cryptography

Data protection is a challenge when outsourcing medical analysis, especially if one is dealing with patient related data. While securing transfer channels is possible using encryption mechanisms, protecting the data during analyses is difficult as it usually involves processing steps on the plain data. A common use case in bioinformatics is when a scientist searches for a biological sequence of amino acids or DNA nucleotides in a library or database of sequences to identify similarities. Most such search algorithms are optimized for speed with less or no consideration for data protection. Fast algorithms are especially necessary because of the immense search space represented for instance by the genome or proteome of complex organisms. We propose a new secure exact term search algorithm based on Bloom filters. Our algorithm retains data privacy by using Obfuscated Bloom filters while maintaining the performance needed for real-life applications. The results can then be further aggregated using Homomorphic Cryptography to allow exact-match searching. The proposed system facilitates outsourcing exact term search of sensitive data to on-demand resources in a way which conforms to best practice of data protection.
Review of Contemporary Literature on Machine Learning based Malware Analysis and Detection Strategies

Malicious software also known as malware are the critical security threat experienced by the current ear of internet and computer system users. The malwares can morph to access or control the system level operations in multiple dimensions. The traditional malware detection strategies detects by signatures, which are not capable to notify the unknown malwares. The machine learning models learns from the behavioral patterns of the existing malwares and attempts to notify the malwares with similar behavioral patterns, hence these strategies often succeeds to notify even about unknown malwares. This manuscript explored the detailed review of machine learning based malware detection strategies found in contemporary literature.