Higher Fano manifolds

In this paper we address Fano manifolds with positive higher Chern characters. They are expected to enjoy stronger versions of several of the nice properties of Fano manifolds. For instance, they should be covered by higher dimensional rational varieties, and families of higher Fano manifolds over higher dimensional bases should admit meromorphic sections (modulo the Brauer obstruction). Aiming at finding new examples of higher Fano manifolds, we investigate positivity of higher Chern characters of rational homogeneous spaces. We determine which rational homogeneous spaces of Picard rank $1$ have positive second Chern character, and show that the only rational homogeneous spaces of Picard rank $1$ having positive second and third Chern characters are projective spaces and quadric hypersurfaces. We also classify Fano manifolds of large index having positive second and third Chern characters. We conclude by discussing conjectural characterizations of projective spaces and complete intersections in terms of these higher Fano conditions

Investigating the effect of light color temperature on selective attention, error and human reaction time

Background and aims: The reaction time of humans that affected by several factors includes the time that takes to stimulate the sensory organs and the stimulus effect is transmitted to the brain, then is perceived and the decision is made; consequently, the command resulting from the decision of the brain is sent from the brain to the functional organs. Failure to respond at the right time may result in human error and accidents. There are important factors that affect the reaction time. Attention is one of the important factors affecting the speed of the reaction. Selective attention and correct perception of several stimuli among the other stimuli is one of the effective factors in promoting performance and safety. Additionally, various environmental factors may be effective in determining selective attention, increasing the number of errors and the human response time in detecting triggers. Lighting is one of the factors affecting the processing mechanisms of the brain. In the design of indoor and outdoor lighting systems, the quality parameters of the lighting system are usually less considered. Color temperature is one of the most important qualitative parameters of light, which is measured by the Kelvin unit and is an indicator for the brightness and color of the light. The aim of this study was to investigate the effect of light color temperature on selective attention, error rate and reaction time. Methods: This research is an interventional and laboratory study in order to determine the effect of the light color temperature on human error, selective attention, and reaction time of students in Tarbiat Modares University (TMU) of Tehran during the fall of 2018. All students were in the same age range. The inclusion criteria for this study were; not having any eye-related diseases, such as diminished vision and subtlety, and mental-psychiatric disorders. On the day before performing the test, participants were informed to: have enough sleep and rest, adhere to a regular diet, and avoid taking medicines, coffee and caffeinated drinks. In this interventional study, 92 students (36 female and 56 male) from Tarbiat Modarres University of Tehran with an average age of 28.33 years were recruited as subjects. The measurements and tests related to selective attention and reaction time of individuals were performed in 4 locations with an equal lighting system and different color temperatures (3500, 4000, 5000, or 6500 degrees Kelvin). In the first step of the study, in order to determine the effect of light color temperature on the studied parameters, the participants were randomly divided into four groups with 24 subjects in each group. Before the main test was being performed, the participants were kept in rooms adjusted to a brightness of 3500° K to rest for at least 5 minutes in order to be adapted to the situation, and then, in the same conditions, to become familiar with the test method they were studied with the Stroop software. In the second step, each group was placed in a separate room where the levels of brightness had been designed with one of the lighting systems to yield a color temperature of 3500, 4000, 5000, and 6500° K. Cognitive performance tests including reaction time, accuracy and selective attention were measured using Stroop tests. Measurement of score interference and time interference, which are indicators for selective attention, were calculated by measuring the difference in the error rate and the reaction time in detecting incongruent and consonant words. Stroop test was used to determine the reaction time, error and other parameters. This test consists of two parts; the practice and the main test, each of them has two stages. The first step is to name the color of circular shapes that appears on the laptop monitor screen. The participant, upon viewing the image, applies pressure on keyboard buttons which are labeled with colors corresponding to the ones on the screen. The second step is to name the word which appears in a white box. The names of the colors appear, and as soon as the correct word is recognized, the participant should press the color word associated to the word on the keyboard. The third step, which is the main stage of the test, is a non-consistent word (red-green-blue) that shown randomly and sequentially on the monitor's screen. The subject must only press the keyboard button with the same color, only emphasizing the color and regardless of its connotation. In this test, 48 consistent colored words (the color of the word is identical with the meaning of the word; red, yellow, green and blue) and 48 non-consistent colored words (the color of the word is not the same as the word meaning; for example, the blue word shown in red). The time lap between the stimulants was 800 milliseconds and the duration of each of them was 2000 milliseconds. The subject's task was to select the correct color only. Finally, the data were analyzed using SPSS software. Results: Based on the results of this study, the highest mean of correct selection (474.49 ± 10.65) and the lowest mean of the correct ones (654.49 ± 11.77) were assigned to the color temperature of 6500 and 3500 ° K, respectively. Also, the highest mean of error rate (15.65 ± 9.77) and the lowest mean of error rate (10.94 ± 9.4) were reported at a color temperature of 3500 and 6500 ° K, respectively. According to the results of this study, with increase in color temperature from 3500 to 5000° Kelvin, the number of questions that were not responded decreased. Likewise, the number of unanswered questions for the color temperature of 6500 °K slightly increased compared to the color temperature of 5000 and 4000 °K. The results also indicated that, with an increase in color temperature from 3500 to 6500 °K, the reaction time to visual stimuli also decreased. The highest interference score was in the light color temperature of 3500 °K which indicates that the number of faults in naming inconsistent words relative to consonant words was higher in color temperature of 3500° K compared to other color temperatures. Also, according to Fig. 3, the maximum interference time was at 6500 ° K. This indicates that the performance time of the subjects in naming inconsistent words was higher relative to consonants in color temperature of 6,500° K compared to other color temperatures. Although the average response time under lighting condition with color temperature of 6500° K (718.95 ± 65.33) was less than the color temperature of 3500° K (728.58 ± 43.48), according to the results of the study, with a decrease in color temperature, the increase in mean response time was observed, but this difference was not significant (p p). Also, based on independent t-test (Table 2), there was a significant relationship between subjects' gender and variables such as interference score, interference time and number of unanswered questions. For all of these three variables (interference score, interference time and number of unanswered questions) mean in men was significantly lower than women (p <0.05). Based on subjects' gender, the average response time under different color temperatures showed that the response time (or reaction time) of female under lighting conditions with 3000 and 5,000 ° K was higher than male, while under lighting conditions with 4000 and 6500° K the response time of male was higher than female students. Although the average response time under different color temperatures was different between male and female subjects, based on the results of independent t-test, such difference was not significant. Conclusion: In general, the results of this study showed that when subjects are exposed to light color temperature of 6,500 ° K, the number of correct responses by them is higher than those exposed to other color temperatures, and with increasing the color temperature, the number of correct answers increases. Also, according to the results of this study, the error rate decrease by increasing color temperature of light source. Based on the results of this study, it is suggested to make use of light sources with a color temperature of 6,500 ° K in designing the lighting system of the places where human reaction time and error are high importance. Accordingly, it is recommended to repeat this study in other demographic groups, as well as taking into account the qualitative parameters of the lighting system in addition to its quantitative parameters. © 2020 Iran University of Medical Sciences. All rights reserved

UNav: An Infrastructure-Independent Vision-Based Navigation System for People with Blindness and Low vision

Vision-based localization approaches now underpin newly emerging navigation pipelines for myriad use cases from robotics to assistive technologies. Compared to sensor-based solutions, vision-based localization does not require pre-installed sensor infrastructure, which is costly, time-consuming, and/or often infeasible at scale. Herein, we propose a novel vision-based localization pipeline for a specific use case: navigation support for end-users with blindness and low vision. Given a query image taken by an end-user on a mobile application, the pipeline leverages a visual place recognition (VPR) algorithm to find similar images in a reference image database of the target space. The geolocations of these similar images are utilized in downstream tasks that employ a weighted-average method to estimate the end-user's location and a perspective-n-point (PnP) algorithm to estimate the end-user's direction. Additionally, this system implements Dijkstra's algorithm to calculate a shortest path based on a navigable map that includes trip origin and destination. The topometric map used for localization and navigation is built using a customized graphical user interface that projects a 3D reconstructed sparse map, built from a sequence of images, to the corresponding a priori 2D floor plan. Sequential images used for map construction can be collected in a pre-mapping step or scavenged through public databases/citizen science. The end-to-end system can be installed on any internet-accessible device with a camera that hosts a custom mobile application. For evaluation purposes, mapping and localization were tested in a complex hospital environment. The evaluation results demonstrate that our system can achieve localization with an average error of less than 1 meter without knowledge of the camera's intrinsic parameters, such as focal length

Extracellular Vesicles from Mesenchymal Stromal Cells for the Treatment of Inflammation-Related Conditions

Over the past two decades, mesenchymal stromal cells (MSCs) have demonstrated great potential in the treatment of inflammation-related conditions. Numerous early stage clinical trials have suggested that this treatment strategy has potential to lead to significant improvements in clinical outcomes. While promising, there remain substantial regulatory hurdles, safety concerns, and logistical issues that need to be addressed before cell-based treatments can have widespread clinical impact. These drawbacks, along with research aimed at elucidating the mechanisms by which MSCs exert their therapeutic effects, have inspired the development of extracellular vesicles (EVs) as anti-inflammatory therapeutic agents. The use of MSC-derived EVs for treating inflammation-related conditions has shown therapeutic potential in both in vitro and small animal studies. This review will explore the current research landscape pertaining to the use of MSC-derived EVs as anti-inflammatory and pro-regenerative agents in a range of inflammation-related conditions: osteoarthritis, rheumatoid arthritis, Alzheimer's disease, cardiovascular disease, and preeclampsia. Along with this, the mechanisms by which MSC-derived EVs exert their beneficial effects on the damaged or degenerative tissues will be reviewed, giving insight into their therapeutic potential. Challenges and future perspectives on the use of MSC-derived EVs for the treatment of inflammation-related conditions will be discussed

Aligning Monitoring and Compliance Requirements in Evolving Business Networks

Dynamic business networks (BNs) are intrinsically characterised by change. Compliance requirements management, in this context, may become particularly challenging. Partners in the network may join and leave the collaboration dynamically and tasks over which compliance requirements are specified may be consequently delegated to new partners or backsourced by network participants. This paper considers the issue of aligning the compliance requirements in a BN with the monitoring requirements they induce on the BN participants when change (or evolution) occurs. We first provide a conceptual model of BNs and their compliance requirements, introducing the concept of monitoring capabilities induced by compliance requirements. Then, we present a set of mechanisms to ensure consistency between the monitoring and compliance requirements when BNs evolve, e.g. tasks are delegated or backsourced in-house. Eventually, we discuss a prototype implementation of our framework, which also implements a set of metrics to check the status of a BN in respect of compliance monitorability

Enkephalon - technological platform to support the diagnosis of alzheimer’s disease through the analysis of resonance images using data mining techniques

Dementia can be considered as a decrease in the cognitive function of the person. The main diseases that appear are Alzheimer and vascular dementia. Today, 47 million people live with dementia around the world. The estimated total cost of dementia worldwide is US $ 818 billion, and it will become a trilliondollar disease by 2019 The vast majority of people with dementia not received a diagnosis, so they are unable to access care and treatment. In Colombia, two out of every five people presented a mental disorder at some point in their lives and 90% of these have not accessed a health service. Here it´s proposed a technological platform so early detection of Alzheimer. This tool complements and validates the diagnosis made by the health professional, based on the application of Machine Learning techniques for the analysis of a dataset, constructed from magnetic resonance imaging, neuropsychological test and the result of a radiological test. A comparative analysis of quality metrics was made, evaluating the performance of different classifier methods: Random subspace, Decorate, BFTree, LMT, Ordinal class classifier, ADTree and Random forest. This allowed us to identify the technique with the highest prediction rate, that was implemented in ENKEPHALON platform