LLukas22/scidocs huggingface dataset:
Mechanisms Employed by Trichoderma Species in the Biological Control of Plant Diseases: The History and Evolution of Current Concepts.

Fungal species belonging to the genus Trichoderma are worldwide in occurrence and easily isolated from soil, decaying wood, and other forms of plant organic matter. They are, for the most part, classified as imperfect fungi, in that they have no known sexual stage. Rapid growth rate in culture and the production of numerous spores (conidia) that are varying shades of green characterize fungi in this genus. The reverse side of colonies is often uncolored, buff, yellow, amber, or yellow-green, and many species produce prodigious quantities of thick-walled spores (chlamydospores) in submerged mycelium (8). The potential of Trichoderma species as biocontrol agents of plant diseases was first recognized in the early 1930s (31), and in subsequent years, control of many diseases has been added to the list (1,3,5,7,9,11,19, 23,29,34,37,40). This has culminated in the commercial production of several Trichoderma species for the protection and growth enhancement of a number of crops in the United States (24), and in the production of Trichoderma species and mixtures of species in India, Israel, New Zealand, and Sweden (D. R. Fravel, personal communication). One of the most interesting aspects of the science of biological control is the study of the mechanisms employed by biocontrol agents to effect disease control. Past research indicates that the mechanisms are many and varied, even within the genus Trichoderma. In order to make the most effective use of biocontrol agents for the control of plant diseases, we must understand how the agents work and what their limitations are. We can then develop effective means of culturing, storing, applying, and utilizing biocontrol agents so that we harness their best effort for disease control. The selected research papers cited in this article were chosen because they illustrate what has been learned about mechanisms involved in biocontrol with Trichoderma species.
Edge Computing Framework for Cooperative Video Processing in Multimedia IoT Systems

Multimedia Internet-of-Things (IoT) systems have been widely used in surveillance, automatic behavior analysis and event recognition, which integrate image processing, computer vision, and networking capabilities. In conventional multimedia IoT systems, videos captured by surveillance cameras are required to be delivered to remote IoT servers for video analysis. However, the long-distance transmission of a large volume of video chunks may cause congestions and delays due to limited network bandwidth. Nowadays, mobile devices, e.g., smart phones and tablets, are resource-abundant in computation and communication capabilities. Thus, these devices have the potential to extract features from videos for the remote IoT servers. By sending back only a few video features to the remote servers, the bandwidth starvation of delivering original video chunks can be avoided. In this paper, we propose an edge computing framework to enable cooperative processing on resource-abundant mobile devices for delay-sensitive multimedia IoT tasks. We identify that the key challenges in the proposed edge computing framework are to optimally form mobile devices into video processing groups and to dispatch video chunks to proper video processing groups. Based on the derived optimal matching theorem, we put forward a cooperative video processing scheme formed by two efficient algorithms to tackle above challenges, which achieves suboptimal performance on the human detection accuracy. The proposed scheme has been evaluated under diverse parameter settings. Extensive simulation confirms the superiority of the proposed scheme over other two baseline schemes.
An unexpected unity among methods for interpreting model predictions

Understanding why a model made a certain prediction is crucial in many data science fields. Interpretable predictions engender appropriate trust and provide insight into how the model may be improved. However, with large modern datasets the best accuracy is often achieved by complex models even experts struggle to interpret, which creates a tension between accuracy and interpretability. Recently, several methods have been proposed for interpreting predictions from complex models by estimating the importance of input features. Here, we present how a model-agnostic additive representation of the importance of input features unifies current methods. This representation is optimal, in the sense that it is the only set of additive values that satisfies important properties. We show how we can leverage these properties to create novel visual explanations of model predictions. The thread of unity that this representation weaves through the literature indicates that there are common principles to be learned about the interpretation of model predictions that apply in many scenarios.
Physical Internet Foundations

This paper provides insights into the foundations of the Physical Internet that has been introduced as a solution to the Global Logistics Sustainability Grand Challenge [1-2]. The Challenge sets as its goal to improve, by an order of magnitude, the economic, environmental and social efficiency and sustainability of the way physical objects are moved, stored, realized, supplied and used across the world. The paper introduces a formal definition of the Physical Internet as an open global logistics system founded on physical, digital and operational interconnectivity through encapsulation, interfaces and protocols. It is a perpetually evolving system driven by technological, infrastructural and business innovation. In line with the proposed definition, this chapter explains and provides insights into eight foundations of the Physical Internet: a means for logistics efficiency and sustainability, universal interconnectivity, encapsulation, standard smart interfaces, standard coordination protocols, logistics web enabler, an open global logistics system, and driven by innovation.
Brain 5-HT neurotransmission during paroxetine treatment.

BACKGROUND
Animal experimental studies suggest that repeated administration of selective serotonin reuptake inhibitors (SSRIs) produces complex adaptive changes in brain serotonin (5-HT) pathways. The effect of these adaptive changes on different aspects of brain 5-HT neurotransmission and their clinical consequences are not well understood.


METHOD
We studied the effect of repeated administration of the SSRI, paroxetine (20 mg daily), on the cortisol responses to the 5-HT precursor, 5-hydroxytryptophan (5-HTP), in healthy subjects and depressed patients.


RESULTS
In healthy subjects, following one week of paroxetine treatment there was a large increase in the cortisol response to 5-HTP. This increase had all but disappeared following 3 weeks treatment. In contrast, in depressed patients treated with paroxetine for 8 weeks, the cortisol response to 5-HTP was significantly increased.


CONCLUSIONS
SSRI treatment in depressed patients produces a persistent increase in the cortisol response to 5-HTP, a probable measure of neurotransmission at central 5-HT2 receptors. Potentiation of 5-HT2 neurotransmission is unlikely to account for the efficacy of SSRIs in major depression but might underlie their actions in obsessive-compulsive disorder and also perhaps certain of their adverse effects, notably sexual dysfunction.
The information value of online social networks: Lessons from peer-to-peer lending

We examine whether social networks facilitate online markets using data from a leading peer-to-peer lending website. We find that borrowers with social ties are consistently more likely to have their loans funded and receive lower interest rates; however, most borrowers with social ties do not perform better ex post. This finding suggests that lenders do not fully understand the relationship between social ties and unobserved borrower quality. We also find evidence of gaming on borrower participation in social networks. Overall, our findings suggest that return-maximizing lenders should be careful in interpreting social ties within the risky pool of social borrowers.
Gamification of online surveys: conceptual foundations and a design process based on the MDA framework

Gamification has been employed to make online surveys more engaging to fill. Related work has evaluated the psychological and behavioral outcome of gamified surveys, but has been unclear about design methods and best practices. This work discusses foundations, relevant design dimensions (game elements, survey areas and the design process), and critical issues concerning validity. It then proposes a structured process for survey gamification based on the MDA (mechanics, dynamics, aesthetics) framework. An evaluation of the proposed process within a case study is briefly presented along with preliminary, but promising results. The gamification process is put forth in the CHI community for further discussion, evaluation, and application.
Risk prediction of ventricular arrhythmias and myocardial function in Lamin A/C mutation positive subjects.

AIMS
Mutations in the Lamin A/C gene may cause atrioventricular block, supraventricular arrhythmias, ventricular arrhythmias (VA), and dilated cardiomyopathy. We aimed to explore the predictors and the mechanisms of VA in Lamin A/C mutation-positive subjects.


METHODS AND RESULTS
We included 41 Lamin A/C mutation-positive subjects. PR-interval and occurrence of VA were recorded. Left ventricular (LV) myocardial function was assessed as ejection fraction and speckle tracking longitudinal strain by echocardiography. Magnetic resonance imaging was performed to assess fibrosis in a selection of subjects. Ventricular arrhythmias were documented in 21 patients (51%). Prolonged PR-interval was the best predictor of VA (P < 0.001). Myocardial function by strain was reduced in the interventricular septum compared with the rest of the LV segments (-16.7% vs. -18.7%, P = 0.001) and correlated to PR-interval (R = 0.41, P = 0.03). Myocardial fibrosis was found exclusively in the interventricular septum and only in patients with VA (P = 0.007). PR-interval was longer in patients with septal fibrosis compared with those without (320 ± 66 vs. 177 ± 40 ms, P < 0.001).


CONCLUSION
Prolonged PR-interval was the best predictor of VA in Lamin A/C mutation-positive subjects. Electrical, mechanical, and structural cardiac properties were related in these subjects. Myocardial function was most reduced in the interventricular septum and correlated to prolonged PR-interval. Myocardial septal fibrosis was associated with prolonged PR-interval and VA. Localized fibrosis in the interventricular septum may be the mechanism behind reduced septal function, atrioventricular block and VA in Lamin A/C mutation-positive subjects.
Real-time 3D Ball Recognition using Perspective and Catadioptric Cameras

In this paper we present methods capable of performing ball recognition and tracking on a RoboCup Midsize robot in three-dimensions in real-time. The system uses information from a perspective as well as a catadioptric camera to yield stereoscopic depth. Robustness, accuracy and efficiency are evaluated.
Multiple Object Tracking: A Literature Review

Multiple Object Tracking (MOT) is an important computer vision task which has gained increasing attention due to its academic and commercial potential. Although different kinds of approaches have been proposed to tackle this problem, there still exists many issues unsolved. For example, factors such as abrupt appearance changes and severe object occlusions pose great challenges for MOT. In order to help the readers understand this topic and start working on it, we contribute a systematic and comprehensive review. In the review, we inspect the recent advances in various aspects about this topic and propose some interesting directions for future research. To our best knowledge, there has not been any review about this topic in the community. We endeavor to provide a thorough review on the development of this problem in the last decades. The main contributions of this review are fourfold: 1) Key aspects in a multiple object tracking system, including how to formulate MOT generally, how to categorize MOT algorithms, what needs to be considered when developing a MOT system and how to evaluate a MOT system, are discussed from the perspective of understanding a topic. We believe in that this could not only provide researchers, especially new comers to the topic of MOT, a general understanding of the state of the arts, but also help them to comprehend the essential components of a MOT system and the inter-component connection. 2) Instead of enumerating individual works, we discuss existing work according to the various aspects involved in a MOT system. In each aspect, methods are divided 1 Imperial College London, London, United Kingdom 2 National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China 3 Institute of Intelligent System and Decision, Wenzhou University, Zhejiang, China into different groups and each group is discussed in details for the principles, advances and drawbacks. 3) We examine experiments of existing publications and give tables which list results on the popular data sets to provide convenient comparison. We also provide some interesting discoveries by analyzing these tables. 4) We offer some potential directions and respective discussions about MOT, which are still open issues and need more research efforts. This would be helpful for researchers to identify further interesting problems.
Treatment Efficacy of Sacral Nerve Stimulation in Slow Transit Constipation: A Two-Phase, Double-Blind Randomized Controlled Crossover Study

Objectives:Sacral nerve stimulation (SNS) is a potential treatment for constipation refractory to standard therapies. However, there have been no randomized controlled studies examining its efficacy. In patients with slow transit constipation, we evaluated the efficacy of suprasensory and subsensory SNS compared with sham, in a prospective, 18-week randomized, double-blind, placebo-controlled, two-phase crossover study. The primary outcome measure was the proportion of patients who, on more than 2 days/week for at least 2 of 3 weeks, reported a bowel movement associated with a feeling of complete evacuation.Methods:After 3 weeks of temporary peripheral nerve evaluation (PNE), all patients had permanent implantation and were randomized to subsensory/sham (3 weeks each) and then re-randomized to suprasensory/sham (3 weeks each) with a 2-week washout period between each arm. Daily stool dairies were kept, and quality of life (QoL; SF36) was measured at the end of each arm.Results:Between November 2006 and March 2012, 234 constipated patients were assessed, of whom 59 were willing and deemed eligible to participate (4 male; median age 42 years). Of the 59 patients, 16 (28%) responded to PNE. Fifty-five patients went on to permanent SNS implantation. The proportion of patients satisfying the primary outcome measure did not differ between suprasensory (30%) and sham (21%) stimulations, nor between subsensory (25%) and sham (25%) stimulations. There were no significant changes in QoL scores.Conclusions:In patients with refractory slow transit constipation, SNS did not improve the frequency of complete bowel movements over the 3-week active period.
An Empirical Study of Machine Learning Algorithms Applied to Modeling Player Behavior in a "First Person Shooter" Video Game - Semantic Scholar

Modern video games present many challenging applications for artificial intelligence. Agents must not only appear intelligent but must also be fun to play against. In the video game genre of the first person shooter an agent must mimic all the behaviors of a human soldier in a combat situation. The standard opponent in a first person shooter uses a finite-state machine and a series of hand coded rules. Drawbacks of this system include a high level of predictability of opponents and a large amount of work manually programming each rule. Modern advances in machine learning have enabled agents to accurately learn rules from a set of examples. By sampling data from an expert player we use these machine learning algorithms in a first person shooter. With this system in place, the programmer has less work when hand coding the combat rules and the learned behaviors are often more unpredictable and life-like than any hardwired finite state machine. This thesis explores several popular machine learning algorithms and shows how these algorithms can be applied to the game. The empirical study includes decision trees, Naïve Bayes classifiers, neural networks, and neural networks trained using boosting and bagging methods. We show that a subset of AI behaviors can be learned by player modeling using machine learning techniques. Under this system we have successfully been able to learn the combat behaviors of an expert player and apply them to an agent in a modified version of the video game Soldier of Fortune 2. The following tasks were learned: speed of acceleration, direction of movement, direction of facing, and jumping. We evaluate both empirically and aesthetically which learner performed the best and make recommendations for the future. We also have created a system which uses these learned behaviors in a finite-state system within the game at real time.
The midline-based nasolabial transposition (MNT) flap: an original single-stage technique for nasal tip reconstruction.

BACKGROUND
Nasolabial flaps based on the lateral side of the nose for the reconstruction of lateral nasal defects in a single-stage procedure have been described. Similarly, in midline defects, nasolabial flaps can be used but a 2-stage procedure is classically required. The Midline-based Nasolabial Transposition (MNT) flap is presented as a new single-stage procedure for nasal tip reconstruction.


MATERIALS AND METHODS
Between 2009 and 2011, an MNT flap was used as a single-stage procedure in 3 cases of large nasal defects of the tip where the forehead flap was either contraindicated or rejected as an option by the patient.


RESULTS
There were no complications and a satisfactory aesthetic result was achieved in all cases.


CONCLUSIONS
The MNT flap is a new single-stage procedure for large nasal tip defects and as such represents an interesting alternative to the classical 2-stage forehead and nasolabial flaps, especially in elderly patients.
Design of Reversible Latches Optimized for Quantum Cost, Delay and Garbage Outputs

Reversible logic has extensive applications in emerging nanotechnologies, such as quantum computing, optical computing, ultra low power VLSI and quantum dot cellular automata. In the existing literature, designs of reversible sequential circuits are presented that are optimized for the number of reversible gates and the garbage outputs. The optimization of the number of reversible gates is not sufficient since each reversible gate is of different computational complexity, and thus will have a different quantum cost and delay. While the computational complexity of a reversible gate can be measured by its quantum cost, the delay of a reversible gate is another parameter that can be optimized during the design of a reversible sequential circuit. In this work, we present novel designs of reversible latches that are optimized in terms of quantum cost, delay and the garbage outputs. The optimized designs of reversible latches presented in this work are the D Latch, JK latch, T latch and SR latch.
Image Retrieval for Image-Based Localization Revisited

Image-based localization is the task of determining the exact location from which a query photo was taken. In this paper, we consider imagebased localization relative to a 3D point cloud of a scene, obtained from Structure-from-Motion, which allows an accurate estimate of the full camera pose from correspondences between 2D features and 3D points. To quickly establish the required 2D-to-3D matches, Irschara et al. use image retrieval methods [5] to find database images (used for the reconstruction) similar to the query image [1]. Since the relation between 2D features and 3D points is known for the database images, the correspondences for the query image can be computed by feature matching between images. Recent work has demonstrated that directly matching the features against the points outperforms retrieval-based methods in terms of the number of images that can be localized successfully [4]. Yet, direct matching is inherently less scalable than retrieval-based approaches since it needs to keep SIFT descriptors [3] in memory at all times. In this paper, we therefore analyze the algorithmic factors that cause the gap in registration performance. We show that using selective voting schemes enable retrieval methods to outperform state-of-the-art direct matching methods and explore how both selective voting and correspondence search can be accelerated by using a Hamming embedding [2].
Asthma identification and medication administration forms in New York City schools.

Clinical Trial Registration: clinicaltrials.gov, identifier NCT01873755. Disclosure: The authors have nothing to disclose. Funding: This study was supported by grant 5K23HD065742 (Marina Reznik, principal investigator) from the National Institutes of Health, the Eunice Kennedy Shriver National Institute of Child Health & Human Development, the Stony-Wold Herbert Foundation, the Monaghan Medical Corporation, and the Department of Pediatrics, Children’s Hospital at Montefiore. Spanish translation services of informed consent materials were performed by Bronx CREED, which is funded by grant P60 MD000514 from the National Institutes of Health National Center for Minority Health & Health Disparities. This study was presented in part at the 2014 Pediatric Academic Societies Meeting, Vancouver, BC, Canada, May 4, 2014. xHematology Department “Ion Chiricuţa” Cancer Institute Cluj-Napoca, Romania irena.manea@gmail.com
Results of surgical treatment compared with ultrasound-guided foam sclerotherapy in patients with varicose veins: a prospective randomised study.

OBJECTIVE
This study aims to compare venous clinical severity scores in patients with healed venous ulcers due to varicose veins of the lower limbs (the clinical, etiologic, anatomic, and pathophysiologic data (CEAP) classification: C(5) EpAsPr) treated by saphenous stripping and phlebectomy or by ultrasound-guided foam sclerotherapy.


METHOD
Sixty patients were included: 29 underwent saphenous stripping and phlebectomy for varices in saphenous tributaries and 27 were treated by ultrasound-guided foam sclerotherapy; four cases were lost to follow-up. The main outcome measure was venous clinical severity scores (pain, oedema, inflammation, hyperpigmentation and lipodermatosclerosis). An ultrasound examination was carried out prior to treatment and 30, 60 and 180 days after the procedure to assess the relative efficacy of the methods in obliterating the saphenous trunk.


RESULTS
The mean venous clinical severity scores measured before and after 180 days were as follows: Surgery group - pain: before 1.97 standard deviation (SD) 0.19, 180 days 0.72 SD 0.53; oedema: before 1.66 SD 0.48, 180 days 0.55 SD 0.63; inflammation: before 1.55 SD 0.63, 180 days 0.72 SD 0.45. Foam sclerotherapy group - pain: before 1.81 SD 0.40, 180 days 0.56 SD 0.51; oedema: before 1.70 SD 0.47, 180 days 0.48 SD 0.64; inflammation: before 1.67 SD 0.68, after 0.89 SD 0.32. All scores showed statistically significant reductions in both patient groups. The saphenous vein had been obliterated, 180 days after treatment, in 78% of the surgery group, compared with 90% in the foam sclerotherapy group.


CONCLUSIONS
Ultrasound-guided foam sclerotherapy is a safe and effective option for patients with chronic venous disorders.