Miracle-dz/UniFAR-FTUs huggingface dataset:
Managing Team Innovation in the Research and Development (R&D) Organization: Critical Determinants of Team Effectiveness

Background Teams are the principal vehicle in developing new drug development strategy and executing the tasks required to accomplish those objectives. The key research questions related to the measurement of team innovation performance in the branded pharmaceutical industry and identification of the drivers for optimal team performance outcomes. This project evaluated the key drivers for team innovation performance (defined as “outcomes”). Team outcomes included new information creation, compression of development time, expansion of image, learning, capability development, growth satisfaction, and overall effectiveness. Methods A total of 13 questions, with multiple subparts, as part of 7 key dimensions were adapted from previously validated scales. Eligible participants were those who were employed in a pharmaceutical R&D organization and were a member of a drug discovery and/or development team. Survey respondents were prompted to respond to the degree they agreed or disagreed using 5- to 7-point Likert-type scales. All analyses (reliability tests, factor analysis, and multivariate regression) were performed in IBM SPSS v22. Results While good correlations individually existed between team outcomes (dependent variable) and tested independent variables (autonomy, coaching, climate, proactive personality, empowering leadership, and transactive memory systems [TMSs]), the best predictors identified through multivariate regression analysis were leader and peer coaching and TMSs. Conclusions This research offers key insights for managers when forming and staffing teams. One is an emphasis on coaching. It is imperative for senior managers to assign individuals to teams who liaise with broader management that are capable of offering coaching and availability for team members to enhance their skills. This is particularly important in a growing hypercompetitive environment that is witnessing continuous strategic change. A second area of emphasis is on TMS, in an expertise-centered organization. As this is a central driver to team performance, it is imperative to improve adaptation skills of team members.
A Novel Antibacterial Membrane Electrode Based on Bacterial Cellulose/Polyaniline/AgNO3 Composite for Bio-Potential Signal Monitoring

We propose a flexible, dry, and antibacterial electrode with a low and stable skin electrode contact impedance for bio-potential signal monitoring. We fabricated a bacterial cellulose/polyaniline/AgNO3 nanocomposite membrane (BC/PANI/AgNO3) and used it for bio-potential signal monitoring. The bacterial cellulose (BC) provides a 3-D nanoporous network structure, and it was used as a substrate material in the BC/PANI/AgNO3 nanocomposite membrane. Polyaniline (PANI) and AgNO3, acting as conductive and antibacterial components, respectively, were polymerized and deposited on the surfaces of BC nanofibers to produce uniform thin film membrane with flexible, antibacterial, and conductive properties. Various measurements were conducted, in terms of antibacterial activity, skin electrode contact impedance, and qualitative analysis of ECG signal recordings. The BC/PANI/AgNO3 membrane revealed 100% antibacterial activities against both the Staphylococcus aureus and Escherichia coli bacteria. The skin electrode contact impedance of the proposed BC/PANI/AgNO3 electrode is lower than that of the Ag/AgCl gel electrode, with the same active area. In addition, the electrocardiogram (ECG) signals acquired with the proposed electrodes have stable characteristic waveforms, and they are not contaminated by noise. The waveform fidelity of the BC/PANI/AgNO3 membrane electrodes over 800 ECG cardiac cycles is 99.49%, and after the electrodes were worn for 24 hours, a fidelity of 98.40% was recorded over the same number of cardiac cycles. With the low and stable skin electrode contact impedance, the proposed dry BC/PANI/AgNO3 membrane electrode provided high fidelity for ECG signal recordings, thus offering a potential approach for bio-potential signal monitoring. With the above benefits, the novel flexible and dry BC/PANI/AgNO3 electrode has a significant antibacterial. Most of all, it is the first research to develop antibacterial in the electrode design.
Data Augmentation using Conditional Generative Adversarial Networks for Leaf Counting in Arabidopsis Plants

Deep Learning models are being applied to address plant phenotyping problems such as leaf segmentation and leaf counting. Training these models requires large annotated datasets of plant images, which, in many cases, are not readily available. We address the problem of data scarcity by proposing a data augmentation approach based on generating artificial images using conditional Generative Adversarial Networks (cGANs). Our model is trained by conditioning on the leaf segmentation mask of plants with the aim to generate corresponding, realistic, plant images. We also provide a novel method to create the input masks. The proposed system is thus capable of generating realistic images by first producing a mask, and subsequently using the mask as input to the cGANs. We evaluated the impact of the data augmentation on the leaf counting performance of the Mask R-CNN model. The average leaf counting error is reduced by 16.67% when we augment the training set with the generated data.
A method for deducing neck mobility in plesiosaurs, using the exceptionally preserved Nichollssaura borealis

The elongate-necked aquatic plesiosaurs existed for 135 Myr during the Mesozoic. The function of this elongate neck is a point of debate. Using computed tomography and three-dimensional (3D) modelling, the range of motion (ROM) of the plesiosaur Nichollssaura borealis neck was assessed. To quantify the ROM, the intervertebral mobility was measured along the cervical vertebral column. This was done by manipulating the 3D models in the lateral and dorsoventral directions during two trials. The first assessed the mean intervertebral ROM between pairs of cervical vertebrae along the entire column, and the second assessed ROM with reduced intervertebral spaces. The results suggest that there may be preference for lateral neck movements in N. borealis, which could correspond to an ecological function related to prey capture. This study demonstrates that 3D modelling is an effective tool for assessing function morphology for structures where no good modern analogue exists.
Intake, sources, and determinants of free sugars intake in Australian children aged 12–14 months

The consumption of free sugars is directly associated with adiposity and dental caries in early childhood; however, intake data in the first 2 years of life are limited. This cross-sectional analysis aims to identify major food sources of free sugars for Australian children aged 12-14 months and investigate factors associated with meeting the World Health Organisation (WHO) Guideline for sugars intake. Three days of nonconsecutive dietary data were collected via a 24-hr recall and 2-day food record for 828 participants. Usual intake of energy, total sugars, and free sugars were estimated, along with food group contributions to free sugars. Multiple logistic regression analysis was used to investigate factors associated with exceeding the WHO conservative recommendation that <5% of energy should come from free sugars. Mean free sugars intake was 8.8 (SD 7.7, IQR 3.7-11.6) g/day, contributing 3.6% (SD 2.8, IQR 1.6-4.8) of energy. Only 2.4% of participants exceeded the WHO recommendation that <10% of energy should come from free sugars, with 22.8% of participants exceeding the <5% recommendation. Children from households with greater socio-economic disadvantage (IRSAD <5, OR = 1.94) and in the lowest income bracket (OR = 2.10) were more likely to have intakes ≥5% of energy. Major food sources of free sugars were commercial infant foods (26.6%), cereal-based products (19.7%), namely, sweet biscuits (8.3%) and cakes (7.6%), followed by yoghurt (9.6%), and fruit and vegetable beverages (7.4%). These findings highlight the substantial contribution of infant foods to free sugars intakes and provide further evidence that dietary intakes are influenced by social determinants.
Improved discrimination between normal‐tension and primary open‐angle glaucoma with advanced vascular examinations – the Leuven Eye Study

Vascular factors have been suggested to influence the development and progression of glaucoma. They are thought to be especially relevant for normal‐tension glaucoma (NTG) patients. We aim to investigate which vascular factors, including advanced vascular examinations, better describe patients with NTG comparing to those with primary open‐angle glaucoma (POAG).
Optical Coherence Tomography Angiography Findings in X-Linked Retinoschisis.

BACKGROUND AND OBJECTIVE The aim of the study was to determine optical coherence tomography angiography (OCTA) findings and to identify mutations in the RS1 gene in a three-generation family with X-linked juvenile retinoschisis (XLRS). PATIENTS AND METHODS Clinical and genetic assessments were performed in 12 family members. OCTA was performed at baseline (12 members including cases and carriers) and after acetazolamide administration (three cases). Twenty healthy subjects (20 eyes, controls) were chosen for comparison. Molecular genetic analysis of the RS1 gene was performed in all family members. RESULTS Deep capillary plexus density was reduced in cases compared with controls (P < .01) and was negatively related with retinal thickness (P < .05). After treatment, retinal thickness decreased (P < .05) and deep capillary plexus density increased (P < .05) in cases. In three cases and in four carriers, p.Arg197 His mutation was found. CONCLUSION OCTA shows reduced macular deep vessel density in patients with XLRS probably related to vessel displacement and disruption due to schitic cysts. [Ophthalmic Surg Lasers Imaging Retina. 2018;49:e20-e31. ].
A Dataset and Preliminary Results for Umpire Pose Detection Using SVM Classification of Deep Features

In recent years, there has been increased interest in video summarization and automatic sports highlights generation. In this work, we introduce a new dataset, called SNOW, for umpire pose detection in the game of cricket. The proposed dataset is evaluated as a preliminary aid for developing systems to automatically generate cricket highlights. In cricket, the umpire has the authority to make important decisions about events on the field. The umpire signals important events using unique hand signals and gestures. We identify four such events for classification namely SIX, NO BALL, OUT and WIDE based on detecting the pose of the umpire from the frames of a cricket video. Pre-trained convolutional neural networks such as Inception V3 and VGG19 networks are selected as primary candidates for feature extraction. The results are obtained using a linear SVM classifier. The highest classification performance was achieved for the SVM trained on features extracted from the VGG19 network. The preliminary results suggest that the proposed system is an effective solution for the application of cricket highlights generation.
Granular cell astrocytoma: an aggressive IDH‐wildtype diffuse glioma with molecular genetic features of primary glioblastoma

Granular cell astrocytoma (GCA) is a rare adult infiltrating glioma subtype. We studied a series of 39 GCAs. Median age of presentation was 57.8 years and most cases developed in the frontal or temporal lobes. Tumors included grade II (n = 14), grade III (n = 11), and grade IV (n = 14) by WHO criteria. Granular cell morphology was diffuse in 31 (79%) cases and partial in eight (21%). Immunohistochemistry showed frequent positivity for GFAP (28 of 31), OLIG2 (16 of 16), and CD68 (27 of 30), but HAM56, CD163, and IBA‐1 histiocytic markers were all negative (22 of 22). IDH1(R132H) was negative in all the cases tested (16 of 16), while ATRX expression was retained (12 of 12). Cytogenetics demonstrated monosomy 10 (6 of 6) cases, +7 in 4 (of 6), −13q in 4 of 6, and −14 in 4 of 6. Next‐generation sequencing demonstrated mutations in PTEN/PIK3 genes in 6/13 (46%), NF1 in 3 of 10 (30%), TP53 in 3 of 13 (23%), PALB2 in 3 of 10 (30%), STAG2 in 3 of 10 (30%), EGFR mutation/amplification in 3 of 13 (23%), and AR in 2 of 10 (20%). CDKN2A/B deletion was identified in 5 of 13 (30%) cases (homozygous deletion in 4). The TERT C228T mutation was identified in 9 of 13 (69%). No mutations were encountered in IDH1, IDH2, CIC, FUBP1, H3F3A, BRAF or ATRX genes. The mean overall survival was 11.3 months. Patients >60 years old at diagnosis had a worse survival than patients <60 years (P = 0.001). There were no statistically significant differences in survival by WHO grade, extent of granular cell change, sex or MIB‐1 (P > 0.05). GCA is a variant of IDH‐wildtype diffuse glioma with aggressive behavior irrespective of grade and extent of granular cell morphology, and with molecular genetic features corresponding to primary glioblastoma.
Real- Time Pedestrian Detection in Crowded Scenes Using Deep Omega-Shape Features

Region-based Fully ConvNet (R-FCN) designed for general object detection is difficult to be directly applied for pedestrian detection, due to being with large human pose and scale changes, and even with partial occlusion in surveillance scenarios. This paper presents a real time pedestrian detection method with partial occlusion handling, which builds on the framework of Region-based Fully ConvNet. We introduce a deep Omega-shape feature learning and multi-paths detection to make our detector being robust to human pose and scale changes. A novel predicted boxes fusion strategy is proposed to reduce the number of false negatives caused by partial occlusion in crowded environment. Our end-to-end approach achieved 95.35% mAP on the Caltech dataset and 97.43% on Bronze dataset at a test-time speed of 86ms second per image.
Answering Science Exam Questions Using Query Rewriting with Background Knowledge

Open-domain question answering (QA) is an important problem in AI and NLP that is emerging as a bellwether for progress on the generalizability of AI methods and techniques. Much of the progress in open-domain QA systems has been realized through advances in information retrieval methods and corpus construction. In this paper, we focus on the recently introduced ARC Challenge dataset, which contains 2,590 multiple choice questions authored for grade-school science exams. These questions are selected to be the most challenging for current QA systems, and current state of the art performance is only slightly better than random chance. We present a system that rewrites a given question into queries that are used to retrieve supporting text from a large corpus of science-related text. Our rewriter is able to incorporate background knowledge from ConceptNet and -- in tandem with a generic textual entailment system trained on SciTail that identifies support in the retrieved results -- outperforms several strong baselines on the end-to-end QA task despite only being trained to identify essential terms in the original source question. We use a generalizable decision methodology over the retrieved evidence and answer candidates to select the best answer. By combining query rewriting, background knowledge, and textual entailment our system is able to outperform several strong baselines on the ARC dataset.
Loading Range for the Development of Peak Power in the Close-Grip Bench Press versus the Traditional Bench Press

The close-grip bench press (CGBP) is a variation of the traditional bench press (TBP) that uses a narrower grip (~95% biacromial distance) and has application for athletes performing explosive arm actions where the hands are positioned close to the torso. Limited research has investigated CGBP peak power. Twenty-six strength-trained individuals completed a one-repetition maximum TBP and CGBP. During two other sessions, subjects completed two repetitions as explosively as possible with loads from 20% to 90% for each exercise, with peak power measured by a linear position transducer. A factorial ANOVA calculated between- and within-exercise differences in peak power. Partial correlations controlling for sex determined relationships between absolute and relative strength and peak power load. Peak power for the TBP occurred at 50% 1RM, and 30% 1RM for the CGBP. There were no significant (p = 0.680) differences between peak power at each load when comparing the TBP and CGBP. For the within-exercise analysis, there were generally no significant differences in TBP and CGBP peak power for the 20–50% 1RM loads. There were no significant relationships between strength and peak power load (p = 0.100–0.587). A peak power loading range of 20–50% 1RM for the TBP and CGBP is suggested for strength-trained individuals.
Job Performance Through Knowledge Sharing Behavior in Global Software Development Organizations

Global software development is a knowledge intensive activity which is supported by knowledge sharing with team members working from different locations and backgrounds. Knowledge is considered as “power” and usually people hesitate to share it. There is an essential need to promote and create a knowledge sharing environment. In this research, Theory of Planned Behavior has been applied as the theoretical backbone of the conceptual framework with focus on knowledge sharing in global software development. This study examines impact of key factors, including attitude, subjective norms and perceived behavioral control on knowledge sharing intention and how knowledge sharing intention impacts knowledge sharing behavior. Furthermore, the impact of knowledge sharing behavior on job performance has also been explored. Data analysis results showed that attitude, subjective norms and perceived behavioral control had positive effects on knowledge sharing intention. Knowledge sharing behavior was found to have strongest impact on job performance. The results of this research should be of interest to academics and practitioners in the domain of global software development.
Why do I think and talk about it? Perceived functions and phenomenology of episodic counterfactual thinking compared with remembering and future thinking

People revisit situations from their past and imagine what could have happened had the situation played out differently. This form of hypothetical thinking is known as episodic counterfactual thinking. The reasons why people engage in episodic counterfactual thinking have not been examined in the same context with remembering the past and imagining the future. We addressed this gap, by focusing on the perceived functions and phenomenological characteristics of the most important episodic counterfactuals compared with episodic memories and future projections in younger adults. We base our analyses on four categories of functions previously identified for past events: reflective, social, generative, and ruminative. The reflective and social functions dominated across all events, with the reflective function being most pronounced for future projections, potentially suggesting a close connection between future projections and self-regulation and/or identity formation. Counter to predictions, the ruminative function was not rated higher for episodic counterfactuals than for other events; however, ratings of ruminative function showed unique correlations with the emotional intensity and involuntary remembering for episodic counterfactuals. Overall, these results suggest that episodic counterfactuals are used for self-reflection and social sharing more than they are used for rumination and generative concerns.
Holistic and Deep Feature Pyramids for Saliency Detection

Saliency detection has been increasingly gaining research interest in recent years since many computer vision applications need to derive object attentions from images in the ﬁrst steps. Multi-scale awareness of the saliency detector becomes essential to ﬁnd thin and small attention regions as well as keeping high-level semantics. In this paper, we propose a novel holistic and deep feature pyramid neural network architecture that can leverage multi-scale semantics in feature encoding stage and saliency region prediction (decoding) stage. In the encoding stage, we exploit multi-scale and pyramidal hierarchy of feature maps via the densely connected network with variable-size dilated convolutions as well as a pyramid pooling. In the decoding stage, we fuse multi-level feature maps via up-sampling and convolution. In addition, we utilize the multi-level deep supervision via plugging in loss functions at every feature fusion level. Multi-loss supervision regularizes weights searching space among different tasks minimizing over-ﬁtting and enhances gradient signal during backpropagation, and thus enables us training the network from scratch. This architecture builds an inherent multi-level semantic pyramidal feature maps at different scales and enhances model’s capability in the saliency detection task. We validated our approach on six benchmark datasets and compared with
No interaction between rivastigmine and citalopram on memory and novelty processing in healthy human volunteers

Background: Animal literature suggests an interaction between acetylcholine and serotonin on cognitive functions. Aims: The aim of the current study was to assess whether both neurotransmitters interact during memory and novelty processing in humans. Methods: We tested the interaction between acetylcholine and serotonin on cognitive functions in healthy volunteers by means of treatment with rivastigmine and citalopram, respectively. Results: The main result of the study showed that during the verbal learning task participants significantly recalled fewer words after citalopram treatment than after rivastigmine or placebo during both the immediate and delayed recall tasks. Rivastigmine was not able to reverse the impairing effect of citalopram. Conclusions: This finding is in line with previous studies in which we manipulated acetylcholine and serotonin in different manners. Taken together, these studies in humans do not support the notion from animal studies that these two neurotransmitters interact on cognitive functions.
Future Directions in Research on Bryde's Whales

One of the lesser known species of baleen whales, the Bryde’s whale, also known as Eden’s whale (Balaenoptera edeni edeni and B. edeni brydei), although hunted as part of a North Pacific Japanese research programme , was not heavily exploited by commercial whaling and remains a data deficient species. Their taxonomic status is not fully resolved and they are often mistaken for other species leading to uncertainty about their true distribution, behavior and conservation status. Some populations are critically endangered, whilst others are small but have high genetic diversity suggesting wider connectivity. The species’ unpredictable coastal and offshore global distribution throughout warm-temperate waters has led to populations with unknown genetic variation, and facing different threats. Few areas are well-studied, but each study reveals often contrasting movement patterns, foraging strategies and vocal repertoires; there are considerable knowledge gaps for Bryde’s whales. There are few Bryde’s populations with abundance estimates but they typically number in the mid- to high-hundreds of individuals, with other populations small, <100 mature individuals, and exposed to high levels of anthropogenic impacts. Future research should focus on understanding the diversity within and between populations. Here, we suggest an integrative, comparative approach towards future work on Bryde’s whales, including acoustic monitoring, trophic interactions, telemetry tools, understanding their novel behaviors, and resolving their species status. This will inform conservation management of this unusual species of whale vulnerable to anthropogenic impacts.