Miracle-dz/UniFAR-FTUs huggingface dataset:
A tale of two densities: active inference is enactive inference

The aim of this article is to clarify how best to interpret some of the central constructs that underwrite the free-energy principle (FEP) – and its corollary, active inference – in theoretical neuroscience and biology: namely, the role that generative models and variational densities play in this theory. We argue that these constructs have been systematically misrepresented in the literature, because of the conflation between the FEP and active inference, on the one hand, and distinct (albeit closely related) Bayesian formulations, centred on the brain – variously known as predictive processing, predictive coding or the prediction error minimisation framework. More specifically, we examine two contrasting interpretations of these models: a structural representationalist interpretation and an enactive interpretation. We argue that the structural representationalist interpretation of generative and recognition models does not do justice to the role that these constructs play in active inference under the FEP. We propose an enactive interpretation of active inference – what might be called enactive inference. In active inference under the FEP, the generative and recognition models are best cast as realising inference and control – the self-organising, belief-guided selection of action policies – and do not have the properties ascribed by structural representationalists.
Intratumor Heterogeneity of EGFR Activating Mutations in Advanced NSCLC Patients at Single-Cell Level

Introduction: Present study is to explore the controversial problem whether the intratumoral heterogeneity of EGFR activating mutation exists at the level of single cancer cells. Materials and Methods: Single H1975 cells harbored EGFR exon 21 L858R mutation were isolated by flow cytometry to assess the feasibility of single-cell analysis for EGFR exon 21 by nested polymerase chain reaction and derect sequence. Then, six patients diagnosed with lung adenocarcinoma whose fresh frozen specimens harbored EGFR exon 21 mutation tested by direct sequencing were chosen. All of them received gefitnib treatment and the PFS of three patients was longer than 12 months (Group A) while the PFS of other three patients was shorter than 6 months (Group B). By using the established method based on single H1975 cells, EGFR exon 21 mutational status was analyzed in single tumor cells which were captured from tumor sample by Laser Capture Microdissection. Results: A total of 104 individual H1975 cells were obtained. The amplification rate and allele drop-out rate were 96.2% and 7.0%, respectively. A total of 135 tumor cells from six patients’ samples were captured. The amplification rate of nested PCR was 84.3% (59/70) in Group A and 93.8% (61/65) in Group B (P=0.077). The mutational rate was 86.4% in Group A, which was significantly higher than the total mutational rate 68.9% in Group B (P=0.021). Conclusion: The intratumoral heterogeneity of EGFR activating mutation in lung adenocarcinoma does exist based on the analysis of single cancer cells.
Diosgenin Biosynthesis in the Sprouts of Fenugreek as Influenced by Chitosan

Trigonella foenum-graecum L. (Fabaceae), known as Fenugreekis an annual herb, contains various secondary metabolites including steroidal saponins, flavonoids, phenolic compounds and alkaloids. This study was planned to investigate the effect of concentrations of chitosan on growth, expression of diosgenin biosynthetic genes and diosgenin accumulation in sprouts of T. foenum-graecum. Results revealed that there is no positive response of chitosan in any of the studied growth parameters i.e. shoot and root length, fresh and dry weight. In control treatment without any chitosan solution the highest values for all the parameters were observed. The results indicated that increasing concentrations of chitosan had no significant effect on shoot and root lengths. The fresh weight of sprouts treated with chitosan decreased markedly, but not significantly, compared with that of the control. However, the dry weight of sprouts treated with chitosan was almost similar to that of the control. Diosgenin biosynthetic pathway in response to different concentration of chitosan enhanced to an increasing level in the expression of all treated sprouts than those of no chitosan (control) treated sprouts. The highest expression level was detected when treated with 0.05 mg/mL chitosan in most of the genes except TfSQS. The expression of TfSQS was slightly higher in sprouts treated with 0.01 mg/mL chitosan than in those treated with 0.05 mg/mL chitosan. The highest expression level was in TfCAS at 0.05 mg/mL chitosan exhibiting 3 times higher expressing than that of control. The increasing expression trend for both TfSQLE and TfSTRL remained up to 0.05 mg/mL chitosan showing 1.7 times more expression in this concentration and then started to decrease the expression level. Diosgenin content in the T. foenum-graecum sprouts did not respond positively to chitosan treatment. Our findings could be potentially implemented for future studies in this arena.
Transactional Networking : Concurrent and Consistent Policy Composition

It seems natural to imagine that SDN policy specification and control is distributed, and this paper focuses on the resulting concurrency issues. Indeed, conflicts among concurrent policy updates may result in serious inconsistencies on the data plane, even when each update is installed with perpacket consistent update semantics. This paper introduces the problem of consistent composition of concurrent policy updates. Intuitively, consistent concurrent policy composition must appear as though there is no concurrency neither between any policy updates, nor between a policy update and in-flight packets on the data plane. We propose an elegant policy composition abstraction based on a transactional interface with all-or-nothing semantics: a policy update is either committed, in which case the policy is guaranteed to compose consistently over the entire network and the update is installed in its entirety, or aborted, in which case, no packet is affected by it. Consequently, the control application logic is relieved from the cumbersome and potentially error-prone synchronization and locking tasks, and control applications are kept lightweight. In this paper, we also sketch a simple implementation of the transactional synchronization: our approach is based on fine-grained locking on network components and avoids complex state machine replication.
Automatic Geometric Calibration in Full-Parallax 3D Display using Holographic Screen

We develop an automatic geometric calibration technique for a full-parallax 3D display using a holographic screen and a projector. In the proposed method, the test patterns suitable for the holographic screen are sequentially projected and captured by a camera. In the experiment, correct 3D image was reconstructed after the calibration.
Manual Physical Therapy and Exercise for Neck Pain and Cervicogenic Headache : A Case Report

Study Design: The design is a case report of a clinical physical therapy case. Background: Neck pain is very common among the general population and is associated with increased disability, poor self-perceived health, and high recurrence rates. Patients with neck pain may be experiencing an accompanying cerviogenic headache. Neck pain and cervicogenic headache is often treated with manual therapy and therapeutic exercise; however, limited research exists on the effectiveness of intervention variety. Case Description: The patient was a 71-year-old male experiencing neck pain and cervicogenic headache symptoms. Limitations included but were not limited to pain with ADLs, driving, cervical mobility and reduced activity tolerance. Treatment focused on manual therapy consisting of cervical and thoracic thrust and nonthrust mobilization/manipulation techniques and instrument assisted soft tissue massage. Therapeutic exercise was also implemented into the treatment program for a combination approach. Outcomes: The patient had reductions in disability evidenced by a lower score on the NDI and no pain according to the NPRS at the end of treatment. Results also showed improvements in cervical AROM, deep cervical neck flexor strength/endurance, and postural awareness. Patient reports indicated increased activity tolerance resulting in return to prior level of function. Conclusion: A multimodal approach combining manual therapy and therapeutic exercise to target cervical musculoskeletal impairments resulted in beneficial outcomes. Further research can help determine the optimal approach for certain patient subtypes as well as long-term effectiveness of treatment to help prevent recurrence.
START NMT STOP Yes Update parameters No Accept ? Yes No Request Feedback ? Keep / Delete / Substitute / Accept Generate partial translations Identify uncertain locations Ask feedback

We propose an interactive-predictive neural machine translation framework for easier model personalization using reinforcement and imitation learning. During the interactive translation process, the user is asked for feedback on uncertain locations identified by the system. Responses are weak feedback in the form of “keep” and “delete” edits, and expert demonstrations in the form of “substitute” edits. Conditioning on the collected feedback, the system creates alternative translations via constrained beam search. In simulation experiments on two language pairs our systems get close to the performance of supervised training with much less human effort.
Stability of the convex linear combination of fractional positive discrete-time linear systems

The asymptotic stability of the convex linear combination of fractional positive discrete-time linear systems is addressed. Necessary and sufficient conditions for the asymptotic stability of the convex linear combination are established. The notion of diagonal dominant matrices for nonnegative real matrices is introduced. It is shown that the convex linear combination is asymptotically stable if its matrices are diagonal dominant.
Introducing Spaced Mosaic Plots ✩

Recent research has developed a group of likelihood-based finite mixture models for a data matrix with ordinal data, establishing likelihood-based multivariate methods which applies fuzzy clustering via finite mixtures to the ordered stereotype model. There are many visualisation tools which depict reduction of dimensionality in matrices of ordinal data. This technical report introduces the spaced mosaic plot which is one new graphical tool for ordinal data when the ordinal stereotype model is used. It takes advantage of the fitted score parameters to determine the spacing between two adjacent ordinal categories. We develop a function in R and its documentation is presented. Finally, the description of a spaced mosaic plot is shown.
FINANCIAL DEVELOPMENT AND ECONOMIC GROWTH : A SURVEY OF LITERATURE

The paper provides a survey of the literature on the relationship of financial development and economic growth. In the finance-growth nexus literature, a large body of research has empirically shown that financial development exerts positive impact on economic growth. Higher level of financial development suggests that the well-functioning financial sectors are efficient in mobilizing and allocating capital to its most productive use. From the classical views, financial sector development has been recognized as a major catalyst that contributes positively to economic growth. Well-functioning financial sectors have been shown to enhance economic growth by lowering transaction costs, reducing market frictions and ensuring that capital flows are steered towards the most productive use possible. The paper also provides directions for future research.
Dynamic online homework system : An enabler of learning

This paper outlines the results of the implementation of an online homework system for a Business Statistics course in an undergraduate Commerce program. The findings show that as a result of this online system, students feel better prepared for tests, understand concepts better, receive timely feedback, discuss concepts with their peers, and generally have higher confidence in dealing with statistical concepts. In terms of performance, those with high marks on the online homework, also had high final grades.
An Efficient Citrus Canker Detection Method based on Contrast Limited Adaptive Histogram Equalization Enhancement

Plant leaf disease is one of the critical causes for heavy loss of yield that reduces quantity and reduces quality of the agricultural product. Citrus plants such as lemon are mainly affected by citrus canker disease which affects the fruit production of the plants. Early canker disease identification is one of the challenging solution for increasing the plant production. This paper aims to identify and classify the canker disease accurately from the affected leaf images by adopting image processing techniques to detect plant leaf diseases from digital images. The proposed approach involves two stages to improve the clarity of leaf images. The primary stage uses Contrast Limited Adaptive Histogram Equalization (CLAHE) in pre-processing step which improves the contrast level of disease affected leaf image, segment the region of interest using K-mean Clustering and texture feature extraction using statistical GLCM. The second stage by adopting the Support Vector Machine classifier to detect the canker leaf image and implements these methods in lemon citrus canker disease detection. Experimental results show effective accuracy detection and reduced execution time of canker disease detection.
Production of Fiber Bragg Gratings in Phase Mask Interferometers

This article describes the production of fiber Bragg gratings using Phase Mask interferometers assembled at the Physics Department, University of Aveiro and Laser Laboratory, CEFET-PR. Those facilities were planned and installed as a consequence of a joint research project established under the auspices of the CAPES/GRICES (formerly ICCTI) international cooperation agreement. Results from the optical characterization of Bragg gratings produced at both centers are reported.
' s personal copy The genetics of investment biases

For a long list of investment “biases,” including lack of diversification, excessive trading, and the disposition effect, we find that genetic differences explain up to 45% of the remaining variation across individual investors, after controlling for observable individual characteristics. The evidence is consistent with a view that investment biases are manifestations of innate and evolutionary ancient features of human behavior. We find that work experience with finance reduces genetic predispositions to investment biases. Finally, we find that even genetically identical investors, who grew up in the same family environment, often differ substantially in their investment behaviors due to individualspecific experiences or events. & 2014 Elsevier B.V. All rights reserved.
Using Fat Supplementation to Improve the Chances of Pregnancy of Lactating Dairy Cows

The proportion of lactating dairy cows on commercial farms that become pregnant at the first insemination has decreased over the last 25 to 30 years. Data from New York herds indicate that the first service conception rates decreased from ~55% in 1975 to just under 40% in 2001 (Butler, 2005). The number of services per conception increased from 1.62 in 1970 to 2.91 in 1999 in Kentucky herds (Silva, 1998). The DHIA records from Raleigh, NC show that the 143 herds on DHIA for 29 consecutive years (1970 to 1999) experienced a decrease in services per conception from ~1.75 to just under 3.0 (Lucy, 2001). Conception rates measured for cows managed under controlled experimental conditions as reported in scientific journals also have decreased. Rates dropped from ~55% to ~45% (breeding at spontaneous estrus) to ~35% (timed AI) over a 50-year period (Lucy, 2001).
The effect of dielectric surface modification and heat-treatment on the performance of Rubrene based organic field-effect transistor

In this work, bottom gate top contact structured organic field-effect transistors (OFETs) were fabricated using Rubrene as active material and SiO2as the dielectric on n-type silicon wafer by thermal evaporation method. The effect of dielectric surface modification and abrupt heat treatment on the crystallinity of Rubrene thin film and its influence on the performance of OFETs are investigated. The surface morphologies and the crystal structure of Rubrene films are characterized using differential scanning calorimetry, X-ray diffraction and atomic force microscopy. It is observed that the dielectric surface affects the crystalline structure of Rubrene thin film as well as the electrical performance of the OFETs. Thermal transition of Rubrene from amorphous state to highly crystalline state is observed after abrupt heat treatment. It is observed that highly crystalline Rubrene thin films can be obtained by carefully deploying the rapid heat treatment method followed by surface treatment. The electrical properties of the OFETs such as field effect mobility, threshold voltage and current on/off ratio are evaluated using the V-I characteristics and the results are compared with the published data. Improvements in the performance of OFET are evident due to the improved crystallization and highly ordered structure of Rubrene molecules.
Towards Edge-based Representations for Image-to-Geometry Registration Working Paper

Existing methods for image-to-geometry registration typically assume that a reasonable initialization is available. For example, previously registered color images are used to bootstrap the registration process. This is because the employed dense registration criteria often result in optimization problems with many local optima; good initialization is thus required to overcome poor local optima. In this working paper we sketch a fully automated system that provides registration hypotheses solely based on matchings between points on the 2D image and sparse 3D key points on the model. To avoid having to rely on a pre-registration, we require representations of the local 3D geometry that are efficiently matchable to the appearance of the corresponding points in 2D images. To address this we propose two different representations. The first is based on learning custom feature point detectors for 2D images, which are trained to identify the appearance of specific 3D key points. They are based on renderings of characteristic lines, which correspond well with gradient information in images. The second representation unifies 2D gradient information from different viewpoints into a single 3D gradient descriptor, which can be matched to images via a projection.
Attainment of Target Blood Pressure Values in Patients with Survived Myocardial Infarction and Diabetes Mellitus

Although arterial hypertension is an important factor contributing to cardiovascular complications in coronary patients with and without diabetes mellitus (DM), target values of blood pressure are rarely achieved in practice. The aim of the study was to compare the attainment of target blood pressure in patients with DM who survived myocardial infarction (MI) (group A) with that in patients without DM (group B). A group of 118 patients (both genders, with confirmed diagnosis of MI) was followed for three years, out of which 34 belonged to group A, and 84 to group B. After three years of secondary prevention measures, in group B patients target blood pressure values (TA<140/90mmHg) were registered more often compared to the beginning of the study (84.8% vs 28.6%) (p<0.0001). Group A patients did not have statistically significant higher percentage of target blood pressure values (TA<130/80 mmHg) at the end of the study (11.8% vs 24.2%) (p>0.05), but the percentage of those with TA<140/90mmHg was significantly higher (57.6% vs 18.2%) (p<0.0005). Our analysis of secondary prevention indicated that 21.3% of group A and 12.7% of group B patients did not take β-blockers, but the difference was not statistically significant (p>0.05). In addition, there were no statistically significant differences in the use of ACE inhibitors between group A (84.8%) and group B (89.8%) (p>0.05). Our study of the evaluation of secondary prevention measures in achieving target blood pressure values in patients with and without DM who survived MI demonstrated high prevalence of higher blood pressure values, especially in patients with DM, and still insufficient use of β-blockers and ACE inhibitors. Secondary prevention of cardiovascular events thus has to be intensified, particularly in patients with diabetes.
Conditional Image Decoder ‖ ! − ‖ # ! Perceptual Reconstruction Loss Skeleton Discriminator Video Frames Clean Skeleton Image

We introduce a method for learning landmark detectors from unlabelled video frames and unpaired labels. This allows us to learn a detector from a large collection of raw videos given only a few example annotations harvested from existing data or motion capture. We achieve this by formulating the landmark detection task as one of image translation, learning to map an image of the object to an image of its landmarks, represented as a skeleton. The advantage is that this translation problem can then be tackled by CycleGAN. However, we show that a naive application of CycleGAN confounds appearance and pose information, with suboptimal keypoint detection performance. We solve this problem by introducing an analytical and differentiable renderer for the skeleton image so that no appearance information can be leaked in the skeleton. Then, since cycle consistency requires to reconstruct the input image from the skeleton, we supply the appearance information thus removed by conditioning the generator with a second image of the same object (e.g. another frame from a video). Furthermore, while CycleGAN uses two cycle consistency constraints, we show that the second one is detrimental in this application and we discard it, significantly simplifying the model. We show that these modifications improve the quality of the learned detector leading to state-of-the-art unsupervised landmark detection performance in a number of challenging human pose and facial landmark detection benchmarks. Project page: http://www.robots. ox.ac. uk/ ̃vgg/research/unsupervised_pose/
Fast dynamic deployment adaptation for mobile devices

Mobile devices that are limited in terms of CPU power, memory or battery power are only capable of executing simple applications. To be able to run advanced applications we introduce a framework to split up the application and execute parts on a remote server. In order to dynamically adapt the deployment at runtime, techniques are presented to keep the migration time as low as possible and to prevent performance loss while migrating. Also methods are presented and evaluated to cope with applications generating a variable load, which can lead to an unstable system.
3 D Cascaded Condensation Tracking for Multiple Objects Submitted for Blind Review

The Condensation and the Wavelet Approximated Reduced Vector Machine (W-RVM) approach are joined by the core idea to spend only as much as necessary effort for easy to discriminate regions (Condensation) or vectors (W-RVM) of the feature space, but most for regions with high statistical likelihood to contain the object of interest. In this paper we unify both approaches by adapting the W-RVM classifier to tracking and refine the Condensation approach. Additionally, we utilize Condensation for abstract multidimensional feature vectors and provide a template based tracking of the three-dimensional camera scene. Moreover, we introduce a robust multi-object tracking by extensions to the Condensation approach. The new 3D Cascaded Condensation Tracking (CCT) for multiple objects yields a more than 10 times faster tracking than state-of-art detection methods. We demonstrate more natural HCI applications by tracking a large camera scene with an active dual camera system.