Miracle-dz/UniFAR-FTUs huggingface dataset:
Finding minimum-cost circulations by canceling negative cycles

A classical algorithm for finding a minimum-cost circulation consists of repeatedly finding a residual cycle of negative cost and <italic>canceling</italic> it by pushing enough flow around the cycle to saturate an arc. We show that a judicious choice of cycles for canceling leads to a polynomial bound on the number of iterations in this algorithm. This gives a very simple strongly polynomial algorithm that uses no scaling. A variant of the algorithm that uses dynamic trees runs in <italic>O</italic>(<italic>nm</italic>(log <italic>n</italic>) min{log(<italic>nC</italic>), <italic>m</italic>log <italic>n</italic>}) time on a network of <italic>n</italic> vertices, <italic>m</italic> arcs, and arc costs of maximum absolute value <italic>C</italic>. This bound is comparable to those of the fastest previously known algorithms.
Susceptibility status of Aedes aegypti and Aedes albopictus against insecticides at eastern Punjab, Pakistan

Susceptibility status of Ae. albopictus and Ae. aegypti was evaluated in different localities of four towns namely Samanabad, Nishtar, Ravi and Iqbal town in Lahore district, Eastern Punjab, Pakistan. Susceptibility test using WHO test kits was applied on adult females (12-24) hrs. Post emergence (nonblood fed) live mosquitoes under laboratory conditions at 27-29 0C temperature and 85-95% humidity. Ae. aegypti and Ae. Albopictus were found resistant to 4% DDT with < 36.28% mortality. Both species were also found resistant against 0.05% deltamethrin, 0.05%, lambdacyhalothrin and 0.75% permethrin at all localities with <75.00%, <87.00% and <81.05% mortalities respectively. Ae. albopictus was found resistant to 0.1% bendiocarb at Samanabad and Iqbal towns, while resistance possible to be confirmed at Nishtar and Ravi towns. Ae. aegypti found susceptible to 0.1% bendiocarb at Samanabad town, resistant at Ravi town and resistance possible to be confirmed (incipient) at Nishtar and Iqbal towns with 92.23% and 94.00% mortalities. Malathion was found most suitable insecticide with 100% mortality rate in Ae. albopictus and Ae. aegypti at Lahore district. Alternative use of malathion and bendiocarb may be the best option to reduce dengue vector density.
BERT Models for Arabic Text Classiﬁcation: A Systematic Review

: Bidirectional Encoder Representations from Transformers (BERT) has gained increasing attention from researchers and practitioners as it has proven to be an invaluable technique in natural languages processing. This is mainly due to its unique features, including its ability to predict words conditioned on both the left and the right context, and its ability to be pretrained using the plain text corpus that is enormously available on the web. As BERT gained more interest, more BERT models were introduced to support different languages, including Arabic. The current state of knowledge and practice in applying BERT models to Arabic text classiﬁcation is limited. In an attempt to begin remedying this gap, this review synthesizes the different Arabic BERT models that have been applied to text classiﬁcation. It investigates the differences between them and compares their performance. It also examines how effective they are compared to the original English BERT models. It concludes by offering insight into aspects that need further improvements and future work.
EEG Based Emotion Identification Using Unsupervised Deep Feature Learning

Capturing user’s emotional state is an emerging way for implicit relevance feedback in information retrieval (IR). Recently, EEG-based emotion recognition has drawn increasing attention. However, a key challenge is effective learning of useful features from EEG signals. In this paper, we present our on-going work on using Deep Belief Network (DBN) to automatically extract high-level features from raw EEG signals. Our preliminary experiment on the DEAP dataset shows that the learned features perform comparably to the use of manually generated features for emotion recognition.
Named entity disambiguation on an ontology enriched by Wikipedia

Currently, for named entity disambiguation, the short-age of training data is a problem. This paper presents a novel method that overcomes this problem by automatically generating an annotated corpus based on a specific ontology. Then the corpus was enriched with new and informative features extracted from Wikipedia data. Moreover, rather than pursuing rule-based methods as in literature, we employ a machine learning model to not only disambiguate but also identify named entities. In addition, our method explores in details the use of a range of features extracted from texts, a given ontology, and Wikipedia data for disambiguation. This paper also systematically analyzes impacts of the features on disambiguation accuracy by varying their combinations for representing named entities. Empirical evaluation shows that, while the ontology provides basic features of named entities, Wikipedia is a fertile source for additional features to construct accurate and robust named entity disambiguation systems.
Painting with Interactive Control of Perceptual Entropy

Painting with Interactive Control of Perceptual Entropy MINGTIAN ZHAO and SONG-CHUN ZHU, University of California, Los Angeles and Lotus Hill Institute This article presents a framework for generating abstract art from photographs. The aesthetics of abstract art is largely attributed to its greater perceptual ambiguity than photographs. According to psychological theories [Berlyne 1971], the ambiguity tends to invoke moderate mental efforts of the viewer for interpreting the underlying contents, and this process is usually accompanied with subtle aesthetic pleasures. We study this phenomenon through human experiments comparing subjects’ interpretations of abstract art and photographs, and quantitatively verify the increased perceptual ambiguities in terms of recognition accuracy and response time. Based on the studies, we measure the level of perceptual ambiguity using entropy as it measures uncertainty levels in information theory, and propose a painterly rendering method with interactive control of the ambiguity levels. Given an input photograph, we first segment it into regions corresponding to different objects and parts in an interactive manner, and organize them into a hierarchical parse tree representation. Then we execute a painterly rendering process with image obscuring operators to transfer the photograph into an abstract painting style with increased perceptual ambiguities of both the scene and individual objects. Finally, using kernel density estimation and message passing algorithms, we compute and control the ambiguity levels numerically to the desired levels, during which we may predict and control the viewer’s perceptual path among the image contents by assigning different ambiguity levels to different objects. We have evaluated the rendering results using a second set of human experiments, and verified that they achieve similar abstract effects to original abstract paintings by artists.
Comparing Deep-Sea Fish Fauna between Coral and Non-Coral “Megahabitats” in the Santa Maria di Leuca Cold-Water Coral Province (Mediterranean Sea)

Two experimental longline surveys were carried out in the Santa Maria di Leuca (SML) cold-water coral province (Mediterranean Sea) during May–June and September–October 2010 to investigate the effect of corals on fish assemblages. Two types of “megahabitat” characterized by the virtual absence of fishing were explored. One was characterized by complex topography including mesohabitats with carbonate mounds and corals. The other type of megahabitat, although characterized by complex topographic features, lacks carbonate mounds and corals. The fishing vessel was equipped with a 3,000 m monofilament longline with 500 hooks and snoods of 2.5 m in length. A total of 9 hauls, using about 4,500 hooks, were carried out both in the coral megahabitat and in the non-coral megahabitat during each survey. The fish Leucoraja fullonica and Pteroplatytrygon violacea represent new records for the SML coral province. The coral by-catch was only obtained in the coral megahabitat in about 55% of the stations investigated in both surveys. The total catches and the abundance indices of several species were comparable between the two habitat typologies. The species contributing most to the dissimilarity between the two megahabitat fish assemblages were Pagellus bogaraveo, Galeus melastomus, Etmopterus spinax and Helicolenus dactylopterus for density and P. bogaraveo, Conger conger, Polyprion americanus and G. melastomus for biomass. P. bogaraveo was exclusively collected in the coral megahabitat, whereas C. conger, H. dactylopterus and P. americanus were found with greater abundance in the coral than in the non-coral megahabitat. Differences in the sizes between the two megahabitats were detected in E. spinax, G. melastomus, C. conger and H. dactylopterus. Although these differences most probably related to the presence-absence of corals, both megahabitats investigated play the role of attraction-refuge for deep-sea fish fauna, confirming the important role of the whole SML coral province as a refuge area from fishing.
Identification of satellite images based on mel frequency cepstral coefficients

MFCC technique is an efficient technique which can be used for speech signals' classification as MFCC can be applied for 1-D signals. This paper suggests a new application for MFCC technique as it can be used for classification of satellite images, which are 2-D objects. Applying MFCC to images, through transforming images to 1-D vectors is an innovation in its own right. The used images for training and testing are acquired by high-resolution satellites such as IKONOS, QuickBird, and SPOT. This image set can be applied before and after roads extraction approach that is called morphological direction and length filters approach.
Go With the Flow, on Jupiter and Snow. Coherence From Video Data without Trajectories

Viewing a data set such as the clouds of Jupiter, coherence is readily apparent to human observers, especially the Great Red Spot, but also other great storms and persistent structures. There are now many different definitions and perspectives mathematically describing coherent structures, but we will take an image processing perspective here. We describe an image processing perspective inference of coherent sets from a fluidic system directly from image data, without attempting to first model underlying flow fields, related to a concept in image processing called motion tracking. In contrast to standard spectral methods for image processing which are generally related to a symmetric affinity matrix, leading to standard spectral graph theory, we need a not symmetric affinity which arises naturally from the underlying arrow of time. We develop an anisotropic, directed diffusion operator corresponding to flow on a directed graph, from a directed affinity matrix developed with coherence in mind, and corresponding spectral graph theory from the graph Laplacian. Our examples will include partitioning the weather and cloud structures of Jupiter, and a local to Potsdam, N.Y. lake-effect snow event on Earth, as well as the the benchmark test double-gyre system.
Neuropsychological Deficits Are Not Predictive of Deficient Emotional Self-Regulation in Adults With ADHD

Objective: To investigate whether neuropsychological deficits account for the association between deficient emotional self-regulation (DESR) and ADHD. Method: DESR was identified in adults with and without ADHD who reported extreme frequency of items from the Barkley Current Behavior Scale (>95th percentile of control participants). A neuropsychological battery and structured diagnostic interview were administered to 113 adults with ADHD and DESR, 93 adults with ADHD without DESR, and 119 participants without ADHD or DESR. Results: Relative to adults with ADHD without DESR, adults with ADHD and DESR demonstrated lower scores on Wechsler Adult Intelligence Scale (WAIS) arithmetic but no other significant differences in neuropsychological performance. Relative to adults without ADHD, both ADHD groups demonstrated lower scores across several measures of executive function. Conclusion: Our findings do not support the hypothesis that neuropsychological deficits are linked to DESR in adults with ADHD. This finding is consistent with the hypothesis that DESR could be a manifestation of ADHD, but further study of alternate hypotheses is necessary to support this conclusion.
Evaluating Male Fertility in Brown Swiss Cattle Combining Multiple Sources of Information

Improving reproductive performance remains one of the major goals for the dairy industry worldwide. Bull fertility has been recognized as an important factor influencing reproductive success in dairy cattle. In this study, we investigated bull fertility in the Italian Brown Swiss dairy cattle population based on extensive records. The data set included a total of 397,926 breeding records from 1,228 bulls and 129,858 lactating cows between first and fifth lactation from 2000 to 2019, and all bulls have a genomic analysis on 454k single nucleotide polymorphisms (SNP). We estimated sire conception rate using only factors related to the bulls, our analyses revealed that there is a substantial variation in conception rate among Brown Swiss bulls, with more than 20% conception rate difference between high-fertility and low-fertility bulls and cross-validation analyses achieved predictive correlations equal to 0.30 for sire conception rate. The analysis included alternative whole-genome scans and gene-set analyses identified two genomic regions, located on BTA6 and BTA26 that showed marked non-additive effects. These regions harbor genes, such as WDR19 and ADGRA1 , that are directly involved in male fertility, including sperm motility, acrosome reaction, and embryonic development. The analysis to evaluate association between runs of homozygosity (ROH) and male fertility showed four different ROH regions located on chromosomes 6, 10, 11, and 24 were significantly overrepresented in low-fertility bulls. The predictive performance of the linear kernel-based regression models fitting the entire set of SNP markers exhibited predictive correlations around 0.19. Interestingly, the inclusion of two major non-additive markers as fixed effects achieved predictive correlations around 0.32. Moreover, including in the estimation also a new knowledge on the effect of ROH on the male fertility could improve reliability of prediction
Evaluation of ONU power saving modes for gigabit-capable passive optical networks

Energy efficiency has become an increasingly important aspect of designing access networks, due to both increased concerns for global warming and increased network costs related to energy consumption. Comparing access, metro, and core, the access constitutes a substantial part of the per subscriber network energy consumption and is regarded as the bottleneck for increased network energy efficiency. One of the main opportunities for reducing network energy consumption lies in efficiency improvements of the customer premises equipment. Access networks in general are designed for low utilization while supporting high peak access rates. The combination of large contribution to overall network power consumption and low utilization implies large potential for CPE power saving modes where functionality is powered off during periods of idleness.
On the Structure of P4-connected Graphs and the Separable -Homogeneous Decomposition

In recent years the study of the P 4-structure of graphs has attracted considerable attention , particularly in the context of graph decomposition. In this paper we investigate the structure of P 4-connected graphs. These are graphs such that, for every partition of the vertices into two nonempty disjoint sets, there is some P 4 containing vertices from both sets in the partition. Then we introduce the separable-homogeneous decomposition of graphs which extends both the well-known modular and the homogeneous decomposition. It is based on a previously known structure theorem for arbitrary graphs which decomposes a graph into its P 4-connected components and on a new decomposition theorem for P 4-connected graphs. As a nal result we obtain a tree representation for arbitrary graphs which is unique up to isomorphism.
End-to-end bandwidth guarantees through fair local spectrum share in wireless ad-hoc networks

Sharing the common spectrum among the links in a vicinity is a fundamental problem in wireless ad-hoc networks. Lately, some scheduling approaches have been proposed that guarantee fair share of bandwidth among the links. The quality of service perceived by the applications however depends on the end-to-end bandwidth allocated to the multihop sessions. We propose an algorithm that provides provably maxmin fair end-to-end bandwidth to sessions. The algorithm combines a link scheduling that avoids collisions, a fair session service discipline per link, and a hop-by-hop window flow control. All the stages of the algorithm are implementable based on local information, except the link scheduling part that needs some network-wide coordination.
Learning an efficient model of hand shape variation from depth images

We describe how to learn a compact and efficient model of the surface deformation of human hands. The model is built from a set of noisy depth images of a diverse set of subjects performing different poses with their hands. We represent the observed surface using Loop subdivision of a control mesh that is deformed by our learned parametric shape and pose model. The model simultaneously accounts for variation in subject-specific shape and subject-agnostic pose. Specifically, hand shape is parameterized as a linear combination of a mean mesh in a neutral pose with a small number of offset vectors. This mesh is then articulated using standard linear blend skinning (LBS) to generate the control mesh of a subdivision surface. We define an energy that encourages each depth pixel to be explained by our model, and the use of a smooth subdivision surface allows us to optimize for all parameters jointly from a rough initialization. The efficacy of our method is demonstrated using both synthetic and real data, where it is shown that hand shape variation can be represented using only a small number of basis components. We compare with other approaches including PCA and show a substantial improvement in the representational power of our model, while maintaining the efficiency of a linear shape basis.
A Hierarchical Model for Continuous Gesture Recognition Using Kinect

Human gesture recognition is an area, which has been studied thoroughly in recent years, and close to 100% recognition rates in restricted environments have been achieved, often either with single separated gestures in the input stream, or with computationally intensive systems. The results are unfortunately not as striking, when it comes to a continuous stream of gestures. In this paper we introduce a hierarchical system for gesture recognition for use in a gaming setting, with a continuous stream of data. Layer 1 is based on Nearest Neighbor Search and layer 2 uses Hidden Markov Models. The system uses features that are computed from Microsoft Kinect skeletons. We propose a new set of features, the relative angles of the limbs from Kinect’s axes to use in NNS. The new features show a 10 percent point increase in precision when compared with features from previously published results. We also propose a way of attributing recognised gestures with a force attribute, for use in gaming. The recognition rate in layer 1 is 68.2%, with an even higher rate for simple gestures. Layer 2 reduces the noise and has a average recognition rate of 85.1%. When some simple constraints are added we reach a precision of 90.5% with a recall of 91.4%.
Incentives and Performance in Large-scale Lean Software Development - An Agent-based Simulation Approach

The application of lean principles and agile project management techniques in the domain of large-scale software product development has gained tremendous momentum over the last decade. However, a simple transfer of good practices from the automotive industry combined with experiences from agile development on a team level is not possible due to fundamental differences stemming from the particular domain specifics – i.e. different types of products and components (material versus immaterial goods), knowledge work versus production systems as well as established business models. Especially team empowerment and the absence of a a hierarchical control on all levels impacts goal orientation and business optimization. In such settings, the design of adequate incentive schemes in order to align local optimization and opportunistic behavior with the overall strategy of the company is a crucial activity of central importance. Following an agent-based simulation approach with reinforcement learning, we (i) address the question of how information regarding backlog item dependencies is shared within and in between development teams on the product level subject to different incentive schemes. We (ii) compare different incentive schemes ranging from individual to team-based compensation. Based on our results, we are (iii) able to provide recommendations on how to design such incentives, what their effect is, and how to chose an adequate development structure to foster overall software product development flow by means of more economic decisions and thus resulting in a shorter time to market. For calibrating our simulation, we rely on practical experience from a very large software company piloting and implementing lean and agile for about three years.
Angiogenesis and bone regeneration of porous nano-hydroxyapatite/coralline blocks coated with rhVEGF165 in critical-size alveolar bone defects in vivo

To improve the regenerative performance of nano-hydroxyapatite/coralline (nHA/coral) block grafting in a canine mandibular critical-size defect model, nHA/coral blocks were coated with recombinant human vascular endothelial growth factor165 (rhVEGF) via physical adsorption (3 μg rhVEGF165 per nHA/coral block). After the nHA/coral blocks and VEGF/nHA/coral blocks were randomly implanted into the mandibular box-shaped defects in a split-mouth design, the healing process was evaluated by histological observation and histomorphometric and immunohistological analyses. The histological evaluations revealed the ingrowth of newly formed blood vessels and bone at the periphery and cores of the blocks in both groups at both 3 and 8 weeks postsurgery, respectively. In the histomorphometric analysis, the VEGF/nHA/coral group exhibited a larger quantity of new bone formation at 3 and 8 weeks postsurgery. The percentages of newly formed bone within the entire blocks in the VEGF/nHA/coral group were 27.3%±8.1% and 39.3%±12.8% at 3 weeks and 8 weeks, respectively, and these values were slightly greater than those of the nHA/coral group (21.7%±3.0% and 32.6%±10.3%, respectively), but the differences were not significant (P>0.05). The immunohistological evaluations revealed that the neovascular density in the VEGF/nHA/coral group (146±32.9 vessel/mm2) was much greater than that in the nHA/coral group (105±51.8 vessel/mm2) at the 3-week time point (P<0.05), but no significant difference was observed at the 8-week time point (341±86.1 and 269±50.7 vessel/mm2, respectively, P>0.05). The present study indicated that nHA/coral blocks might be optimal scaffolds for block grafting in critical-size mandibular defects and that additional VEGF coating via physical adsorption can promote angiogenesis in the early stage of bone healing, which suggests that prevascularized nHA/coral blocks have significant potential as a bioactive material for bone regeneration in large-scale alveolar defects.