Miracle-dz/UniFAR-FTUs huggingface dataset:
Topics in Graph Algorithms: Structural Results and Algorithmic Techniques, with Applications

Coping with computational intractability has inspired the development of a variety of algorithmic techniques. The main challenge has usually been the design of polynomial time algorithms for NP -complete problems in a way that guarantees some, often worst-case, satisfactory performance when compared to exact (optimal) solutions. We mainly study some emergent techniques that help to bridge the gap between computational intractability and practicality. We present results that lead to better exact and approximation algorithms and better implementations. The problems considered in this dissertation share much in common structurally, and have applications in several scientific domains, including circuit design, network reliability, and bioinformatics. We begin by considering the relationship between graph coloring and the immersion order, a well-quasi-order defined on the set of finite graphs. We establish several (structural) results and discuss their potential algorithmic consequences. We discuss graph metrics such as treewidth and pathwidth. Treewidth is well studied, mainly because many problems that areNP -hard in general have polynomial time algorithms when restricted to graphs of bounded treewidth. Pathwidth has many applications ranging from circuit layout to natural language processing. We present a linear time algorithm to approximate the pathwidth of planar graphs that have a fixed disk dimension. We consider the face cover problem, which has potential applications in facilities location and logistics. Being fixed-parameter tractable, we develop an algorithm that solves it in time O(5 + n) where k is the input parameter. This is a notable improvement over the previous best known algorithm, which runs in O(8n).
The OnHW Dataset: Online Handwriting Recognition from IMU-Enhanced Ballpoint Pens with Machine Learning

This paper presents a handwriting recognition (HWR) system that deals with online character recognition in real-time. Our sensor-enhanced ballpoint pen delivers sensor data streams from triaxial acceleration, gyroscope, magnetometer and force signals at 100 𝐻𝑧 . As most existing datasets do not meet the requirements of online handwriting recognition and as they have been collected using specific equipment under constrained conditions, we propose a novel online handwriting dataset acquired from 119 writers consisting of 31,275 uppercase and lowercase English alphabet character recordings (52 classes) as part of the UbiComp 2020 Time Series Classification Challenge . Our novel OnHW-chars dataset allows for the evaluations of uppercase, lowercase and combined classification tasks, on both writer-dependent (WD) and writer-independent (WI) classes and we show that properly tuned machine learning pipelines as well as deep learning classifiers (such as CNNs, LSTMs, and BiLSTMs) yield accuracies up to 90% for the WD task and 83% for the WI task for uppercase characters. Our baseline implementations together with the rich and publicly available OnHW dataset serve as a baseline for future research in that area.
learning the dynamic appearance and shape of facial action units. In: Winter Conference on Applications of Computer Vision (WACV), 7-9 March 2016, Lake Placid, USA. (In Press)

Spontaneous facial expression recognition under uncon-trolled conditions is a hard task. It depends on multiple factors including shape, appearance and dynamics of the facial features, all of which are adversely affected by environmen-tal noise and low intensity signals typical of such conditions. In this work, we present a novel approach to Facial Action Unit detection using a combination of Convolutional and Bi-directional Long Short-Term Memory Neural Networks (CNN-BLSTM), which jointly learns shape, appearance and dynamics in a deep learning manner. In addition, we introduce a novel way to encode shape features using binary image masks computed from the locations of facial landmarks. We show that the combination of dynamic CNN features and Bi-directional Long Short-Term Memory ex-cels at modelling the temporal information. We thoroughly evaluate the contributions of each component in our system and show that it achieves state-of-the-art performance on the FERA-2015 Challenge dataset.
Neural network classification based on quantification of uncertainty

This thesis deals with feedforward backpropagation neural networks and interval neutrosophic sets for the binary and multiclass classification problems. Neural networks are used to predict “true” and “false” output values. These results together with the uncertainty of type error and vagueness occurred in the prediction are then represented in the form of interval neutrosophic sets. Each element in an interval neutrosophic set consists of three membership values: truth, indeterminacy, and false. These three membership values are then used in the classification process. For binary classification, a pair of neural networks is first applied in order to predict the degrees of truth and false membership values. Subsequently, bagging technique is applied to an ensemble of pairs of neural networks in order to improve the performance. For multiclass classification, two basic multiclass classification methods are proposed. A pair of neural networks with multiple outputs and multiple pairs of binary neural network are experimented. A number of aggregation techniques are proposed in this thesis. The difference between each pair of the truth and false membership values determines the vagueness value. Error occurred in the prediction are estimated using an interpolation technique. Both vagueness and error then form the indeterminacy membership. Two and three dimensional visualization of the three membership values are also presented. Ten data sets obtained from UCI machine learning repository are experimented with the proposed approaches. The approaches are also applied to two real world problems: mineral prospectivity prediction and lithofacies classification.
Source and Use of Insecticide Treated Net and Malaria Prevalence

This study argues that different practices of sources from which households obtain their Insecticide Treated Nets (ITNs) determine the effect of ITN use on malaria prevalence. The study categorises the sources into those that include some sort of education about how to use the nets and those that do not and examines the effect of these sources on the relationship between ITN use and malaria prevalence among children under-five in Ghana. A recursive bivariate probit estimation technique that addresses endogeneity between ITN use and malaria prevalence was used to analyse data on 2,908 under-five children from the 2011 Multiple Indicator Cluster Survey (MICS). The descriptive results revealed that the proportion of ITN usage among children in households who acquired their ITNs from government, NGOs and Community Based Agents (CBAs) was higher than the proportion of usage among those who acquired their ITNs from private health centers, market, shops and street vendors that do not include education. The estimation shows that controlling for other socio-demographic factors, sleeping under ITN reduces the likelihood of experiencing malaria by 22 percent. Owners of ITNs will not use them to bring the expected reduction in malaria prevalence, unless the source includes education.
Comments on Entanglement Entropy in the dS/CFT Correspondence

We consider the entanglement entropy in the dS/CFT correspondence.In Einstein gravity on de Sitter spacetime we propose the holographic entanglement entropy as the analytic continuation of the extremal surface in Euclidean anti-de Sitter spacetime.Even though dual conformal field theories for Einstein gravity on de Sitter spacetime have not been known yet,we analyzed the free $Sp(N)$ model dual to Vasiliev's higher spin gauge theory as a toy model.In this model we confirmed the behaviour similar to our holographic result from Einstein gravity.
Efforts to improve nutrition in remote Aboriginal communities over the last three decades: lessons from Mai Wiru and the Anangu Pitjantjatjara Yankunytjatjara Lands.

Objective: To examine the impact of efforts to improve nutrition on the Anangu Pitjantjatjara Yankunytjatjara (APY) Lands from 1986, especially in Mai Wiru (good food) stores. Methods: Multiple methods were employed. Literature was searched in a systematic manner. In 2012, the store-turnover method quantified dietary intake of the five APY communities that have a Mai Wiru store. The price of a standard market basket of basic foods, implementation of store nutrition policy requirements and healthy food checklists were also assessed in all seven APY community stores at intervals from 2012. Results were compared with available data dating from 1986. Results: Despite concerted efforts and marked achievements including decreased intake of sugar, increased availability and affordability of healthy foods (particularly fruit and vegetables) and consequent improvement in some nutrient intakes, the overall effect has been a decrease in total diet quality since 1986. This is characterised by increased supply and intake of discretionary foods high in saturated fat, added sugar and salt, particularly sugar sweetened beverages, convenience meals and take-away foods. Conclusions: The documented improvements confirm that residing in these communities can help Aboriginal residents exert control over key aspects of their food supply. However, the overall findings reflect broader changes to the general Australian food supply, and reinforce the notion that, in the absence of supportive regulation and market intervention, adequate and sustained resources are required to improve nutrition and prevent diet-related chronic disease on the APY Lands. Implications : This study also provides insights into food supply/security issues affecting other remote communities and wider Australia.
HIV_A_257502 331..339

1Department of Psychiatry, College of Health Science, Aksum University, Aksum, Ethiopia; 2Department of Psychiatry, College of Medicine and Health Science, Dilla University, Dilla, Ethiopia Background: Suicide is a psychiatric emergency and the second leading cause of death among youths. Suicide risk is 7 to 36 times greater among PLWHA as compared to the general population. This study was aimed at determining the prevalence of suicide and its associated factors among PLWHA and attendings at Hiwot Fana Specialized University Hospital, Ethiopia, 2020. Patients and Methods: We conducted a cross-sectional study on 412 randomly selected respondent PLWHA and attendingz at Hiwot Fana Specialized University Hospital from February 1–March 1, 2020. The interviewers administered a structured questionnaire consisting of the World Health Organization Composite International Diagnostic Interview (CIDI) tool to measure suicidality. We used the clinical records to collect clinical variables of the respondents. We used simple logistic regression ≤ 0.25 at p-value ≤ 0.25 and multiple logistic regression at p-value ≤ 0.05 to identify the predictor variables of the outcome. Results: A total of 412 participants have completed the questionnaire, with a response rate of 97.4%. The majority, 252 (61.2) of the participants were female, while 112 (27.2%) of the respondents were in the age group of 28–37. The prevalence of suicidal ideation and attempt among PLWHA was 24.3% (CI; 20.4, 28.4) and 12.6% (9.5–15.8), respectively. Predictors for suicidal ideation were being in extreme poverty, living alone, widowed, CD4 level less than 250, and current alcohol use, and for suicidal attempt were an urban residence, stage IV HIV, family history of suicide, and depression. Conclusion: Nearly one-fourth of the respondents reported suicidal ideation. So, early screening and working on those identified predictors of suicidality is vital to prevent the mortality of it in PLWHA.
In vivo Identification of Photosystem II Light Harvesting Complexes Interacting with PSBS

Running head: Identification of PSBS-antennae interactions 1 2 Corresponding author: Tomas Morosinotto, 3 Address: Dipartimento di Biologia, Università di Padova, Via U. Bassi 58/B 35121, Padova, Italy. 4 Tel. +390498277484; Fax. +390498276300; 5 e-mail: tomas.morosinotto@unipd.it 6 7 Research area: 8 Membranes, Transport and Bioenergetics: Associate Editor Anna Amtmann (Glasgow) 9 10 11 Plant Physiology Preview. Published on June 11, 2015, as DOI:10.1104/pp.15. 00361
Spectral/quadrature duality: Picard-Vessiot theory and finite-gap potentials

In the framework of differential Galois theory we treat the classical spectral problem $\Psi"-u(x)\Psi=\lambda\Psi$ and its finite-gap potentials as exactly solvable in quadratures by Picard--Vessiot without involving special functions; the ideology goes back to the 1919 works by J. Drach. We show that duality between spectral and quadrature approaches is realized through the Weierstrass permutation theorem for a logarithmic Abelian integral. From this standpoint we inspect known facts and obtain new ones: an important formula for the $\Psi$-function and $\Theta$-function extensions of Picard--Vessiot fields. In particular, extensions by Jacobi's $\theta$-functions lead to the (quadrature) algebraically integrable equations for the $\theta$-functions themselves.
ON MECHANICAL PROPERTIES OF CONCRETE

An ecoment, a recycled coarce aggregate and a recycled PET fiber were employed as recycled materials. Three point bending test with notched beams and shear tests of RC beams were conducted. The results of these tests show that the mechanical properties of concrete using the ecocement provide the similar behavior to that of normal concrete. The mechanical properties of concrete using both the ecocement and the recycled aggregate decreases comparing with that of normal concrete. However, the mechanical properties can be improved due to the reduction of water cement ratio, the increase in the amount of coarse aggregate and the adding the recycled PET fiber. Finally, the nonlinear finite element analysis using the tension softening curve was conducted. The shear carring capacity could be approximately predicted by the nonlinear finite element analysis.
DETERMINATION OF CHEMICAL PARAMETERS OF BEEF AND ITS PRODUCTS

acid value, sausage had the highest mean concentration (1.149 mgkoH /gm of fat) while, frozen beef samples showed the lowest value (1.130 mgkoH /gm). Rgarding free fatty acids, the highest mean concentration (0.750ml/gm) was found in sausage while the lowest (0.565 ml /gm) was in frozen beef samples. In case of conjugated dienes (CD), the highest level (0.069 n mole/mg) was in sausage samples while the lowest (0.041 n mole/mg) was in frozen beef. Concerning thiobarbeturic acid value (TBA), sausage also showed the highest level (0.901 mg malonaldhyde /kg of sample) while frozen beef samples showed the lowest (0.7018 mg malonaldhyde /kg of sample).
Towards an Aspectual Analysis of Legacy Systems

Aspect-Oriented software development provides explicit mechanisms for coping with concerns that crosscut many components and are tangled within individual components. Current AOSD approaches have primarily focused on coping with crosscutting concerns in software systems that are developed from scratch. In this paper we will investigate the applicability of AOSD to the evolution of legacy information systems. Various approaches have been already proposed to enhance LIS, however, these approaches have not explicitly considered crosscutting concerns and/or AOP techniques. We provide a categorization of legacy systems and give some early results in identifying and specifying aspects in legacy systems.
Asymptotic Bias and Equivalence of GMM and GEL Estimators

A number of recent studies have concluded that the most commonly used efficient two-step generalized method of moments (GMM) estimator may have large bias in applications. This problem has motivated the search for alternative efficient estimators with smaller bias. Estimators which have received some attention in the literature are the continuous updating estimator (CUE), the empirical likelihood estimator, and the exponential tilting estimator. We show that the continuous updating estimator is a member of a generalized empirical likelihood (GEL) class that also includes exponential tilting and empirical likelihood. Also, we derive stochastic expansions for each of the estimators along with asymptotic bias expressions. We find that an important part of the bias of GEL estimators will tend to be less than that of GMM with many moment conditions, and that the bias ∗This research was initiated when the first author was Benjamin Meaker Visiting Professor at the University of Bristol. Helpful comments were provided by G. Imbens and seminar participants at Bristol. The NSF provided partial financial support for the first author and the research of the second author was supported by the ESRC under Grant No. R000237386. of empirical likelihood is the same as a GMM estimator where the optimal linear combination coefficients are known. JEL Classification: C13, C30
3D Interacting Hand Pose Estimation by Hand De-occlusion and Removal

Estimating 3D interacting hand pose from a single RGB image is essential for understanding human actions. Unlike most previous works that directly predict the 3D poses of two interacting hands simultaneously, we propose to decompose the challenging interacting hand pose estimation task and estimate the pose of each hand separately. In this way, it is straightforward to take advantage of the latest research progress on the single-hand pose estimation system. However, hand pose estimation in interacting scenarios is very challenging, due to (1) severe hand-hand occlusion and (2) ambiguity caused by the homogeneous appearance of hands. To tackle these two challenges, we propose a novel Hand De-occlusion and Removal (HDR) framework to perform hand de-occlusion and distractor removal. We also propose the first large-scale synthetic amodal hand dataset, termed Amodal InterHand Dataset (AIH), to facilitate model training and promote the development of the related research. Experiments show that the proposed method significantly outperforms previous state-of-the-art interacting hand pose estimation approaches. Codes and data are available at https://github.com/MengHao666/HDR.
Algorithmic fairness in business analytics: Directions for research and practice

The extensive adoption of business analytics (BA) has brought financial gains and increased efficiencies. However, these advances have simultaneously drawn attention to rising legal and ethical challenges when BA inform decisions with fairness implications. As a response to these concerns, the emerging study of algorithmic fairness deals with algorithmic outputs that may result in disparate outcomes or other forms of injustices for subgroups of the population, especially those who have been historically marginalized. Fairness is relevant on the basis of legal compliance, social responsibility, and utility; if not adequately and systematically addressed, unfair BA systems may lead to societal harms and may also threaten an organization's own survival, its competitiveness, and overall performance. This paper offers a forward‐looking, BA‐focused review of algorithmic fairness. We first review the state‐of‐the‐art research on sources and measures of bias, as well as bias mitigation algorithms. We then provide a detailed discussion of the utility–fairness relationship, emphasizing that the frequent assumption of a trade‐off between these two constructs is often mistaken or short‐sighted. Finally, we chart a path forward by identifying opportunities for business scholars to address impactful, open challenges that are key to the effective and responsible deployment of BA.
SPRT-Based Efficient Best Arm Identification in Stochastic Bandits

This paper investigates the best arm identification (BAI) problem in stochastic multi-armed bandits in the fixed confidence setting. The general class of the exponential family of bandits is considered. The existing algorithms for the exponential family of bandits face computational challenges. To mitigate these challenges, the BAI problem is viewed and analyzed as a sequential composite hypothesis testing task, and a framework is proposed that adopts the likelihood ratio-based tests known to be effective for sequential testing. Based on this test statistic, a BAI algorithm is designed that leverages the canonical sequential probability ratio tests for arm selection and is amenable to tractable analysis for the exponential family of bandits. This algorithm has two key features: (1) its sample complexity is asymptotically optimal, and (2) it is guaranteed to be $\delta -$ PAC. Existing efficient approaches focus on the Gaussian setting and require Thompson sampling for the arm deemed the best and the challenger arm. Additionally, this paper analytically quantifies the computational expense of identifying the challenger in an existing approach. Finally, numerical experiments are provided to support the analysis.
Indirect constraints on lepton-flavor-violating quarkonium decays

Within an eﬀective-ﬁeld-theory framework, we present a model-independent analysis of the potential of discovering new physics by searching for lepton ﬂavour violation in heavy quarkonium decays and, more in general, we study the phenomenology of lepton-ﬂavour-violating (LFV) 2 quark - 2 lepton ( 2 q 2 (cid:96) ) operators with two charm or bottom ﬁelds. We compute the constraints from LFV muon and tau decays on the new-physics operators that can induce LFV processes involving c ¯ c and b ¯ b systems, thus providing a comprehensive list of indirect upper limits on processes such as J/ψ → (cid:96)(cid:96) (cid:48) , Υ( nS ) → (cid:96)(cid:96) (cid:48) , Υ( nS ) → (cid:96)(cid:96) (cid:48) γ etc., which can be sought at BESIII, Belle II, and the proposed super tau-charm factory. We show that such indirect constraints are so stringent that they prevent the detection of quarkonium decays into eµ . In the case of decays of quarkonia into (cid:96)τ ( (cid:96) = e, µ ), we ﬁnd that an improvement by 2-3 orders of magnitude on the current sensitivities is in general required in order to discover or further constrain new physics. However, we show that cancellations among diﬀerent contributions to the
Magnetotransport in overdoped La$_{2-x}$Sr$_x$CuO$_4$: Effect of anisotropic scattering

We revisit the Hall eﬀect and magnetoresistivity by incorporating the anisotropic scattering caused by apical oxygen vacancies in overdoped La-based cuprates 1 . The theoretical calculations within the Fermi liquid picture agree well with a handful of anomalous magneto-transport data, better than the results using an isotropic scattering rate alone. In particular, we obtain the upturn of Hall coeﬃcient R H with decreasing temperature T 2,3 , the initial drop of R H in magnetic ﬁeld B in all overdoped regimes 4,5 , the linear resistivity ρ versus B near the van Hove doping level 6,7 , the temperature dependence of the magnetoresistivity ratio 6–9 , and the violation of Kohler’s law 8,9 . These results suggest that many of the anomalous transport behaviors in overdoped La 2 − x Sr x CuO 4 could actually be understood within the Fermi liquid picture.
The integration theory of curved absolute homotopy Lie algebras

The main goal of this thesis is to develop the integration theory of curved homotopy Lie algebras. In the first chapter, we develop the operadic calculus needed: we encode non-necessarily conilpotent coalgebras with operads and introduce their dual notion of an algebra over a cooperad, which we call"absolute algebras". The first sections of this chapter are a state of the art, and the last three sections are made of original results. In the second chapter, we develop the new theory of curved operadic calculus, which allows us to encode curved types of algebras with curved operads. Finally, in the third chapter, we develop the integration theory of curved absolute homotopy Lie algebras using the tools introduced in the first two chapters. This new approach allows us to obtain applications to deformation theory and rational homotopy theory.