Miracle-dz/UniFAR-FTUs huggingface dataset:
Assortment Planning and Inventory Decisions Under Stockout-Based Substitution

We present an efficient dynamic programming algorithm to determine the optimal assortment and inventory levels in a single-period problem with stockout-based substitution. In our model, total customer demand is random and comprises fixed proportion of customers of different types. Customer preferences are modeled through the definition of these types. Each customer type corresponds to a specific preference ordering among products. A customer purchases the highest-ranked product, according to his type (if any), that is available at the time of his visit to the store (stockout-based substitution). We solve the optimal assortment problem using a dynamic programming formulation. We establish structural properties of the value function of the dynamic program that, in particular, help to characterize multiple local maxima. We use the properties of the optima to solve the problem in pseudopolynomial time. Our algorithm also gives a heuristic for the general case, i.e., when the proportion of customers of each type is random. In numerical tests, this heuristic performs better and faster than previously known methods, especially when the mean demand is large, the degree of substitutability is high, the population is homogeneous, or prices and/or costs vary across products.
Robust RA Estimators in AR-2D Models for Images

Usually it is adopted for processing and analysis of images SAR, the multiplicative model ( ) ( ) ( ) n m n m n m Y X Z , , , = , where Z are the observations, X is the backscatter process and Y the noise speckle. In Frost et al (1982) (mentioned by Sant'Anna (1995)) a model AR-2D is suggested for the process X. Because the noise speckle is not cleaned totally, the robust methods are the most appropriate alternative to estimate this model's parameters. The purpose of this paper is to present a proposal of robust estimation in the AR-2D contaminated model: The RA estimators. They conform the bidimensional version of the estimators based on the residual covariances for the ARMA unidimensional models, introduced by Bustos and Yohai (1986).
Gauge-Invariant Ideals in the C*-Algebras of Finitely Aligned Higher-Rank Graphs

Abstract We produce a complete description of the lattice of gauge-invariant ideals in ${{C}^{*}}(\Lambda )$ for a finitely aligned $k$ -graph $\Lambda $ . We provide a condition on $\Lambda $ under which every ideal is gauge-invariant. We give conditions on $\Lambda $ under which ${{C}^{*}}(\Lambda )$ satisfies the hypotheses of the Kirchberg–Phillips classification theorem.
Research Directions for AI in Computer Games

The computer games industry is now bigger than the film industry. Until recently, technology in games was driven by a desire to achieve real-time, photo-realistic graphics. To a large extent, this has now been achieved. As game developers look for new and innovative technologies to drive games development, AI is coming to the fore. This paper will examine how sophisticated AI techniques, such as those being used in mainstream academic research, can be applied to computer games and introduce three projects doing just that.
Application of data mining techniques in customer realationship management for an automobile company

This work analyzes well-known DM techniques in Weka workbench, and reports the simulation results of applying four selected DM techniques and classifiers in the open source workbench to the Customer Relationship Management (CRM) problem in an automobile enterprise. It is proposed that data mining techniques to be used in aiding the salesperson and management of the enterprise for effective decision making. This approach was applied to 500 preprocessed records out of 2000 raw data sets for the past 5 years. Simulation results show that the large volume of customer historical data can play a value-added role for enterprise development in a way that the mined data helps them to study customer behavior so that personalized services can be provided. This paper also discusses the evaluation results of the four classifiers used in mining the customer data.
Markerless 3D Hand Posture Estimation from Monocular Video by Two-Level Searching

In this paper, a marker less 3D hand tracking system for monocular RGB video is presented. We propose a novel two-level approach to efficiently grasp the personal characteristics and high varieties of hand postures. Our system first searches the approximate nearest neighbors in a small personalized real-hand image set, and retrieves more details from a large synthetic 3D hand posture database. Temporal consistency property is also utilized for disambiguating and noise reduction. Our prototype system can approximate hand poses including rigid and non-rigid out-of-image-plane rotation, slow and fast gesture changing during rotation. It can also recover from a short-term missing hand situation in an interactive rate.
A Dyadic Study of Relational Turbulence and Communication in Cross-sex Friendships

ii Dedication.iii Vita.iv List of Tables.vii List of Figures.viii Chapter 1: Introduction and Overview.1 Cross-sex Friendships.2 Relational Turbulence.5 Relational Turbulence in Cross-sex Friendships.8 Channel Selection and Use.12 Dyadic Data Analysis.19 Chapter 2: Study 1.24 Method.25 Results.27 Discussion.35 Chapter 3: Study 2 Method.38 Recruitment . 38 Sample . 39 viii Measures . 39 Chapter 4: Data Analysis and Results.45 Data Preparation.45 Preliminary Analyses.48 Substantive Analyses.50 Chapter 5: Discussion and Conclusions.56 Summary of Study 1 Results.56 Summary of Study 2 Results.58 Implications.61 Limitations and Future Directions . 63 References . 66 Appendix A: Tables and Figures.77 Appendix B: Study 1 Interview Guide . 90
Cystinosin, MPDU1, SWEETs and KDELR Belong to a Well-Defined Protein Family with Putative Function of Cargo Receptors Involved in Vesicle Trafficking

Classification of proteins into families based on remote homology often helps prediction of their biological function. Here we describe prediction of protein cargo receptors involved in vesicle formation and protein trafficking. Hidden Markov model profile-to-profile searches in protein databases using endoplasmic reticulum lumen protein retaining receptors (KDEL, Erd2) as query reveal a large and diverse family of proteins with seven transmembrane helices and common topology and, most likely, similar function. Their coding genes exist in all eukaryota and in several prokaryota. Some are responsible for metabolic diseases (cystinosis, congenital disorder of glycosylation), others are candidate genes for genetic disorders (cleft lip and palate, certain forms of cancer) or solute uptake and efflux (SWEETs) and many have not yet been assigned a function. Comparison with the properties of KDEL receptors suggests that the family members could be involved in protein trafficking and serve as cargo receptors. This prediction sheds new light on a range of biologically, medically and agronomically important proteins and could open the way to discovering the function of many genes not yet annotated. Experimental testing is suggested.
Emil Mottola

We analyze the constraints of general coordinate invariance for quantum theories possessing conformal symmetry in four dimensions. The character of these constraints simplifies enormously on the Einstein universe R × S 3. The SO(4, 2) global conformal symmetry algebra of this space determines uniquely a finite shift in the Hamiltonian constraint from its classical value. In other words, the global Wheeler-De Witt equation is modified at the quantum level in a well-defined way in this case. We argue that the higher moments of T 00 should not be imposed on the physical states a priori either, but only the weaker condition ˙ T 00 = 0. We present an explicit example of the quantization and diffeomorphism constraints on R × S 3 for a free conformal scalar field.
Ferulic acid ethyl ester protects neurons against amyloid β‐ peptide(1–42)‐induced oxidative stress and neurotoxicity: relationship to antioxidant activity

Alzheimer's disease (AD) is neuropathologically characterized by depositions of extracellular amyloid and intracellular neurofibrillary tangles, associated with loss of neurons in the brain. Amyloid β‐peptide (Aβ) is the major component of senile plaques and is considered to have a causal role in the development and progress of AD. Several lines of evidence suggest that enhanced oxidative stress and inflammation play important roles in the pathogenesis or progression of AD. The present study aimed to investigate the protective effects of ethyl‐4‐hydroxy‐3‐methoxycinnamic acid (FAEE), a phenolic compound which shows antioxidant and anti‐inflammatory activity, on Aβ(1–42)‐induced oxidative stress and neurotoxicity. We hypothesized that the structure of FAEE would facilitate radical scavenging and may induce protective proteins. Aβ(1–42) decreases cell viability, which was correlated with increased free radical formation, protein oxidation (protein carbonyl, 3‐nitrotyrosine), lipid peroxidation (4‐hydroxy‐2‐trans‐nonenal) and inducible nitric oxide synthase. Pre‐treatment of primary hippocampal cultures with FAEE significantly attenuated Aβ(1–42)‐induced cytotoxicity, intracellular reactive oxygen species accumulation, protein oxidation, lipid peroxidation and induction of inducible nitric oxide synthase. Treatment of neurons with Aβ(1–42) increases levels of heme oxygenase‐1 and heat shock protein 72. Consistent with a cellular stress response to the Aβ(1–42)‐induced oxidative stress, FAEE treatment increases the levels of heme oxygenase‐1 and heat shock protein 72, which may be regulated by oxidative stresses in a coordinated manner and play a pivotal role in the cytoprotection of neuronal cells against Aβ(1–42)‐induced toxicity. These results suggest that FAEE exerts protective effects against Aβ(1–42) toxicity by modulating oxidative stress directly and by inducing protective genes. These findings suggest that FAEE could potentially be of importance for the treatment of AD and other oxidative stress‐related diseases.
Comparison of speaker dependent and speaker independent emotion recognition

Abstract This paper describes a study of emotion recognition based on speech analysis. The introduction to the theory contains a review of emotion inventories used in various studies of emotion recognition as well as the speech corpora applied, methods of speech parametrization, and the most commonly employed classification algorithms. In the current study the EMO-DB speech corpus and three selected classifiers, the k-Nearest Neighbor (k-NN), the Artificial Neural Network (ANN) and Support Vector Machines (SVMs), were used in experiments. SVMs turned out to provide the best classification accuracy of 75.44% in the speaker dependent mode, that is, when speech samples from the same speaker were included in the training corpus. Various speaker dependent and speaker independent configurations were analyzed and compared. Emotion recognition in speaker dependent conditions usually yielded higher accuracy results than a similar but speaker independent configuration. The improvement was especially well observed if the base recognition ratio of a given speaker was low. Happiness and anger, as well as boredom and neutrality, proved to be the pairs of emotions most often confused.
An Interview-Based Case Study in Software Architecture Evolution

In recent years, researchers have worked to develop approaches and models to support software architects in planning and carrying out major evolutions of software systems. To date, this line of work has been largely theoretical. These new approaches and models are seldom accompanied by empirical evidence to support them, let alone subjected to rigorous empirical evaluation. This paper describes a formal case study examining architecture evolution in a real-world organization. Based on content analysis of interview data and architectural documentation, the study examines how practicing architects plan and reason about evolution, what challenges they face, and whether the modeling approach developed in our previous work can capture the concerns that arise in a real-world evolution.
Period–luminosity relations for Galactic Cepheid variables with independent distance measurements

In this paper, we derive the period-luminosity (PL) relation for Galactic Cepheids with recent independent distance measurements from open cluster, Barnes-Evans surface brightness, interferometry and Hubble Space Telescope astrometry techniques. Our PL relation confirms the results from recent works, which showed that the Galactic Cepheids follow a different PL relation to their Large Magellanic Cloud (LMC) counterparts. Our results also show that the slope of the Galactic PL relation is inconsistent with the LMC slope with more than 95 per cent confidence level. We apply this Galactic PL relation to find the distance to NGC 4258. Our result of μ o = 29.49 ± 0.06 mag (random error) agrees at the ∼1. 4σ level with the geometrical distance of μ = 29.28 ± 0.15 mag from water maser measurements.
Securing Vehicle to Vehicle Communications using Blockchain through Visible Light and Acoustic Side-Channels

Autonomous and self-driving vehicles are appearing on the public highways. These vehicles commonly use wireless communication techniques for both vehicle-to-vehicle and vehicle-to-infrastructure communications. Manufacturers, regulators and the public are understandably concerned about large-scale systems failure or malicious attack via these wireless vehicular networks. This paper explores the use of sensing and signalling devices that are commonly integrated into modern vehicles for side-channel communication purposes. Visible light (using a CMOS camera) and acoustic (ultrasonic audio) side-channel encoding techniques are proposed, developed and evaluated in this context. The side-channels are examined both theoretically and experimentally and an upper bound on the line code modulation rate that is achievable with these side channel schemes in the vehicular networking context is established. A novel inter-vehicle session key establishment protocol, leveraging both side-channels and a blockchain public key infrastructure, is then presented. In light of the limited channel capacity and the interoperability/security requirements for vehicular communications, techniques for constraining the throughput requirement, providing device independence and validating the location of the intended recipient vehicle, are presented. These reduce the necessary device handshake throughput to 176 bits for creating symmetric encryption and message authentication keys and in verifying a vehicle's certificate with a recognised certification authority.
Fast Face-Swap Using Convolutional Neural Networks

We consider the problem of face swapping in images, where an input identity is transformed into a target identity while preserving pose, facial expression and lighting. To perform this mapping, we use convolutional neural networks trained to capture the appearance of the target identity from an unstructured collection of his/her photographs. This approach is enabled by framing the face swapping problem in terms of style transfer, where the goal is to render an image in the style of another one. Building on recent advances in this area, we devise a new loss function that enables the network to produce highly photorealistic results. By combining neural networks with simple pre- and post-processing steps, we aim at making face swap work in real-time with no input from the user.
Location-aware Friend Recommendation in Event-based Social Networks: A Bayesian Latent Factor Approach

In this paper we study the friend recommendation problem in event-based social networks (EBSNs). Effective friend recommendation is of benefit to EBSNs, since it can promote user interaction and accelerate information diffusion for promoted events. Different from usual friend recommendations, the aim of making friends in EBSNs is to better participate offline events and enhance user experience. Meanwhile friend recommendation in EBSNs encounters three types of data, i.e. geographical information, implicate user rating, and user behavior. These differences imply that existing friend recommendation approaches are not adequate any more for EBSNs. Under this background, in this paper we propose a Bayesian latent factor model, which can jointly formulate above three types of data, for friend recommendation with better event promotion and user experience. Results on real-world datasets show the efficacy of our approach.
Shifted Subspaces Tracking on Sparse Outlier for Motion Segmentation

In low-rank & sparse matrix decomposition, the entries of the sparse part are often assumed to be i.i. d. sampled from a random distribution. But the structure of sparse part, as the central interest of many problems, has been rarely studied. One motivating problem is tracking multiple sparse object flows (motions) in video. We introduce "shifted subspaces tracking (SST)" to segment the motions and recover their trajectories by exploring the low-rank property of background and the shifted subspace property of each motion. SST is composed of two steps, background modeling and flow tracking. In step 1, we propose "semi-soft GoDec" to separate all the motions from the low-rank background L as a sparse outlier S. Its soft-thresholding in updating S significantly speeds up GoDec and facilitates the parameter tuning. In step 2, we update X as S obtained in step 1 and develop "SST algorithm" further decomposing X as X = Σi=1k L(i)oτ(i)+ S+G, wherein L(i) is a low-rank matrix storing the ith flow after transformation τ(i). SST algorithm solves k sub-problems in sequel by alternating minimization, each of which recovers one L(i) and its τ(i) by randomized method. Sparsity of L(i) and between-frame affinity are leveraged to save computations. We justify the effectiveness of SST on surveillance video sequences.
Effect of information quality on decision performance at regency development priorities

Information quality (IQ) is essential for decision-making. Several research have been undertaken to analysis relationship between information quality and decision-making. Since the eGovernment has emerged in Indonesia, many government institutions have deployed Information System (IS) in their public services. Unfortunately, deployment of IS in government institutions are not followed by mature planning. Consequently, IS deployment did not give significant impact on information quality. It is time for Local Government to review their IS from customer perspective. We recommend that IS deployment should not only improve its accessibility IQ but should also improve its contextual IQ, intrinsic IQ and representational IQ.
Clinical Significance of Pre- and Post-Transplant BAFF Levels in Kidney Transplant Recipients

It is well known that pre-transplant B cell activating factor (BAFF) levels are associated with the development of de novo anti-HLA antibodies and antibody mediated rejection post-transplant. However, the clinical significance of BAFF values at allograft rejection has not been determined. In this study, we investigated the clinical significance of pre-transplant BAFF level as well as post-transplant BAFF levels measured when indication biopsy was done. We checked for anti-HLA antibodies in 115 kidney transplant recipients who required allograft biopsy due to an increase in serum creatinine. With the same serum specimen, we measured BAFF levels, and in 78 of these patients, pre-transplant BAFF and anti-HLA antibody levels were detected as well. Patients in each group were divided into tertiles according to BAFF levels. We investigated the relationship between BAFF levels and the occurrence of anti-HLA antibodies. Pre-transplant BAFF levels showed significant association with pre-transplant sensitization, and also with early rejection (Tertile 3, 26.9% vs. Tertile 1, 11.5%; P<0.05). Post-transplant BAFF levels showed significant association with pre-transplant sensitization, but did not show association with anti-HLA antibodies and positive donor-specific antibodies at the time of biopsy. We did not find any association between post-transplant BAFF levels and allograft biopsy results, Banff scores and microvascular inflammation scores. In conclusion, pre-transplant BAFF levels are associated with pre-transplant sensitization and are useful in predicting allograft rejection. But post-transplant BAFF levels measured at the time of indication biopsy are not associated with the appearance of de novo HLA-DSA, allograft rejection, biopsy findings and other allograft outcomes.
Promising Noninvasive Cellular Phenotype in Prostate Cancer Cells Knockdown of Matrix Metalloproteinase 9

Cell surface interaction of CD44 and MMP9 increases migration and invasion of PC3 cells. We show here that stable knockdown of MMP9 in PC3 cells switches CD44 isoform expression from CD44s to CD44v6 which is more glycosylated. These cells showed highly adhesive morphology with extensive cell spreading which is due to the formation of focal adhesions and well organized actin-stress fibers. MMP9 knockdown blocks invadopodia formation and matrix degradation activity as well. However, CD44 knockdown PC3 cells failed to develop focal adhesions and stress fibers; hence these cells make unstable adhesions. A part of the reason for these changes could be caused by silencing of CD44v6 as well. Immunostaining of prostate tissue microarray sections illustrated significantly lower levels of CD44v6 in adenocarcinoma than normal tissue. Our results suggest that interaction between CD44 and MMP9 is a potential mechanism of invadopodia formation. CD44v6 expression may be essential for the protection of non-invasive cellular phenotype. CD44v6 decrease may be a potential marker for prognosis and therapeutics.
A Multi-band OFDM System in HF Communications

In allusion to the character of HF channels, this paper presents an MB-OFDM system, which uses hopping carrier to reduce ISI caused by multi-paths in HF communications. Theoretic analysis shows the system with Rake receiver can improved the BER performance significantly. Monte Carlo simulation results confirm the conclusion and show that more improvement is obtained when the path number increases. These results proved the proposed system can work well in HF fading channel under low SNR