Miracle-dz/UniFAR-FTUs huggingface dataset:
Weakly Paired Multi-Domain Image Translation

In this paper, we aim at studying the new problem of weakly paired multi-domain image translation. To this end, we collect a dataset that contains weakly paired images from multiple domains. Two images are considered to be weakly paired if they are captured from nearby locations and share an overlapping ﬁeld of view. These images are possibly captured by two asynchronous cameras—often resulting in images from separate domains, e.g. summer and winter. Major motivations for using weakly paired images are: (i) performance improvement towards that of paired data; (ii) cheap labels and abundant data availability. For the ﬁrst time in this paper, we propose a multi-domain image translation method speciﬁcally designed for weakly paired data. The proposed method consists of an attention-based generator and a two-stream discriminator that deals with misalignment between source and target images. Our method generates images in the target domain while preserving source image content, including foreground objects such as cars and pedestrians. Our extensive experiments demonstrate the superiority of the proposed method in comparison to the state-of-the-art. The new dataset and the source code are available at https://github.com/zhangma123/weaklypaired .
A Potential Reduction Inspired Algorithm for Exact Max Flow in Almost O͠(m4/3) Time

We present an algorithm for computing $s$-$t$ maximum flows in directed graphs in $\widetilde{O}(m^{4/3+o(1)}U^{1/3})$ time. Our algorithm is inspired by potential reduction interior point methods for linear programming. Instead of using scaled gradient/Newton steps of a potential function, we take the step which maximizes the decrease in the potential value subject to advancing a certain amount on the central path, which can be efficiently computed. This allows us to trace the central path with our progress depending only $\ell_\infty$ norm bounds on the congestion vector (as opposed to the $\ell_4$ norm required by previous works) and runs in $O(\sqrt{m})$ iterations. To improve the number of iterations by establishing tighter bounds on the $\ell_\infty$ norm, we then consider the weighted central path framework of Madry \cite{M13,M16,CMSV17} and Liu-Sidford \cite{LS20}. Instead of changing weights to maximize energy, we consider finding weights which maximize the maximum decrease in potential value. Finally, similar to finding weights which maximize energy as done in \cite{LS20} this problem can be solved by the iterative refinement framework for smoothed $\ell_2$-$\ell_p$ norm flow problems \cite{KPSW19} completing our algorithm. We believe our potential reduction based viewpoint provides a versatile framework which may lead to faster algorithms for max flow.
Verifying replicated data types with typeclass refinements in Liquid Haskell

This paper presents an extension to Liquid Haskell that facilitates stating and semi-automatically proving properties of typeclasses. Liquid Haskell augments Haskell with refinement types—our work allows such types to be attached to typeclass method declarations, and ensures that instance implementations respect these types. The engineering of this extension is a modular interaction between GHC, the Glasgow Haskell Compiler, and Liquid Haskell’s core proof infrastructure. The design sheds light on the interplay between modular proofs and typeclass resolution, which in Haskell is coherent by default (meaning that resolution always selects the same implementation for a particular instantiating type), but in other dependently typed languages is not. We demonstrate the utility of our extension by using Liquid Haskell to modularly verify that 34 instances satisfy the laws of five standard typeclasses. More substantially, we implement a framework for programming distributed applications based on replicated data types (RDTs). We define a typeclass whose Liquid Haskell type captures the mathematical properties RDTs should satisfy; prove in Liquid Haskell that these properties are sufficient to ensure that replicas’ states converge despite out-of-order update delivery; implement (and prove correct) several instances of our RDT typeclass; and use them to build two realistic applications, a multi-user calendar event planner and a collaborative text editor.
The Feasibility of Financing Indonesian Migrant Workers by Islamic Banks

This paper identifies the profile of migrant workers located in Banyumas regency, assesses the financial feasibility of the scheme, and gauges the viability of the migrant workers financing from conventional and Islamic banks’ perspectives. The samples comprises potential migrant workers, ex-migrant workers and their relatives. The nature of the study is descriptive qualitative where both primary and secondary data were analysed during the study. The result of the study indicates that financing migrant workers to work abroad is economically desirable for both conventional and Islamic banks. Either mode of financing, Islamic and conventional, are advantageous to the Indonesian workers who want to work abroad.
2ST-UNet: 2-Stage Training Model using U-Net for Pneumothorax Segmentation in Chest X-Rays

Pneumothorax, also called a collapsed lung, is the presence of the air outside of the lung in the space between the lung and chest wall. It is generally diagnosed using a chest X-ray. However, for some cases, the diagnosis can be difficult as other medical conditions appear similarly. Machine Learning algorithms have been providing great assistance in detecting and locating pneumothorax lately. In this paper, we propose a 2-Stage Training system to segment images with pneumothorax. This system has been built based on U-Net, the state-of-the-art Fully Convolutional Network (FCN) architecture, with a backbone Residual Networks (ResNet-34) that is pre-trained on the ImageNet dataset. In the beginning, we train the network at a lower resolution. Then, we load the trained model weights to retrain the network with a higher resolution. Moreover, we utilize different techniques including Stochastic Weight Averaging (SWA), data augmentation, and Test-Time Augmentation (TTA). We use the chest X-ray dataset that is provided by the 2019 SIIM-ACR Pneumothorax Segmentation Challenge, which contains 12047 training images and 3205 testing images. Our experiments show that 2-Stage Training leads to better and faster network convergence. Our method achieves 0.8356 mean Dice coefficient placing it among the top 9% of competitors with a rank of 124 out of 1475.
Information Technology System-on-Chip

This paper presented a method constructing the ITSoC(Information Technology System-on-Chip). In order to implement the ITSoC, designers are increasing relying on reuse of intellectual property(IP) blocks. Since IP blocks are pre-designed and pre-verified, the designer can concentrate on the complete system without having to worry about the correctness or performance of the individual components. Also, embedded core in an ITSoC access mechanisms are required to test them at the system level. That is the goal, in theory. In practice, assembling an ITSoC using IP blocks is still an error-prone, labor-intensive and time-consuming process. This paper discuss the main challenge in ITSoC designs using IP blocks and elaborates on the methodology and tools being put in place for addressing the problem. It explains ITSoC architecture and gives algorithmic details on the high-level tools being developed for ITSoC design
Identification of Proteins Coded in Phage Lambda

Phage λ has sufficient DNA to encode about 50 proteins of molecular weight 33,000, and about 35 genes are known. However, fewer than ten λ proteins have been studied in any detail, largely because of the lack of specific assays for the others, and because host protein synthesis continues after infection by λ . This paper describes the labeling, identification, and characterization of λ proteins by a technique devised by Ptashne which circumvents these problems. The proteins identified belong to both the early and late classes, and several are products of genes which have not been described previously. EXPERIMENTAL METHOD The basic method used here to characterize λ proteins is to label them with radioactive amino acids and to compare the electrophoretic patterns of radioactive proteins obtained from various mutants. These experiments depend on the fact, first reported by Ptashne, that infection by wild-type λ ( λ + ), of cells heavily irradiated with ultraviolet light (UV), stimulates the ability of the cells to incorporate radioactive leucine into TCA-insoluble material by 10–15-fold (Ptashne, 1967). This technique makes it possible to label phage-specific proteins without an intolerable level of labeling of Escherichia coli proteins. Synthesis of Early and Late λ Proteins in Irradiated Bacteria Figure 1 shows the dependence of total leucine incorporation on UV dose for uninfected cells and for cells infected with three different phages. The ratio of incorporation between λ + -infected and uninfected cells can be seen to increase with dose up to about 12,000 erg/mm 2 and then to remain approximately constant.
A Random Walk From the Landau to the Riemann Hypothesis

The Riemann hypothesis is arguably the most important unsolved problem in mathematics. It is even difficult to state to beginning students since it requires a knowledge of the zeta function for complex values of the argument. However, there are at least 23 equivalent statements of this hypothesis that are much easier to state. In this paper we examine one such idea called the Landau hypothesis. This Landau hypothesis has a very simple interpretation in terms of the prime factorization of integers. Surprisingly this hypothesis also has a useful description in terms of a one dimensional random walk. We show by means of a known, but not often seen, integral representation for any Dirichlet series that the Landau hypothesis implies the Riemann hypothesis.
Product Quality, Duration, and Trade Growth

We investigate the effects of product quality on the probability of survival in export market and the trade growth condition on exports. We present a tractable model of heterogeneous firms and endogenous quality choices. The model shows that product quality is positively related to the probability of survival and trade growth. The empirical results using 5-digit SITC level bilateral trade data and IMF 4-digit SITC quality data support the theoretical predictions: products with higher quality are less likely to cease and have larger trade growth.
TP53 Mutation in Saudi Breast Cancer Patients: Correlations with Cancer Stem Cell Markers Expression and Clinicopathological Variables

Background: Breast cancer is one of the most common cancers with a high mortality rate worldwide including Saudi Arabia. It is characterized by the presence of both intraand intertumor heterogeneity. It describes the origin of this heterogeneity to the cancer stem cells (CSC). Breast cancer stem cells are characterized by the expression of the surface markers CD44 and lack or very low expression of CD24. Objectives: To assess cancer stem cell markers (CD44 andCD24) in 126 breast cancer cases by immunohistochemistry and study their association with a different type of TP53 gene mutations by applying next-generation sequencing (NGS). In addition to analyze the association between these markers and the clinicopathological characteristics. Results: CD44 expression was significantly associated with lymph node metastasis, tumor grade, stage (each P<0.0001), and ER expression (P = 0.016). CD24 expression was found to be associated with lymph node metastasis and ER only. For the molecular analysis, the number of mutations per case was significantly associated with the advanced stage of breast cancer (p = 0.004). Also, missense mutation was highly associated with CD44 and CD24 (p=0.04, p=0.005), respectively. Stop-gained mutation and Frameshift mutation both were associated with CD44 only (p=0.01, p=0.05), respectively. Finally, the synonymous mutation was only associated with the stage of cancer (p=0.01). Conclusion, we believe that the combination of CD44, CD24, TP53 and TP53 gene mutations can be prognostic factors for breast cancer patients and the information obtained may contribute to the development of a treatment.
The computation of a fi nite-frequency travel time sensitive kernel for P-waves in the AK 135 earth model *

Finite-frequency travel time tomography is a newly developing method. The main procedure in this new method is to compute the traveltime sensitive kernel. The travel time of the same scatterer needs to be used for computing the traveltime sensitive kernel many times. It is a time-consuming task. It is easy and fast to get the travel time from analytic equations in a simple model such as a homogenous or linear velocity media. However, most of the earth models are layered. It is cumbersome to get the travel time from analytic equations. In order to enhance the computation effi ciency, we used the table look-up method to compute the fi nite-frequency travel time sensitive kernel for P-waves in a layered structure model. We chose the AK135 earth model for the velocity model. The table look-up method saved about 50% of the computation time. We enhanced the computation speed by using the table lookup method in the same velocity model, which was very useful for enhancing the computation effi ciency for the fi nite-frequency travel time tomography.
Efficient spatial allocation of wind power plants given environmental externalities due to turbines and grids

Negative environmental externalities associated with wind power plants depend on the physical characteristics of turbine installations and associated power lines and the geographical siting. We derive analytically an environmental taxation scheme for achieving the efficient spatial distribution of new wind power production, taking account of both production and environmental costs. Further, we illustrate the analytical results by means of a detailed numerical energy system model for Norway. We show that a given target for wind power production can be achieved at a significantly lower social cost by implementing a tax scheme, compared to the current situation with no environmental taxes. We also show that the environmental costs associated with both turbines and power lines were crucial to the efficient spatial allocation of wind power plants.
Design and characteristics analysis of novel transverse flux switched reluctance generator for wind turbine

This paper presents design and characteristics analysis of transverse flux switched reluctance generator(TFSRG) for wind turbine. Dimension is calculated by using output equation and maximum magnetomotive force(mmf) equation per pole. Design specification within effective range of mechanical and electrical energy is suggested in order to perform the analysis. it is confirmed to torque, inductance and induced electromotive force(emf) for one phase through three dimension Finite Element Analysis. Then design specification can be verified by comparing with proposed specification.
On the Application of Prioritized Safe-interval Path Planning with Kinematic Constraints to the Single-shot Pickup and Delivery Problem

: In this paper, we address the multi-agent pickup and delivery problem, a variant of multi-agent path ﬁnding. Speciﬁcally, we decouple the problem into two parts: task allocation and path planning. We employ the any-angle safe-interval path planning algorithm introduced in our recent work and study the performance of several task allocation strategies. Furthermore, the proposed approach has been integrated into a control system to verify its feasibility in deployment on real robots. A key part of the system is a visual localization system which is based on the detection of unique artiﬁcial markers placed in the working environment. The conducted experiments show that generated plans can be safely executed on a real system.
An obstacle disturbance selection framework: emergent robot steady states under repeated collisions

Natural environments are often filled with obstacles and disturbances. Traditional navigation and planning approaches normally depend on finding a traversable “free space” for robots to avoid unexpected contact or collision. We hypothesize that with a better understanding of the robot–obstacle interactions, these collisions and disturbances can be exploited as opportunities to improve robot locomotion in complex environments. In this article, we propose a novel obstacle disturbance selection (ODS) framework with the aim of allowing robots to actively select disturbances to achieve environment-aided locomotion. Using an empirically characterized relationship between leg–obstacle contact position and robot trajectory deviation, we simplify the representation of the obstacle-filled physical environment to a horizontal-plane disturbance force field. We then treat each robot leg as a “disturbance force selector” for prediction of obstacle-modulated robot dynamics. Combining the two representations provides analytical insights into the effects of gaits on legged traversal in cluttered environments. We illustrate the predictive power of the ODS framework by studying the horizontal-plane dynamics of a quadrupedal robot traversing an array of evenly-spaced cylindrical obstacles with both bounding and trotting gaits. Experiments corroborate numerical simulations that reveal the emergence of a stable equilibrium orientation in the face of repeated obstacle disturbances. The ODS reduction yields closed-form analytical predictions of the equilibrium position for different robot body aspect ratios, gait patterns, and obstacle spacings. We conclude with speculative remarks bearing on the prospects for novel ODS-based gait control schemes for shaping robot navigation in perturbation-rich environments.
Deposited in DRO : 05 October 2018 Version of attached le : Published Version Peer-review status of attached

We provide a refined interpretation of a gravitational Wilson line in AdS3 in terms of Ishibashi states in the dual CFT2. Our strategy is to give a method to evaluate the Wilson line that accounts for all the information contained in the representation, and clarify the role of boundary conditions at the endpoints of the line operator. This gives a novel way to explore and reconstruct the local bulk dynamics which we discuss. We also compare our findings with other interpretations of Ishibashi states in AdS3/CFT2.
Running head: FLUENCY AND ORIGINALITY 1 Age-Related Similarities and Differences in the Components of Semantic Fluency: Analyzing the Originality and Organization of Retrieval from Long-Term Memory

The present study investigated age-related differences in retrieval from long-term memory using a semantic fluency task in which participants were asked to write down as many animals as they could remember during a 5-minute retrieval period. We evaluated the relative uniqueness of items and their output position within the retrieval process to further elucidate how younger and older adults access and retrieve semantic knowledge in long-term memory. Although older (n = 96, aged 56-79, M = 62.44, SD = 4.75) and younger adults (n = 98, aged 18-27, M = 23.44, SD = 2.07) scored similarly for retrieval fluency and originality, these abilities tended to decline when we analyzed age as a continuous variable, indicating some preservation in earlier adulthood, and then impairment in older age. Furthermore, participants tended to recall common, more easily accessible items before unique, less accessible items, and this pattern was more prominent in older adults. In sum, results revealed age effects in fluency, originality, and measures of retrieval organization such that older adults generally retrieve more common items and when retrieving items from semantic long-term memory, both younger and healthy older adults generally proceed in an easy to difficult order.
The Relationship Between Service Quality And Customer Satisfaction

service quality is one of the most effective tools to gain customer satisfaction and loyalty. This study aimed to examine the relationship between service quality and customer satisfaction on private telecom sector in India. The study based on primary and secondary data, a total of 310 customers of the private telecom sector companies were surveyed by applying a structured questionnaire. Statistical tools like Cronbach's alpha coefficient and correlation coefficients, frequencies and percentages, descriptive statistics analysis, correlation analysis are employed to assess the relationship between the dependent variable and independent variable. The results revealed that there is a significant relationship between service quality and customer satisfaction. This study contributes invaluable information for both academician and managers for their theoretical and practical purposes.
Tuning Causal Discovery Algorithms

There are numerous algorithms proposed in the literature for learning causal graphical probabilistic models. Each one of them is typically equipped with one or more tuning hyper-parameters. The choice of optimal algorithm and hyper-parameter values is not universal; it depends on the size of the network, the density of the true causal structure, the sample size, as well as the metric of quality of learning a causal structure. Thus, the challenge to a practitioner is how to “tune” these choices, given that the true graph is unknown and the learning task is unsupervised. In the paper, we evaluate two previously proposed methods for tuning, one based on stability of the learned structure under perturbations of the input data and the other based on balancing the in-sample ﬁtting of the model with the model complexity. We propose and comparatively evaluate a new method that treats a causal model as a set of predictive models: one for each node given its Markov Blanket. It then tunes the choices using out-of-sample protocols for supervised methods such as cross-validation. The proposed method performs on par or better than the previous methods for most metrics.
Phosphorylated Rho-kinase (ROCK) as a novel therapeutic target in treatment of breast cancer

3508 Background: Rho-kinase (ROCK) has been identified as one of the effectors of the small GTP-binding protein Rho. ROCK is activated through phosphorylation (p-ROCK) by activated Rho. Accumulating evidence both in vitro and in vivo has demonstrated that Rho/ROCK pathway plays an important role in invasion and migration of cancer cells. However, it remains to be examined whether ROCK activation is linked to the clinicopathological factors and prognosis of patients with breast cancer. Methods: Primary breast cancer tissues were obtained from 221 patients with breast cancer. The distribution and location of ROCK and p-ROCK protein were evaluated with immunohistochemical staining in paraffin sections. The extent of the immunoreactivity was analyzed in terms of the clinicopathological factors and survival of the patients in the 3-years follow-up period after the operation. Results: The enhanced immunoreactivity of p-ROCK (>20% positive area in total high-power field) was frequently observed in patients with .
Pedestrian Walking Direction Classification for Moroccan Road Safety

This paper tackles one of the first causes of death all around the world. In fact, third world countries including Morocco suffers more from road accidents caused by undisciplined human behavior specially pedestrians. To address this issue, our work as part of a road safety project named SAFEROAD, aims to detect pedestrians and classify their walking direction in order to alert the driver of their presence using a new neural network algorithm named Capsule Network. As we work for the Moroccan case, we collected the first Moroccan pedestrian dataset from several Moroccan cities so as to consider the Moroccan pedestrian behavior in the proposed system. The collected dataset was used to train the proposed network giving an accuracy of 78.95% on the validation phase. The proposed approach shown better results compared to convolutional neural network algorithms.