Miracle-dz/UniFAR-FTUs huggingface dataset:
Generating Natural-Language Navigation Instructions from Panoramic Images

The goal of the Vision-and-Language Navigation task (VLN) [1] is to train an agent to move through a lifelike environment using visual cues and a natural language instruction. The agent is required to understand the provided instruction and decide which action to take in order to get as close as possible to the target location. An example instruction can be found in Figure 1. The agent must be able to follow the commanded instruction even in previously unexplored environments. Following navigation instructions is rather trivial for humans but hard for an agent [1, 4]. Humans tend to subjectively select reference points in the environment to describe a path. Therefore, we end up with a diverse set of instructions from the same sequence of images in the path. This can explain why it is difficult for an artificial intelligent agent to replicate humans in this task. Previous approaches to this task [4] include a speaker-follower model. The speaker part of the model is a method for generating navigation instructions from panoramic images and actions in a path. The speaker model alone is useful because it can be used to interesting and important real-life applications such as autonomous driving navigation and virtual-reality navigation. In this work, we focus on the navigation instruction generation problem. We extend the speaker model by taking into account the human behavior of selecting diverse reference points. In addition, we consider the fact that each view angle in a panoramic image corresponds to a time step on the simulator, representing actions Left, Right, Up, Down, Forward, and Stop. Instruction 1: Turn left and to towards the kitchen, turn left at the kitchen and go until you are right before the yellow couch by the picture on the right.
Assumptions in Economics*

Any scientific discipline, any theory, formal or informal, rests on assumptions. These assumptions matter, and in the case of social sciences, influence our vision of society and our policy recommendations. This essay reviews and comments on assumptions most commonly made by economists -methodological individualism vs. socially determined preferences, consequentialism, utility comparisonsand discusses their attitudes toward the market and ethical choices.
Data editing for machine learning prediction models

1. Imputation is the common practice of substituting in realistic values when there is missing data. It is both useful to have complete data in order to create nice tables but can also be used to improve estimations by correcting for various missing data patterns. It is a technique used in official statistics for completing both survey data and administrative data in many different contexts. The methods used for imputing are now expanding beyond the traditional statistical approaches into the area of statistical learning involving machine-learning algorithms. 2. One concern is the quality of the training data, for which the imputation model or algorithm is learnt. If this contains many erroneous values, we must expect many error-prone values to also be predicted. Even if the imputation method is highly predictive, if we are basing it on data with a high error rate, we are not going to achieve high accuracy. This is not easily solved by simply improving the imputation method. 3. Alternately, the training data may contain high-quality data but be skewed in a way that means it does not represent the group to impute. In this case, there are certain methodological approaches that can be taken to improve the predictive outcome. For example, if using hot-deck imputation, stratifying using variables related to the outcome and missing data pattern can improve the estimates compared to simple hot-deck imputation. 4. In this study, we look at outlier detection and imputation of a key variable for Statistics Norway’s employment statistics: contractual working hours in terms of the contractual full-time equivalent percentage (FTE). This is the number of contractual hours as specified in their working contract divided by the number of hours in a full-time position, as a percentage. This variable provides the basis for estimating the number of fulland part-time workers in Norway. It is also used in calculating earnings statistics, which are published in terms of full-time equivalent wages. We describe the processes used to identify outliers in the data, comparing the method used in 2018 and changes in 2019. We look at how this change in the identification of outliers has affected the imputation groups characteristics and the resulting predictions for imputation. Finally, we investigate an alternative approach to learning the prediction model by synthetically balancing the training dataset to represent the imputation population. 5. Numbers in this paper may differ from those published by Statistics Norway. This is due to some differences in the underlying available data at the time of this study and some simplifications of the editing processes for analysis reasons. Statistics in this study should therefore not be used for official statistics use.
Effect of the factor to transpire unintended pregnancy in Bangladesh: A cross-sectional study

----------------------------------------************************---------------------------------Abstract: Unintended pregnancy is a very important issue for every country in the world. Which factors mainly affect to occur unintended pregnancy, it does not study. The aim of this study to find out factors affecting variables to occur unintended pregnancy and also find out to socio-demographic characteristics variables, how much effect on unintended pregnancy variable. I am also concentrating on the association of the unintended pregnancy variable with some other related variables. The result of socio-demographic characteristics variables such as current contraception method, unmet need for contraception, etc are significantly related to unintended pregnancy but sexual violence is insignificantly related to the selected independent variable. The study examines how much impact on the independent variable to the dependent variable. Unmet need for contraception has a significant effect on unintended pregnancy, also the husband's education level has a significant effect on unintended pregnancy but the husband's education level has an insignificant effect on the dependent variable. Unmet need for contraception and unintended pregnancy are significantly positively related. Frequency distribution, Percentage of the variable, Factor influencing model (Multinomial logistic regression model) was run to useable data. The findings of the study could provide clear guidelines for the next researcher.
Portuguese Speech Synthesis for ALS Patients

Amyotrophic Lateral Sclerosis (ALS) is a group of rare neurological diseases that mainly affects the nerve cells responsible for voluntary muscle movement. The disease is progressive, meaning that the symptoms get worse over time, leaving the patient in a highly incapacitating state. Due to the progressive muscle atrophy that affects patients, dependence on caregivers grows, and the role of assistive technologies comes into play. Most patients experience a dramatic loss in speech intelligibility caused by an increasing muscle weakness, and hence both written and spoken communication are distressed. By developing a way for patients to preserve their voice in a speech synthesizer, we are helping them retaining a vital part of their identity, instead of using off-the-shelf synthesizers with generic voices. During the course of this work we will develop a Portuguese speech synthesizer that is able to perform speaker adaptation on small voice banks, which is most useful in the case of ALS, where the task of recording extensive voice banks is both physically and mentally exhausting.
Wage Imputation With Deep Learning in the French Labor Force Survey

1. The French Labor Force Survey (LFS) surveys about 100000 in about 60000 dwellings each quarter. The LFS is a rotating panel: we survey dwellings for six consecutive quarters, and one sixth of the sample is renewed each quarter. Like other national LFS, it is the source for the ILO unemployment rate, and for numerous other publications on employment and working conditions. Since 1982 in the French LFS, employees are asked for their monthly wage, first in income bands up until 1989, then for the exact amount since 1990. Self-employed still answer with (annual) income bands categories. We collect wage and income for each individual on the first interview (usually the first quarter a dwelling is in the sample) and on the last dwelling interview.
Design of a Reinforcement Learning PID controller

This paper addresses a design problem of a Proportional-Integral-Derivative (PID) controller with new adaptive updating rule based on Reinforcement Learning (RL) approach for nonlinear systems. A new design scheme that RL can be used to complement the conventional control technology PID is presented. In this study, a single Radial Basis Function (RBF) network is introduced to calculate the control policy function of Actor and the value function of Critic simultaneously. Regarding to the PID controller structure, the inputs of RBF network are system error, the difference of output as well as the second order difference of output, and they are defined as system states. The Temporal Difference (TD) error in this study is newly defined and involves the error criterion which is defined by the difference between one-step ahead prediction and the reference value. The gradient descent method is adopted based on TD error performance index, then the updating rules can be obtained. Therefore, the network weights and the kernel function can be calculated in an adaptive manner. Finally, the numerical simulations are conducted in nonlinear systems to illustrate the efficiency and robustness of the proposed scheme.
ADA-X: A System for Domain-Independent Feature-Based Product Review Aggregation

When looking to buy a product, consumers often look for written reviews to gain insight into its various features. However, many reviews are cluttered with irrelevant information, which makes reading through them an arduous task. Some systems have been proposed to alleviate this task in specific review domains such as film reviews, but a general solution remains to be implemented. We present ADA-X, a general-domain review aggregation system that is able to provide feature-based explanations for any product’s reviews via a conversational interface. The generality of ADA-X is enabled by a novel domain-independent ontology extraction method using the state-of-the-art language model BERT, which we have shown to obtain product ontologies with an F1-score multiple times higher than the state-of-the-art general knowledge networks of ConceptNet and WordNet. ADA-X has been demonstrated to be capable of providing conversational feature-based review explanations for any Amazon product, and its methodology could be extended to any review domain with sufficient amounts of data. User evaluation has demonstrated that the explanations provided by ADA-X improve the user experience of product review inspection.
Di ff erent modes associated with the neutron di ff usion equation and their computation

The λ, γ and α-modes can be defined in neutron diffusion equation to study the characteristics of nuclear reactor. A high order finite element method is used for the discretization of the differential eigenvalue problems. The aim of this work is to study the differences between the modes and analyze two methods to compute the resulting algebraic eigenvalue problem after the spatial discretization. Krylov-Schur method is used to solve these kind of problems. As an alternative to speed-up the calculations for γ and α-modes, a strategy based on the modified block Newton method is proposed. To present numerical results and compare the eigenvalue solvers, a homogeneous reactor and the NEACRP reactor are studied.
Relationship between Synchronization Rates and Parameter Mismatches in Coupled Chaotic Circuits Using Memristors

In our previous studies, the relationship between synchronization rates and small parameter mismatches on an asymmetrical coupled chaotic systems has been investigated. As a result of investigating these systems, interesting phenomenon can be observed. We consider that the phenomenon can be observed in the case of any kinds of chaotic oscillators. In this study, a memristor based chaotic circuit are applied to our proposed system. By this investigation, our hypothesis for the phenomenon observed in our system is reinforced.
New Formulation of Clethodim/Adjuvant at Control of Grass Weeds for Soybean Crops

The use of ACCase-inhibiting herbicides without the correct addition of an adjuvant is a major cause of inefficient poaceous weed control. As such, this study aimed to assess the efficiency of a new clethodim/adjuvant formulated mixture in postemergence weed control for soybean crops. Two field experiments were conducted in the 2015/16 and 2016/17 growing seasons. A randomized block design, consisting of ten treatments with four repetitions, was used. The treatments and doses were: clethodim (108 g a.i. ha -1 ) + Lanzar® (0.5%), clethodim (108 g a.i. ha -1 ) + Nimbus® (0.5%), clethodim/adjuvant formulation at doses of (84 g a.i. ha -1 ), (96 g a.i. ha -1 ), (108 g a.i. ha -1 ), (120 g a.i. ha -1 ), (132 g a.i. ha -1 ), and (144 g a.i. ha -1 ), and a control with and without weeding. The formulated clethodim/adjuvant mixture showed high control at 7 days after application (DAA) in the 2015/16 growing season. At 28 DAA, formulation doses of 108 g a.i. ha-1 and higher exhibited superior weed control and the highest crop yields. Therefore, the use of correct adjuvant or formulated mixture is essential to increase the efficiency of clethodim herbicide.
Distributed subgraph counting

In this paper, we study local subgraph counting, which is to count the occurrences of a user-given pattern graph p around every node v in a data graph G, when v matches to a given orbit o in p, where the orbit serves as a center to count p. In general, the orbit can be a node, an edge, or a set of nodes in p. Local subgraph counting has played an important role in characterizing high-order local structures that exhibit in a large graph, and has been widely used in denser and relevant communities mining, graphlet degree distribution, discriminative features selection for link prediction, relational classification and recommendation. In the literature, almost all the existing works support a k-node pattern graph, for k ≤ 5, with either 1 node orbit or 1 edge orbit. Their approaches are difficult to support larger k due to the fact that subgraph counting is to count by subgraph isomorphism. In this work, we develop a new general approach to count any k pattern graphs with any orbits selected. The key idea behind is that we do local subgraph counting by homomorphism counting, which can be solved by relational algebra using joins, group-by and aggregation. By homomorphism counting, we do local subgraph counting by eliminating counts for those that are not subgraph isomorphism matchings from the total count for any possible matchings. We have developed a distributed system named DISC on Spark. Our extensive experiments validate the efficiency of our approach by testing 114 local subgraph counting queries used in the existing work over real graphs, where no existing work can support all.
Farmland size, chemical fertilizers, and irrigation management effects on maize and wheat yield in Mexico

ABSTRACT Farmland size is a key factor in debates over agricultural land use, food security, agrochemical pollution, and the future of smallholder systems. This paper examines relationships between farmland size, chemical fertilizers and irrigation management, and maize and wheat yield in Mexico. We used agricultural census data to estimate the mean farmland areas and crop yields of 5.5 million farms and nine million agricultural plots in 2,455 Mexican municipalities. We also derived indices of socio-environmental and management factors to examine relationships with yield. Using multiple regression models, we found that although mean farmland area positively relates to maize and wheat yield, the relationships depend critically on the management contexts of chemical fertilizers and irrigation, which vary widely across farm size gradients. Smallholder yield gaps were associated with deficits in irrigation, rather than chemical inputs. Findings highlight the growing need for expanded irrigation access and/or water management assistance for smaller farms.
Understanding compassion fatigue, optimism and emotional distress among Israeli school counsellors

ABSTRACT Compassion fatigue is common among counselors who are exposed to the ongoing trauma of students and families at times of distress and crisis. The aim of this study was to examine compassion fatigue, perceived stress, optimism and emotional distress among school counselors among 139 Israeli school counselors. The results indicated that compassion fatigue correlates positively both with perceived stress and with emotional distress and negatively with optimism. Levels of compassion fatigue were higher among Israeli school counselors working in elementary school than among those working in high school. Perceived stress mediated the association between compassion fatigue and emotional distress. The findings indicate that the personal resources available to helpers as well as vulnerability factors may affect levels of compassion fatigue and emotional distress.
MuSe

We propose to demonstrate MuSe, a system for Database repairs where constraints are expressed as Declarative Rules and can be interpreted in different ways by using four different semantics. Our framework may capture common, cross-relation, repair semantics such as that of SQL deletion triggers, causal rules, and denial constraints. Our demonstration will show the usefulness of the system in easing specification of database repair policies, for different use cases.
Verifiability of genus-level classification under quantification and parsimony theories: a case study of follicucullid radiolarians

Abstract. The classical taxonomy of fossil invertebrates is based on subjective judgments of morphology, which can cause confusion, because there are no codified standards for the classification of genera. Here, we explore the validity of the genus taxonomy of 75 species and morphospecies of the Follicucullidae, a late Paleozoic family of radiolarians, using a new method, Hayashi's quantification theory II (HQT-II), a general multivariate statistical method for categorical datasets relevant to discriminant analysis. We identify a scheme of 10 genera rather than the currently accepted 3 genera (Follicucullus, Ishigaconus, and Parafollicucullus). As HQT-II cannot incorporate stratigraphic data, a phylogenetic tree of Follicucullidae was reconstructed for 38 species using maximum parsimony. Six lineages emerged, roughly in concordance with the results of HQT-II. Combined with parsimony ancestral state reconstruction, the ancestral group of this family is Haplodiacanthus. Five other groups were discriminated, the Parafollicucullus, Curvalbaillella, Pseudoalbaillella, Longtanella, and Follicucullus–Cariver lineages. The morphological evolution of these lineages comprises a minimum essential list of eight states of four traits. HQT-II is a novel discriminant analytical multivariate method that may be of value in other taxonomic problems of paleobiology.
Live, dead, and fossil mollusks in Florida freshwater springs and spring-fed rivers: Taphonomic pathways and the formation of multisourced, time-averaged death assemblages

Abstract. Taphonomic processes are informative about the magnitude and timing of paleoecological changes but remain poorly understood with respect to freshwater invertebrates in spring-fed rivers and streams. We compared taphonomic alteration among freshwater gastropods in live, dead (surficial shell accumulations), and fossil (late Pleistocene–early Holocene in situ sediments) assemblages from two Florida spring-fed systems, the Wakulla and Silver/Ocklawaha Rivers. We assessed taphonomy of two gastropod species: the native Elimia floridensis (n = 2504) and introduced Melanoides tuberculata (n = 168). We quantified seven taphonomic attributes (aperture condition, color, fragmentation, abrasion, juvenile spire condition, dissolution, and exterior luster) and combined those attributes into a total taphonomic score (TT). Fossil E. floridensis specimens exhibited the greatest degradation (highest TT scores), whereas live specimens of both species were least degraded. Specimens of E. floridensis from death assemblages were less altered than fossil specimens of the same species. Within death assemblages, specimens of M. tuberculata were significantly less altered than specimens of E. floridensis, but highly degraded specimens dominated in both species. Radiocarbon dates on fossils clustered between 9792 and 7087 cal BP, whereas death assemblage ages ranged from 10,692 to 1173 cal BP. Possible explanations for the observed taphonomic patterns include: (1) rapid taphonomic shell alteration, (2) prolonged near-surface exposure to moderate alteration rates, and/or (3) introduction of reworked fossil shells into surficial assemblages. Combined radiocarbon dates and taphonomic analyses suggest that all these processes may have played a role in death assemblage formation. In these fluvial settings, shell accumulations develop as a complex mixture of specimens derived from multiple sources and characterized by multimillennial time-averaging. These findings suggest that, when available, fossil assemblages may be more appropriate than death assemblages for assessing preindustrial faunal associations and recent anthropogenic changes in freshwater ecosystems.
The relationships between pelvic range of motion, step width and performance during an athletic sprint start

ABSTRACT The aims of this study were (a) to describe the kinematics underlying the phenomenon of the knee of the swing leg passing medially in front of the athlete during the single push (SP) phase of the block sprint start, and (b) to determine the relationships between block phase pelvis range of motion (RoM), 1st step width and block phase performance. Three-dimensional kinematic data (250 Hz) were collected from eleven competitive sprinters (100 m PB: 11.17 ± 0.41) performing maximal effort block starts. The joint angles of the rear hip with respect to the pelvis and the pelvis segment angles with respect to the laboratory coordinate system were calculated during the block start phase to the end of the 1st stance. A combination of pelvis list and rotation (not hip adduction) was coupled with the thigh of the swing leg moving medially during the SP phase. A very high positive correlation was found between pelvic list RoM and 1st step width (r = 0.799, p = 0.003). No other significant correlations were found. Attempting to reduce pelvic RoM or changing frontal and transverse plane hip joint angles to minimise medial thigh motion is unlikely to lead to an improvement to performance.
New Results on Synchronization of Fractional-Order Memristor-Based Neural Networks via State Feedback Control

This paper addresses the synchronization issue for the drive-response fractional-order memristor‐based neural networks (FOMNNs) via state feedback control. To achieve the synchronization for considered drive-response FOMNNs, two feedback controllers are introduced. Then, by adopting nonsmooth analysis, fractional Lyapunov’s direct method, Young inequality, and fractional-order differential inclusions, several algebraic sufficient criteria are obtained for guaranteeing the synchronization of the drive-response FOMNNs. Lastly, for illustrating the effectiveness of the obtained theoretical results, an example is given.