Miracle-dz/UniFAR-FTUs huggingface dataset:
Differential Effects of Internal and External Remoteness on Trade Flows: The Case of Pakistan

Following the decline in international trade costs over time, attention is increasingly drawn to tradeinhibiting effects of relatively high behind-the-border trade costs arising from the dispersion of economic activity and poor transport network, especially in developing countries. This study differentiates the trade-impeding effects of internal remoteness from trade-processing infrastructure from those of external remoteness from export markets. Using a novel dataset that identifies the locations of manufacturing facilities and modes of shipment over time, it finds that the marginal effect of domestic distance to sea ports is almost double that of international distance to export markets. Both distances have heterogeneous effects along trade margins. Domestic distance impedes exports primarily through extensive margins (EM) of firms and product, whereas international distance restricts these mainly through quantity margins, in addition to constricting the EM. Although the trade-impeding effects of both components of distance have reduced over time, the drop has been relatively greater for the international leg. These findings imply that reducing inland transportation costs can boost exports though the channels of 1) entry of more firms into exporting and 2) widening of the export product set.
Genetic divergence studies in wheat germplasm using non-hierarchical euclidean cluster analysis

Four hundred and forty-one wheat germplasm collections including important varieties and exotic and indigenous accessions were evaluated for 15 metric characters using non-hierarchical Euclidean cluster analysis. All the genotypes were grouped into 12 different clusters showing existence of high genetic diversity in the material. The genotypes of heterogeneous origin were grouped in the same cluster indicating non-parallelism between genetic and geographic diversity. The intra-cluster distance was maximum (2.90) in cluster II and minimum (2.10) in cluster V. Cluster IV and X were highly diverse (6.66) from each other. Genotypes of cluster IV were the highest yielders (X = 48.57 g, C.V. 23.80%). Several collections which may serve as good genetic donors for high spikelet fertility, dwarfness, long ear, bold grain, high number of ears and good source for multiple resistance against rusts and powdery mildew were identified.
On Modality Bias in the TVQA Dataset

TVQA is a large scale video question answering (video-QA) dataset based on popular TV shows. The questions were specifically designed to require"both vision and language understanding to answer". In this work, we demonstrate an inherent bias in the dataset towards the textual subtitle modality. We infer said bias both directly and indirectly, notably finding that models trained with subtitles learn, on-average, to suppress video feature contribution. Our results demonstrate that models trained on only the visual information can answer ~45% of the questions, while using only the subtitles achieves ~68%. We find that a bilinear pooling based joint representation of modalities damages model performance by 9% implying a reliance on modality specific information. We also show that TVQA fails to benefit from the RUBi modality bias reduction technique popularised in VQA. By simply improving text processing using BERT embeddings with the simple model first proposed for TVQA, we achieve state-of-the-art results (72.13%) compared to the highly complex STAGE model (70.50%). We recommend a multimodal evaluation framework that can highlight biases in models and isolate visual and textual reliant subsets of data. Using this framework we propose subsets of TVQA that respond exclusively to either or both modalities in order to facilitate multimodal modelling as TVQA originally intended.
DEEP NEURAL NETWORKS FOR ESTIMATION AND INFERENCE1

We study deep neural networks and their use in semiparametric inference. We establish novel nonasymptotic high probability bounds for deep feedforward neural nets. These deliver rates of convergence that are suﬃciently fast (in some cases minimax optimal) to allow us to establish valid second-step inference after ﬁrst-step estimation with deep learning, a result also new to the literature. Our nonasymp-totic high probability bounds, and the subsequent semiparametric inference, treat the current standard architecture: fully connected feedforward neural networks (multi-layer perceptrons), with the now-common rectiﬁed linear unit activation function, unbounded weights, and a depth explicitly diverging with the sample size. We discuss other architectures as well, including ﬁxed-width, very deep networks. We establish the nonasymptotic bounds for these deep nets for a general class of nonparametric regression-type loss functions, which includes as special cases least squares, logistic regression, and other generalized linear models. We then apply our theory to develop semiparametric inference, focusing on causal parameters for concreteness, and demonstrate the eﬀectiveness of deep learning with an empirical application to direct mail marketing.
Environmental factors that influence species diversity of floodplain plant communities in different flooding phases in the Okavango Delta, Botswana

Background and objectives: Species composition and distribution in seasonal floodplain plant communities are influenced by variation in flooding. However, the influence of intra-flooding variation phases on the diversity of seasonalfloodplain plant communities has not been studied in the Okavango Delta. The objective of this study was to investigate environmental factors that influence species composition and distribution of seasonal floodplain communities beforeand after flooding. It was hypothesised that environmental factors that influence the species composition and distribution in seasonal floodplain communities will vary with intra-flooding seasons.Methods: Flooding depth was measured in May (before flooding) and September (flood recession/after flooding) in forty 25 m2 plots. Flooding duration was recorded as the number of weeks in which the plots were inundated. The soil was sampled before and after floods and analysed for pH, extractable P, K, Mg, Ca and Na. Plant identification and estimation of percentage cover were done in the 25 m2 plots in which environmental variables were sampled. The relationshipbetween environmental variables and seasonal floodplain plant community composition and distribution was sought using Non-metric Multi-dimensional Scaling. Paired Student’s t test was used to compare the means of environmentalvariables before and after flooding.Results: Factors that influenced the distribution of species before flooding were Na, K, water depth and flooding duration. After flooding, the factors that influenced species composition and distribution were K, Na, Mg, pH, water depth and flooding duration.Conclusion: These results suggest that during flooding K and Mg are deposited in the floodplains due to lateral water flow. Our results also suggest that any water abstraction from the Okavango River Basin should take into consideration theimportance of flooding duration and depth in sustaining species composition and distribution of seasonal floodplain plant communities so that such developments do not disturb the ecological functioning of the Delta.
RAD: Rapid Automobile Data Analytics Framework for Structured Data

Machine learning models are useful for vehicle performance optimization and characterization. They can be used to forecast future events or conditions, classify events as cautious or concerning, and act as a prognostic tool. Currently, supporting these machine learning models requires analytical computations and analysis of raw data collected from vehicles in the cloud. This incurs a large cost associated with transferring large amounts of data to (and from) the cloud to train and run models. Alternatively, models could be executed on board the vehicle. The compromise is that there are limited resources available on an automotive electronic control unit (ECU) and the architecture is currently decentralized to perform these computations. Therefore, any deployed models would need a model execution environment that uses limited computing resources. In this scenario it is important to also consider the trade-off between resources and performance. In this paper, we develop a unified framework enabling rapid deployment of flexible machine learning models to handle a variety of use-cases in constrained environments called the Rapid Automobile Data Analytics (RAD) framework. This paper focuses primarily on creating models and architectures for sequential and structured data. Multiple architectures and models are investigated and evaluated, and an automated pipeline for deployment of the models is developed.
Relationship between Vertical Facial Pattern and Dental Arch Forms in skeletal Class I Malocclusion

Original Research Article Introduction: The purpose of this study was to investigate the relationship between vertical facial pattern and dental arch forms in class I skeletal malocclusion. Materials and Methods: The study comprised of 60 pretreatment (lateral cephalogram, dental cast and photographs) aged between 11-38 years full permanent dentition without agenesis and/or tooth loss except third molar. The evaluation of the dental arch form was performed using a computer analysis (AutoCad). Results: Assessment of interexaminar reliability analysis was performed using Kappa statistic. Pearson correlation was used to analyze the dental arch form and facial vertical dimensions. Conclusion: As the form of dental arches is associated with the vertical growth patterns, it would be desirable to use individualized arches for each patient.
Genetic Diversity in Cowpea

In order to assess the divergence among 169 cowpea genotypes, mahalanobis D2 statistics was applied. The analysis of variance revealed significant differences among the genotypes for all the traits. The 169 genotypes were grouped into 46 clusters, where clusters (6,8,9) were the largest, containing seven genotypes followed by the clusters 1,2,5,6 and 24 with six genotypes. The inter cluster distance was maximum between cluster 11 and 42 followed by cluster 34 and 42. Based on inter cluster distance and perse performance of genotypes, the entries viz., IC 259084, IC 259071, IC 257420, IC 257422, IC 202803, IC 97829, IC 198333, IC 97787, IC 202824 and IC 202781 were selected, which could be intercrossed to recover good recombinants and desirable segregants. The number of pods per plant contributed maximum divergence (14.75) which was followed by harvest index (14.74%) and days to flower termination (13.72%).
C V ] 1 4 O ct 2 01 9 Fourier Spectrum of Clifford H p Spaces on R n + 1 + for 1 ≤ p ≤ ∞

This article studies the Fourier spectrum characterization of functions in the Clifford algebra-valued Hardy spaces Hp(R + ), 1 ≤ p ≤ ∞. Namely, for f ∈ L(R), Clifford algebra-valued, f is further the non-tangential boundary limit of some function in Hp(R + ), 1 ≤ p ≤ ∞, if and only if f̂ = χ+f̂ , where χ+(ξ) = 1 2 (1 + i ξ |ξ| ), the Fourier transformation and the above relation are suitably interpreted (for some cases in the distribution sense). These results further develop the relevant context of Alan McIntosh. As a particular case of our results, the vector-valued Clifford Hardy space functions are identical with the conjugate harmonic systems in the work of Stein and Weiss. The latter proved the corresponding singular integral version of the vector-valued cases for 1 ≤ p < ∞. We also obtain the generalized conjugate harmonic systems for the whole Clifford algebra-valued Hardy spaces rather than only the vector-valued cases in the Stein-Weiss setting.
A Theory of Economic Disintegration

We study the impact of unilateral economic disintegration, such as Brexit, on national and international policies. We introduce firm mobility and business‐tax policies into a general‐equilibrium trade model and analyze the effects of disintegration on tax policies of asymmetric countries. Whereas the disintegrating country taxes less, business taxes converge in the remaining economic area. We highlight important differences with existing two‐country models. Moreover, we predict a realignment of trade policies with a deeper integration inside the union and lower tariffs worldwide. The leaving country's endogenous integration response with other countries may fully compensate for the disintegration‐induced welfare losses.This article is protected by copyright. All rights reserved
Sketches of Dynamic Complexity

How can the result of a query be updated after changing a database? This is a fundamental task for database management systems which ideally takes previously computed information into account. In dynamic complexity theory, it is studied from a theoretical perspective where updates are specified by rules written in first-order logic. In this article we sketch recent techniques and results from dynamic complexity theory with a focus on the reachability query.
Does employee envy trigger the positive outcomes at workplace? A study of upward social comparison, envy and employee performance

The purpose of this research was to investigate the outcomes of envy in the workplace and the moderating role of perceived organizational support. Data was collected from 270 employees of the telecom industry. The cross-sectional research was conducted, and the data was collected through survey questionnaires from employees hailing from private Telecom companies in Pakistan. Results showed that upward social comparison initiates benign and malicious envy which, in turn, affects employee performance. Benign envy results in enhancing the employee performance whereas malicious envy shows no relationship with employee performance. By paying attention to supporting the employees, malicious envy can enhance employee performance.
Lifted Query Answering in Gaussian Bayesian Networks

Gaussian Bayesian networks are widely used for modeling behaviors of continuous random variables. Lifting exploits symmetries when dealing with large numbers of isomorphic random variables to support more compact representations and more efﬁcient query answering. This paper presents a lifted construction and representation of a joint distribution derived from a Gaussian Bayesian network and a lifted query answering algorithm on the lifted joint distribution. To lift the query answering, needed algebraic operations that work fully in the lifted space are developed. A theoretical complexity analysis and experimental results show that both the lifted joint construction and the lifted query answering signiﬁcantly outperform their grounded counterparts.
Spontaneous Infertility Secondary to Testicular Sarcoidosis: A Case Report

Sarcoidosis is a multisystem disease that can affect any region of the body. Rarely, sarcoid involvement may even involve the male genitourinary tract, including the testicles. Testicular sarcoidosis causes spontaneous and severe effects on male fertility due to obstructive azoospermia. The case presented offers an insight into successful fertility treatment in a patient with obstructive testicular sarcoidosis. The patient and his partner presented to the clinic two years post successful natural conception of their first child with subsequent infertility. Within this period, the male partner was diagnosed with sarcoidosis and was on a treatment plan consisting of methotrexate and glucocorticoids. Complete azoospermia was confirmed via two separate semen analyses six weeks apart. The patient’s testosterone (free and total), thyroid stimulating hormone (TSH), prolactin, follicle stimulating hormone (FSH), and luteinizing hormone (LH) were all within normal limits. With approval of pulmonology, methotrexate was discontinued for three months; however, subsequent semen analysis revealed no improvement. The patient was referred to urology, who confirmed the presence a palpable testicular nodule. Treatment of infertility was eventually achieved via testicular sperm aspiration (TESA) followed by in vitro fertilization (IVF) using intracytoplasmic sperm injection (ICSI). This treatment was successful in achieving one blastocyst and one morula, which were replaced via fresh transfer, resulting in a successful term singleton pregnancy. The possibility of obstructive azoospermia should be considered in males diagnosed with sarcoidosis who are seeking to preserve their reproductive potential.
Natural connections : perspectives in community-based conservation

Both realism and justice demand that efforts to conserve biological diversity address human needs as well. The most promising hope of accomplishing such a goal lies in locally based conservation efforts -- an approach that seeks ways to make local communities the beneficiaries and custodians of conservation efforts.Natural Connections focuses on rural societies and the conservation of biodiversity in rural areas. It represents the first systematic analysis of locally based efforts, and includes a comprehensive examination of cases from around the world where the community-based approach is used. The book provides: an overview of community-based conservation in the context of the debate over sustainable development, poverty, and environmental decline case studies from the developed and developing worlds -- Indonesia, Peru, Australia, Zimbabwe, Costa Rica, the United Kingdom -- that present detailed examples of the locally based approach to conservation a review of the principal issues arising from community-based programs an agenda for future action
Artificial Intelligence Buzzword Explained: Scientific workflows

The reproducibility of scientific experiments is crucial for corroborating, consolidating and reusing new scientific discoveries. However, the constant pressure for publishing results [1] has removed reproducibility from the agenda of many researchers: in a recent survey published in Nature (with more than 1500 scientists) over 70% of the participants recognize to have failed to reproduce the work from another colleague at some point in time [2]. Analyses from psychology and cancer biology show reproducibility rates below 40 % and 10% respectively [3] [4]. As a consequence, retractions of publications have occurred in the last years in several disciplines [5] [6], and the general public is now skeptical about scientific studies on topics like pesticides, depression drugs or flu pandemics [7]. Reproducing the results of a previous study can be a challenge, as even when the original datasets and end results are available, a significant investment in time may be required [8]. Fortunately, the community has started to pay attention to initiatives for preserving the data and software used in scientific publications (e.g., Zenodo 1 , Github 2 , etc.). In computational sciences, scientific workflows were proposed in the last decade as a means to address reproducibility. A scientific workflow defines the set of computational tasks and dependencies needed to carry out in silico experiments [9]. Typically, scientific workflows are represented as directed graphs, where the nodes represent computational tasks and the edges represent their dependencies. Figure 1 shows an example with two workflows, one for text analytics on the left and another one for neuro-image analysis on the right. Scientific workflows have been used in many domains, including astronomy
An analysis of prime determinants and constraints of Bangladesh’s export market: Stochastic frontier gravity model approach

This paper adopts the stochastic frontier gravity model approach, using panel data to investigate the prime determinants and constraints of Bangladesh's export industry, and its potential to improve i ts t rading posi t ion in relat ion to i ts top 40 trading partners. The study finds that, for Bangladesh, gross domestic product (GDP), population, distance, average tariff, trade agreements and exchange rates are the prime determinants of export volume. While GDP, population, trade agreements and exchangerate depreciation positively affect exports, the distance between Bangladesh and its partner countries and tariff levels negatively impact trade. The study also finds that socio-political-institutional, ‘behind-the-border’ constraints, such as customs procedures, port inefficiencies and corruption, are restricting trade. The results show that there are huge variations in export levels, even among countries within the same trading blocs, suggesting that a high level of untapped export potential can be realised by removing the behind-the-border constraints and by integrating more efficiently with the international market.
Superpixel Masking and Inpainting for Self-Supervised Anomaly Detection

Anomaly detection aims at identifying abnormal samples from the normal ones. Existing methods are usually supervised or detect anomalies at the instance level without localization. In this work, we propose an unsupervised method called Superpixel Masking And Inpainting (SMAI) to identify and locate anomalies in images. Speciﬁcally, superpixel segmentation is ﬁrst performed on the images. Then an inpainting module is trained to learn the spatial and texture information of the normal samples through random superpixel masking and restoration. Therefore, the model can reconstruct the superpixel mask with normal content. At the inference stage, we mask the image using superpixels and restore them one by one. By comparing the mask areas of the original image and its reconstruction, we can identify and locate the abnormal regions. We conducted a comprehensive evaluation of SMAI on the latest MVTec anomaly detection dataset, and it shows that SMAI plays favorably against state-of-the-art methods.
Site fidelity, homing and spawning migrations of flounder Platichthys flesus in the Tamar estuary, South West England

Brand-marked flounder Platichthys flesus (L.) were used to study migrations, site fidelity and homing ability of individuals in the Tamar estuary, SW England, between 1976 and 1980. A total of 1308 recaptures were made, of 7401 flounder marked at 13 stations along a 29 km length of the estuary and 2 stations in Plymouth Sound. A further 1667 fish were marked on the spawning grounds in 1976, 57 being recaptured. Recaptured fish were released again, with individuals being recap- tured on up to 6 occasions. In all but 118 cases, the recaptures within the estuary or Plymouth Sound were from the original capture sites, despite the displacement of 681 fish, after marking, to a variety of locations. Most flounder in the middle estuary did not move >200 m along the estuary until they left to spawn. Flounder in the upper estuary also showed high site fidelity, but were temporarily dis- placed by adverse conditions such as river spates. Ripe, estuary-marked flounder were recaptured at sea from 10 to 35 km west of Plymouth in water depths of 35 to 55 m. Most individuals returned to their original estuarine range after spawning. Twelve percent failed to return to the Tamar post- spawning, all migrating eastwards. A total of 200 Tamar fish were released 200 km eastwards along the coast. Many of these migrated towards Plymouth, 2 reaching the estuary, although some returned to the release site post-spawning. The results are applicable to the management of flounder stocks and of estuaries, emphasising the value of retaining intertidal mud flats in estuary development plans.