Miracle-dz/UniFAR-FTUs huggingface dataset:
Current state of construction enterprise information systems: survey research

Purpose – The paper's purpose is to describe and examine the level of utilisation of construction enterprise information systems (CEIS) and to identify critical success factors and benefits from their implementation.Design/methodology/approach – A survey was conducted to quantify the current situation of CEIS. The population consisted of stakeholders with reliable working knowledge of their firms' information systems. Statistical tests were conducted to draw conclusions from the data.Findings – A total of 48 per cent of the firms use enterprise resource planning packages, but only 4 per cent of these firms chose to implement the project management modules that are commercially available. Only 16 per cent of the respondents were satisfied with their current level of integration due to CEIS. There was no evidence to suggest a tendency for the integration level due to CEIS to increase together with the business geographical dispersion.Research limitations/implications – The rate of response to the survey was.
Geological interpretation of offshore Central Sumatra basin using topex satellite gravity data

Topex is a geodetic satellite to map earth surface topography with very high precision. Two types of data can be obtained from Topex satellite, namely topographic and free-air gravity field data. Then, it is processed to produce Bouguer anomaly which will be used to interpret the subsurface geology of a specific study area. The purpose of this study was to delineate sedimentary basin and basement configurations. The methods used in this research are spectral analysis, band-pass filter and 2D forward modeling. The spectral analysis results show the average thickness of the sedimentary rocks is 2.1 km. Sub-basin patterns based on the band-pass filter are 7 sedimentary sub-basins and the structural patterns found in this area comprise basement height, graben and fault. The 2D modeling results show that the bedrock in the eastern part of the Central Sumatra basin is granitic with a mass density value of 2.67 gr/cc and the layer above the bedrock is interpreted as a sedimentary rock with a mass density value of 2.35 gr/cc. Analysis of the gravity data shows significant results as initial information to delineate sedimentary sub-basin and regional structure to enhance information to the next stage of hydrocarbon exploration.
Statistics for Environmental Engineers

Statistics for Environmental Engineers covers a wide range of subject areas, some of which are not typically found in textbooks on statistics. The book contains 54 chapters, which are typically 6 to 10 pages in length. The intention was to make each chapter independent of the others and able to stand alone. Books on statistics for non-statisticians can be terse and still cover the necessary material well—an example is Halstead (1966), the text used for the sophomore-level statistics class I took in 1970. However, the result in the present instance is chapters that are unnecessarily limited in scope, so that a complete discussion of some topics, such as prediction of upper confidence limits for a data set based on a limited set of samples, often takes several chapters. The reader would be better served if the chapters were longer and of greater scope. The intended audience for the book is `environmental engineers' in the sense used by civil engineers—that is, water and wastewater treatment engineers. Hence, most of the examples and end-of-chapter exercises concern problems and data types typical of situations encountered in water and wastewater treatment rather than those encountered in environmental engineering in the more generic …
Improving Self-supervised Learning with Automated Unsupervised Outlier Arbitration

Our work reveals a structured shortcoming of the existing mainstream self-supervised learning methods. Whereas self-supervised learning frameworks usually take the prevailing perfect instance level invariance hypothesis for granted, we carefully investigate the pitfalls behind. Particularly, we argue that the existing augmentation pipeline for generating multiple positive views naturally introduces out-of-distribution (OOD) samples that undermine the learning of the downstream tasks. Generating diverse positive augmentations on the input does not always pay off in benefiting downstream tasks. To overcome this inherent deficiency, we introduce a lightweight latent variable model UOTA, targeting the view sampling issue for self-supervised learning. UOTA adaptively searches for the most important sampling region to produce views, and provides viable choice for outlier-robust self-supervised learning approaches. Our method directly generalizes to many mainstream self-supervised learning approaches, regardless of the loss's nature contrastive or not. We empirically show UOTA's advantage over the state-of-the-art self-supervised paradigms with evident margin, which well justifies the existence of the OOD sample issue embedded in the existing approaches. Especially, we theoretically prove that the merits of the proposal boil down to guaranteed estimator variance and bias reduction. Code is available: at https://github.com/ssl-codelab/uota.
See More for Scene: Pairwise Consistency Learning for Scene Classification

Scene classiﬁcation is a valuable classiﬁcation subtask and has its own characteristics which still needs more in-depth studies. Basically, scene characteristics are distributed over the whole image, which cause the need of “seeing” comprehensive and informative regions. Previous works mainly focus on region discovery and aggregation, while rarely involves the inherent properties of CNN along with its potential ability to satisfy the requirements of scene classiﬁcation. In this paper, we propose to understand scene images and the scene classiﬁcation CNN models in terms of the focus area . From this new perspective, we ﬁnd that large focus area is preferred in scene classiﬁcation CNN models as a consequence of learning scene characteristics. Meanwhile, the analysis about existing training schemes helps us to understand the effects of focus area, and also raises the question about optimal training method for scene classiﬁcation. Pursuing the better usage of scene characteristics, we propose a new learning scheme with a tailored loss in the goal of activating larger focus area on scene images. Since the supervision of the target regions to be enlarged is usually lacked, our alternative learning scheme is to erase already activated area, and allow the CNN models to activate more area during training. The proposed scheme is implemented by keeping the pairwise consistency between the output of the erased image and its original one. In partic-ular, a tailored loss is proposed to keep such pairwise consistency by leveraging category-relevance information. Experiments on Places365 show the signiﬁcant improvements of our method with various CNNs. Our method shows an inferior result on the object-centric dataset, ImageNet, which experimentally indicates that it captures the unique characteristics of scenes.
Bone Resorption Evaluation According to Measurements’ Panoramic Radiographs: A Tunisian Cross-Sectional Study

Panoramic radiographs are the first and most efficient method, used to examine and evaluate the heights of residual alveolar ridges of edentulous patients. After tooth extraction, wound healing of the extraction socket is associated with modeling processes leading to dimensional alterations of the residual ridge. Besides, alterations in the size and shape of the jawbones have been observed to occur throughout adult life and it continues further. Most of the bone loss occurs in the early stage of the atrophic process. The rate and the amount of bone loss may be influenced by various factors such as gender, hormones, metabolism, and parafunction. This study aimed to determine and compare differences in the vertical measurements of jawbones in both edentulous and dentate subjects. The study sample included the diagnostic panoramic radiographs of 53 randomly selected edentulous and dentate patients without systemic diseases affecting bone. -The radiographic selection criteria included the absence of obvious facial asymmetry, clearly visible anatomic structure, neither surgical nor fracture history. -The sample was divided into 3 groups: Groupe1: 29 edentulous patients Groupe2: 14 edentulous upper maxilla patients Groupe 3: 10 mandibular edentulous patients The height of the residual bone was measured at 18 predetermined sites. Results: The differences between elderly men and women in percentages of reductions in heights of the maxilla were not significant. The reduction of the anterior ridge height was greater in the maxilla than in the mandible for both sexes. Moreover, we found a significant correlation between age and bone height in both genders. Conclusion: The outcomes in the present study would contribute to better understanding of RRR in dentate and edentulous subjects.
Pruning Pretrained Encoders with a Multitask Objective

The sizes of pretrained language models make them challenging and expensive to use when there are multiple desired downstream tasks. In this work, we adopt recent strategies for model pruning during finetuning to explore the question of whether it is possible to prune a single encoder so that it can be used for multiple tasks. We allocate a fixed parameter budget and compare pruning a single model with a multitask objective against the best ensemble of single-task models. We find that under two pruning strategies (element-wise and rank pruning), the approach with the multitask objective outperforms training models separately when averaged across all tasks, and it is competitive on each individual one. Additional analysis finds that using a multitask objective during pruning can also be an effective method for reducing model sizes for low-resource tasks.
Confident Anchor-Induced Multi-Source Free Domain Adaptation

Unsupervised domain adaptation has attracted appealing academic attentions by transferring knowledge from labeled source domain to unlabeled target domain. However, most existing methods assume the source data are drawn from a single domain, which cannot be successfully applied to explore complementarily trans-ferable knowledge from multiple source domains with large distribution discrepancies. Moreover, they require access to source data during training, which are inefﬁcient and unpractical due to privacy preservation and memory storage. To address these challenges, we develop a novel C onﬁdent-Anchor-induced multi-source-free D omain Adaptation (CAiDA) model, which is a pioneer exploration of knowledge adaptation from multiple source domains to the unlabeled target domain without any source data, but with only pre-trained source models . Specifically, a source-speciﬁc transferable perception module is proposed to automatically quantify the contributions of the complementary knowledge transferred from multi-source domains to the target domain. To generate pseudo labels for the target domain without access to the source data, we develop a conﬁdent-anchor-induced pseudo label generator by constructing a conﬁdent anchor group and assigning each unconﬁdent target sample with a semantic-nearest conﬁdent anchor. Furthermore, a class-relationship-aware consistency loss is proposed to preserve consistent inter-class relationships by aligning soft confusion matrices across domains. Theoretical analysis answers why multi-source domains are better than a single source domain, and establishes a novel learning bound to show the effectiveness of exploiting multi-source domains. Experiments on several representative datasets illustrate the superiority of our proposed CAiDA model. The code is available at https://github.com/Learning-group123/CAiDA .
An analysis of Ermakov-Zolotukhin quadrature using kernels

We study a quadrature, proposed by Ermakov and Zolotukhin in the sixties, through the lens of kernel methods. The nodes of this quadrature rule follow the distribution of a determinantal point process, while the weights are defined through a linear system, similarly to the optimal kernel quadrature. In this work, we show how these two classes of quadrature are related, and we prove a tractable formula of the expected value of the squared worst-case integration error on the unit ball of an RKHS of the former quadrature. In particular, this formula involves the eigenvalues of the corresponding kernel and leads to improving on the existing theoretical guarantees of the optimal kernel quadrature with determinantal point processes.
The argument structure of the bă construction in Mandarin Chinese: Decontextualized and contextualized perspectives

ABSTRACT The properties of the bă construction and the function of the word bă in Mandarin Chinese have long been controversial issues. This paper elaborates the argument structure of the Mandarin bă construction from decontextualized and contextualized perspectives. In decontextualized analysis, the paper argues that the previous treatments of the word bă in the bă construction as an absolutive/accusative/ergative/oblique case marker are not fully satisfactory as they face different problems. It is argued that the bă construction can be treated as an ergative–absolutive construction, where the word bă is not a case marker, but rather a functional word serving as a relator, which helps to distinguish two structural positions, the pre-bă position and the post-bă position, respectively marking an ergative A (Agent) argument and an absolutive P (Patient) argument. The two grammatical roles A and P may subsume various semantic roles, and hence a semantic-role hierarchy for A and P or for ergative and absolutive case in the bă construction can be established. In contextualized analysis, it is found that there exist some constraints on the use of the bă construction in discourse, which appear to be the common features that the bă construction shares with ergative–absolutive constructions in ergative languages.
Cooperation inter-communale et emploi municipal en France

While in many countries municipalities are major employers, studies of the determinants of their labor demand are surprisingly scarce. Since municipalities in inter-municipal cooperation (IMC) bodies lose some of their responsibilities, IMC employment increases but the nature and the size of the municipal reaction are a priori unknown. We build an original balanced panel dataset of 8,362 municipalities of more than 1,000 inhabitants in France over the 2002-2008 period. In order to identify the causal effect of wages and IMC employment, we construct instruments inspired from the industrial organization methodology. We take advantage of the geographical partitions of the French employment zones and IMC bodies to delimit a neighborhood on which we calculate an average wage and average IMC employment.We first show that wages, grants, median income and tax capacity explain the labor demand, wages being by far the main driving force. Second, we evidence a positive impact of the IMC employment on municipal employment (direct IMC effect). Third,we find that IMC leads mayors to increase municipal employment when unemployment is higher (indirect IMC effect). Finally, controlling for the magnitude of the IMC employment level, it turns out that the indirect IMC effect is greater for municipalities nested in large employment cooperation bodies than in small ones.
Barriers to Global Capital Allocation-20pt

Observed patterns of international investment are difficult to reconcile with frictionless capital markets. In this paper, we provide a quantitative theory of international capital allocation: a multicountry dynamic general equilibrium model with rationally-inattentive investors, where cross-border investment is subject to both information and policy frictions. These frictions result in a persistent misallocation of capital across countries. We estimate model parameters using nationality-based, bilateral investment data, and measures of geographic, linguistic and cultural distance, which capture information frictions. Our unified theoretical-empirical framework can account for several stylized facts: the gravity structure of investment flows, home bias, persistent global imbalances and capital return differentials across countries, as well as the paucity of net flows from developed to emerging economies. Finally, we perform counterfactual exercises: we find that information and policy barriers to international investment greatly amplify the capital gap between rich and poor countries, and result in a large reduction in world output. JEL Codes: E22, E44, F2, F3, F4, G15, O4
The effect of underfill epoxy on warpage in flip-chip assemblies

The thermally-induced warpage of both a real flip-chip thermosonically bonded assembly and a simulated tri-layered assembly was investigated. It revealed the warpage of the assemblies was dominated by the forces applied by the underfill epoxy rather than the solder joints. The roles the underfill epoxy and solder joints played in causing warpage did not change even when the assembly had 196 solder joints under a 5.8 mm/spl times/5.8 mm chip. Mechanical properties of epoxy depend on the curing and the glass transition temperatures, and these characteristic temperatures clearly divide the warpage levels into two distinctive regions. When the maximum temperature the assembly was exposed to was less than the glass transition temperature (T/sub g/), the warpage of the assembly was characterized by the curing temperature. When the maximum temperature the assembly was exposed to was higher than T/sub g/, the warpage was characterized by T/sub g/ regardless of how high the temperature was. The distinctive deformation curves with sub-micron repeatability are reported for the first time. Depending upon the different characteristic temperatures of an assembly, e.g., 80/spl deg/C for curing and 130/spl deg/C for T/sub g/, the warpage and the Von Misses stress each could increase by as much as a factor of two. Such an increase could affect device reliability for RF packages and alignment for optoelectronic packages.
Influence of leaching parameters on the vanadium extraction from petroleum coke

More than 60 trace elements, including rare metals, can be found in heavy oils. The most valuable component of oils and petroleum products is vanadium. It is used as an alloying agent to create extra strong steel, as a cathode for lithium-ion batteries, and also as a catalyst in the chemical industry. Nowadays studies of various methods for extracting vanadium from heavy oils and petroleum products are actively carried out. This work presents the method of alkaline and acid leaching of vanadium from petroleum coke and also results of the examination of influence of factors such as the duration of the process (0.5, 1.5 and 2.5 h) and the ratio of solid and liquid phases (1:2, 1:3 and 1:4). The highest yield of vanadium 80% is observed using sulfuric acid with the process duration is 1.5 hours and the ratio S/L = 1:4
Evidence from a Field Experiment

Mathematica Policy Research, Inc. This article summarizes the results from two studies that used experimental data to evaluate nonexperimental methods of program evaluation. These studies compared the experimental estimates&mdash;of an employment and training program that used random assignment to allocate its participants into training positions&mdash;to estimates from nonexperimental procedures. Both studies indicate that the nonexperimental methods may not accurately replicate the experimental estimates, and that recently developed methods for constructing comparison groups are no more likely to yield accurate estimates of the impact of training than the more conventional econometric procedures.
Essential Role of Rho-Associated Kinase in ABO Immune Complex-Mediated Endothelial Barrier Disruption

ABO immune complexes (ABO-IC) formed by ABO-incompatible antigen-antibody interaction are associated with hemolysis and platelet destruction in patients transfused with ABO-nonidentical blood products. However, the effects of ABO-IC on endothelial cells (EC) are unclear. ABO-IC were formed in vitro from normal donor-derived plasma and serum. Human pulmonary artery EC (HPAEC) were cultured and treated with media, ABO-identical and –non-identical plasma, and ABO-IC. EC barrier integrity was evaluated using transendothelial electrical resistance (TEER), scanning electron microscopy (SEM), vascular endothelial (VE)-cadherin and phalloidin staining, and Rho-associated Kinase (ROCK) inhibitor treatment. TEER revealed significant/irreversible barrier disruption within 1–2 h of exposure to ABO non-identical plasma and ABO-IC; this occurred independently of EC ABO type. Treatment with ABO-IC resulted in decreased VE-cadherin staining and increased phalloidin staining in a time-dependent manner, suggesting that the resultant increased EC barrier permeability is secondary to actin stress fiber formation and loss of cell surface VE-cadherin. Inhibition of ROCK was effective in protecting against IC-induced barrier disruption even two hours after ABO-IC exposure. ABO-IC causes increased EC barrier permeability by decreasing cell surface VE-cadherin and promoting stress fiber formation, which is preventable by inhibiting ROCK activation to protect against EC contraction and gap formation.
PFCAs with increasing carbon chain lengths up-regulate amino acid transporters and modulate compensatory response of xenobiotic transporters in HepaRG cells

Perfluorinated carboxylic acids (PFCAs) are widespread environmental pollutants for which human exposure has been documented. PFCAs at high doses were known regulate xenobiotic transporters partly through PPARα and CAR in rodent models. Less is known regarding how various PFCAs at a lower concentration modulate transporters for endogenous substrates such as amino acids in human hepatocytes. Such studies are of particular importance because amino acids are involved in chemical detoxification and their transport system may serve as promising therapeutic targets for structurally similar xenobiotics. The focus of this study was to further elucidate how PFCAs modulate transporters involved in intermediary metabolism and xenobiotic biotransformation. We tested the hepatic transcriptomic response of HepaRG cells exposed to 45  M PFOA, PFNA, or PFDA in triplicates for 24 h (vehicle: 0.1% DMSO), as well as the prototypical ligands for PPARα (WY-14643, 45 µM) and CAR (CITCO, 2 µM). PFCAs with increasing carbon chain lengths (C8-C10) regulated more liver genes, with amino acid metabolism and transport ranked among the top enriched pathways and PFDA ranked as the most potent PFCA tested. Genes encoding amino acid transporters, which are essential for protein synthesis, were novel inducible targets by all 3 PFCAs, suggesting a potentially protective mechanism to reduce further toxic insults. None of the transporter regulations appeared to be through PPARα or CAR but potential involvement of Nrf2 is noted for all 3 PFCAs. In conclusion, PFCAs with increasing carbon chain lengths up-regulate amino acid transporters and modulate xenobiotic transporters to limit further toxic exposures in HepaRG