Miracle-dz/UniFAR-FTUs huggingface dataset:
Image-Based Surrogates of Socio-Economic Status in Urban Neighborhoods Using Deep Multiple Instance Learning

(1) Background: Evidence-based policymaking requires data about the local population's socioeconomic status (SES) at detailed geographical level, however, such information is often not available, or is too expensive to acquire. Researchers have proposed solutions to estimate SES indicators by analyzing Google Street View images, however, these methods are also resource-intensive, since they require large volumes of manually labeled training data. (2) Methods: We propose a methodology for automatically computing surrogate variables of SES indicators using street images of parked cars and deep multiple instance learning. Our approach does not require any manually created labels, apart from data already available by statistical authorities, while the entire pipeline for image acquisition, parked car detection, car classification, and surrogate variable computation is fully automated. The proposed surrogate variables are then used in linear regression models to estimate the target SES indicators. (3) Results: We implement and evaluate a model based on the proposed surrogate variable at 30 municipalities of varying SES in Greece. Our model has $R^2=0.76$ and a correlation coefficient of $0.874$ with the true unemployment rate, while it achieves a mean absolute percentage error of $0.089$ and mean absolute error of $1.87$ on a held-out test set. Similar results are also obtained for other socioeconomic indicators, related to education level and occupational prestige. (4) Conclusions: The proposed methodology can be used to estimate SES indicators at the local level automatically, using images of parked cars detected via Google Street View, without the need for any manual labeling effort.
Transition From Copper to Fiber Broadband : the Role of DSL Speed and Switching Costs

We estimate a mixed logit model using data on choices of broadband technologies by 94,388 subscribers to a single broadband operator in a European country on a monthly basis from January to December 2014. We find that valuation of DSL connection speed in the range between 1 and 8 MB/s is very similar. Moreover, in January 2014, the valuation of FttH connection with speed of 100 MB/s was not much different than of DSL connection with speed of 1 or 8 MB/s. The valuation however increased over time and in December 2014 it was higher by 59% than of DSL connection with speed of 8 MB/s and by 66% than of DSL connection with speed of 1 MB/s. The small initial difference in valuation of DSL and FttH connections may be because basic Internet needs of consumers such as emailing, reading news, shopping, browsing and even watching videos online can be satisfied with connection speed below 8 MB/s. We also find that consumers face significant switching costs when changing broadband tariffs, which are substantially higher when switching from DSL to FttH technology. According to counterfactual simulations based on our model estimates, switching costs between technologies are the main factor which slows down transition from DSL to FttH.
1 A CLOSER EXAMINATION OF INVESTMENT MANAGER HERDING BEHAVIOUR

Utilising a unique database of daily trades of institutional investors, this paper examines herding behaviour. We find active managers herd more substantially when selling stocks, trading in small stocks, and moving between industry sectors. We also show that broker participation results in a much higher level of herding. Brokers pass their best, most timely information to their largest clients first, and later disseminate the information to smaller clients. Consequently, larger broker institutional clients not only trade before, but also outperform, smaller clients. We also find evidence of leader-follower relationships. Active managers tend to follow those managers with higher past performance. JEL classification: G23
Land Use and Precipitation Affect Organic and Microbial Carbon Stocks and the Specific Metabolic Quotient in Soils of Eleven Ecosystems of Mt. Kilimanjaro, Tanzania

Tropical ecosystems are under increasing pressure of land‐use changes, strongly affecting the carbon cycle. Conversion from natural to agri‐cultural ecosystems is often accompanied by a decrease in the stocks of organic and microbial carbon (Corg, Cmic) as well as changes in microbial activity and litter decomposition. Eleven ecosystems along an elevation gradient on the slopes of Mt. Kilimanjaro were used to investigate impacts of land‐use changes on Corg and Cmic stocks as well as the specific metabolic respiration quotient (qsCO2) in surface soils. Six natural, two semi‐natural and three intensively used agricultural ecosystems were investigated on an elevation gradient from 950 to 3,880 m asl. To estimate the effects of precipitation, rainfall regimes of 3·6 and 20·0 mm were simulated. Corg stocks were controlled by water availability, temperature and net primary production. Agricultural management resulted in decreases of Corg and Cmic stocks by 38% and 76%, respectively. In addition, agricultural systems were characterized by low Cmic:Corg ratios, indicating a decline in available substrate. Enhanced land‐use intensity leads to increased qsCO2 (agricultural > semi‐natural > natural). The traditional homegardens stood out as a sustainable land‐use form with high substrate availability and microbial efficiency. Soil CO2 efflux and qsCO2 generally increased with precipitation level. We conclude that soils of Mt. Kilimanjaro's ecosystems are highly sensitive to land‐use changes and are vulnerable to changes in precipitation, especially at low elevations. Even though qsCO2 was measured under different water contents, it can be used as an indicator of ecosystem disturbances caused by land‐use and management practices. Copyright © 2015 John Wiley & Sons, Ltd.
Estimating the disease burden of ME/CFS in the United States and its relation to research funding

At the National Institutes of Health (NIH), burden of disease is an important factor in funding decisions along with such factors as scientific opportunity, the quality of the science, and the interest of researchers. Recent studies have quantified the burden for a number of diseases in the United States and the NIH has used that information to analyze how its own funding patterns correspond to disease burden. However, the burden of disease has not been quantified for myalgic encephalomyelitis, also called chronic fatigue syndrome (ME/CFS) and is often underestimated due to a lack of research and the misperceptions about the nature of the disease. Using the limited information in the literature, this paper develops a preliminary estimate of the disease burden of ME/CFS in the United States, using the World Health Organization’s Disability Adjusted Life Years (DALY) measure. The ME/CFS DALY estimate is then compared to the NIH’s 2013 analysis of research funding versus DALY across other funded diseases in order to estimate a level of funding for ME/CFS that would be commensurate with disease burden. Even given the limitations arising from sparse data, this analysis demonstrates that federal research funding for this disease is far less than what would be expected by the burden of the disease. We conclude that the annual research funding for ME/CFS would need to increase twenty-five fold or more to be commensurate with disease burden. This level of funding would best leverage the growing interest of researchers and the significant scientific opportunities that exist to understand the pathology of this disease and to advance diagnostics and treatments. Correspondence to: Leonard A. Jason, Ph.D., Professor of Psychology, Director, Center for Community Research DePaul University, 990 W. Fullerton Ave, Suite 3100, Chicago, Il. 60614, USA, Tel: 773-325-2018, E-mail: ljason@depaul.edu
Cadaveric Vs. Live-Donor Kidney Transplants: The Interaction Of Institutions And Inequality

“In 1991, the World Health Assembly approved a set of Guiding Principles which emphasize voluntary donation, non-commercialization and a preference for cadavers over living donors” (World Health Organization). We investigate whether factors such as inequality, rule of law and religion have any effect on the ratio of cadaveric transplants to all transplants. Using an unbalanced annual dataset from 64 countries over 1993-2004, we show particularly for developing countries that an improvement in equality and rule of law encourage cadaveric kidney transplants. Religion also plays an important role in that relationship.
Repository September 2018 INSecS : An Intelligent Network Security System

There are new challenges in network security, introduced by the nature of modern networks like IoT systems, Cloud systems, and other distributed systems. System resource limitations in IoT, delays in processing the large stream of data from Cloud and distributed system, incapability to handle multi-step attacks due to delay in updates, limited datasets used for Intrusion Detection System (IDS) training which impacts the system performance are some of the pressing issues. To address these challenges, the author proposes Intelligent Network Security Systems, a framework that can handle these issues and also be as accurate as a commercial grade IDS. The proposed framework consists of three components: a Dataset Creation Software (DCS), an Intrusion Detection System and a Learning module. This thesis presents implementation details and validation results for DCS and IDS. The first component is a highly customizable software framework capable of generating labeled network intrusion datasets on demand. This software is able to collect data from a live network as well as from a pre-recorded packet capture file. The output can be either Raw packet capture (PCAP) with selected attributes per packet or a processed dataset with customized attributes related to both individual packet features and overall traffic behavior within a time window. The abilities of this component are compared with a state-of-the-art dataset creation system through a feature comparison. The proposed Intrusion Detection System is a novel, distributed IDS that is able to perform in real-time in a distributed system. Hierarchical decision making is used to reduce traffic overhead on the IDS and allow faster Intrusion Detection. The IDS also detects multi-step attacks faster by updating the system rules when a reconnaissance attack is detected, without any human intervention. Internal attacks are also detected easily because of the distributed nature of the IDS. The performance tests show that the IDS performs 8 times faster on averages with the hierarchical decision-making structure and still maintains the same level of accuracy as Snort.
Real-time guidance for cardiopulmonary resuscitation in Mixed Reality

Cardiopulmonary Resuscitation (CPR) is a life-saving procedure that gives a cardiac arrest victim a second chance. The application window is short as the chances of survival falls drastically with every minute without resuscitation. Outofhospital cardiac arrests are even riskier, as the state of victim worsens while waiting for specialized medical personnel. CPR is simple and composed of few steps, with instructions widely available in First Aid Kits or online. Nonetheless, it is usually not performed by most bystanders as they fear to harm the victim by its incorrect application. Recently, the introduction of Mixed Reality (MR) devices such as Microsoft HoloLens enabled the development of systems that leverage contextual information such as the location of the victim to display guiding information where it should be performed, thereby allowing bystanders to focus on the task at hand. In this demo, we present HoloCPR, a Mixed Reality application that provides real-time instructions for performing CPR. Paste the appropriate copyright statement here. ACM now supports three different copyright statements: • ACM copyright: ACM holds the copyright on the work. This is the historical approach. • License: The author(s) retain copyright, but ACM receives an exclusive publication license. • Open Access: The author(s) wish to pay for the work to be open access. The additional fee must be paid to ACM. This text field is large enough to hold the appropriate release statement assuming it is single spaced. Every submission will be assigned their own unique DOI string to be included here. ACM Classification
Current Research on the Safety of Pyrethroids Used as Insecticides

Pyrethroids are synthetic derivatives of natural pyrethrins extracted from Chrysanthemum cinerariaefolium. They are 2250 times more toxic to insects than to vertebrates due to insects’ smaller size, lower body temperature and more sensitive sodium channels. In particular, three pyrethroid compounds, namely deltamethrin, permethrin, and alpha-cypermethrin, are commonly used as insecticides and are recommended for in-home insect control because they are considered to be relatively non-toxic to humans in all stages of life. However, recent data show that they are not completely harmless to human health as they may enter the body through skin contact, by inhalation and food or water, and absorption level depending on the type of food. Permethrin seems to have an adverse effect on fertility, the immune system, cardiovascular and hepatic metabolism as well as enzymatic activity. Deltamethrin induces inflammation, nephro- and hepatotoxicity and influences the activity of antioxidant enzymes in tissues. Alpha-cypermethrin may impair immunity and act to increase glucose and lipid levels in blood. The aim of the review is to provide comprehensive information on potential hazards associated to human exposure to deltamethrin, permethrin and alpha-cypermethrin. The results of presented studies prove that the insecticides must be used with great caution.
Report on tooth detection and numbering in panoramic radiographs using CNNs

Dental radiography analysis is an important part of the diagnostic process in clinical dentistry. Interpretation by a human expert includes teeth detection and numbering according to the standard notation. In this paper, a novel end-to-end solution based on the convolutional neural networks (CNN) is proposed to automatically perform this task for panoramic radiographs (PV). Teeth detection method is based on the state-of-the-art Faster R-CNN architecture. Teeth numbering method utilizes the classical VGG-16 CNN together with a heuristic to improve the classification results according to the teeth spatial arrangement rules. The system achieves the F2score of 0.99 for the teeth detection and the accuracy of 0.98 for the teeth numbering on the test dataset. The performance of the proposed solution is comparable with the human expert level.
Convenience Yields for Co2 Emission Allowance Futures Contracts

In January 2005 the EU-wide CO2 emissions trading system (EU-ETS) has formally entered into operation. Within the new trading system, the right to emit a particular amount of CO2 becomes a tradable commodity - called EU Allowances (EUAs) - and affected companies, traders and investors will face new strategic challenges. In this paper we investigate the nature of convenience yields for CO2 emission allowance futures. We conduct an empirical study on price behavior, volatility term structure and correlations in different CO2 EUA contracts. Our findings are that the market has changed from initial backwardation to contango with significant convenience yields in future contracts for the Kyoto commitment period starting in 2008. A high fraction of the yields can be explained by the price level and volatility of the spot prices. We conclude that the yields can be interpreted as market expectation on the price risk of CO2 emissions allowance prices and the uncertainty of EU allocation plans for the Kyoto period.
Iterative Depth Warping

This article presents an iterative backward-warping technique and its applications. It predictively synthesizes depth buffers for novel views. Our solution is based on a fixed-point iteration that converges quickly in practice. Unlike the previous techniques, our solution is a pure backward warping without using bidirectional sources. To efficiently seed the iterative process, we also propose a tight bounding method for motion vectors. Non-convergent depth holes are inpainted via deep depth buffers. Our solution works well with arbitrarily distributed motion vectors under moderate motions. Many scenarios can benefit from our depth warping. As an application, we propose a highly scalable image-based occlusion-culling technique, achieving a significant speed-up compared to the state of the art. We also demonstrate the benefit of our solution in multi-view soft-shadow generation.
A Study of the Replacement of Materials in Smart Card

Gold, nickel and copper are usually used in connector of the smart card. Since Au is expensive and Ni is an allergenic material, simulated (CES) and bibliographical work is carried out in order to replace the Au and Ni layer in smart card connectors without sacrificing reliability. During the work, mechanical and electrical properties, corrosion resistance, cost, toxicity and process compatibility of the samples have been taken into consideration. Cu alloying with Zn or Sn, Cr and stainless steel were selected for electrodeposition process. Secondly, carbides (WC, TiC, ZrC), Ti, TiN, borides (TiB2) and silicide (MoSi2) are considered as a vapour deposited materials and some Cu alloying with Al, N or Mg also considered via ion implantation processes. But, vapour deposition and implantation are high energy processes compared to the electrodeposition process, which is expensive. Therefore, electrodeposited materials such as, Cu alloys (Brass or bronze), Cr and stainless steel could be considered as promising candidate to replace the Au and Ni layer in smart card connectors.
Predicting intentions to fake in psychological testing: which normative beliefs are important

While previous research has examined the utility of the Theory of Planned Behavior (TPB) in relation to intentions to fake in psychological testing, the current research extended the TPB model to empirically assess the role of moral norms and ethics. A hierarchical multiple regression was conducted (N = 225). In step 1, attitude, perceived behavioral control, and subjective norm significantly predicted intention to fake, although only attitude and perceived behavioral control were significant individual predictors, with 52.3% of variance explained. In step 2, addition of moral obligation norms significantly improved predicted intention to fake and explained an additional 14% of variance. In step 3, ethical position explained no additional variance. Future research should consider specific applicant faking scenarios or a behavioral outcome measure. It is concluded that personal, moral norms, rather than other-centred norms, are valuable when predicting faking intentions, and that integration of existing theoretical models of faking is indicated.
FaceID-GAN: Learning a Symmetry Three-Player GAN for Identity-Preserving Face Synthesis

Face synthesis has achieved advanced development by using generative adversarial networks (GANs). Existing methods typically formulate GAN as a two-player game, where a discriminator distinguishes face images from the real and synthesized domains, while a generator reduces its discriminativeness by synthesizing a face of photorealistic quality. Their competition converges when the discriminator is unable to differentiate these two domains. Unlike two-player GANs, this work generates identity-preserving faces by proposing FaceID-GAN, which treats a classifier of face identity as the third player, competing with the generator by distinguishing the identities of the real and synthesized faces (see Fig.1). A stationary point is reached when the generator produces faces that have high quality as well as preserve identity. Instead of simply modeling the identity classifier as an additional discriminator, FaceID-GAN is formulated by satisfying information symmetry, which ensures that the real and synthesized images are projected into the same feature space. In other words, the identity classifier is used to extract identity features from both input (real) and output (synthesized) face images of the generator, substantially alleviating training difficulty of GAN. Extensive experiments show that FaceID-GAN is able to generate faces of arbitrary viewpoint while preserve identity, outperforming recent advanced approaches.
Beyond use versus availability: behaviour-explicit resource selection

Resource selection studies are common in the wildlife ecology literature and typically rely on the comparison of locations used by wildlife and locations assumed to be available for use but where use was not observed. While standard use-availability designs are helpful for establishing general patterns of species occurrence, they are limited in their ability to help researchers understand the underlying behavioural mechanisms that lead to observed space-use patterns. Based on spatially-explicit behavioural observations from coyotes Canis latrans in Yellowstone National Park, Wyoming, we estimated resource selection for specific behaviours (i.e. predatory, laying and travelling) and for all used locations irrespective of behaviour, to test whether resource selection is behaviour-specific and not generalizable across behaviours. Behaviour-specific models differed significantly from the model not partitioned by behaviour. In particular, the predatory model identified selection for mesic-meadows which have previously been documented to have high small-mammal abundance. The non-partitioned model, however, showed avoidance of this vegetation type. Our results show that resource selection differs between behaviours and suggest that standard techniques for estimation of resource selection might be of limited use for understanding the underlying behavioural mechanisms of space use. Future research should continue to improve on methods for partitioning fine-scale movement data obtained from telemetry collars into discrete movement bouts representative of different behaviours.
Preparation and Spectroscopic Properties of Monolayer-Protected Silver Nanoclusters

Silver nanoclusters protected by 2-phenylethanethiol (1), 4-fluorothiophenol (2), and l-glutathione (3) ligands were successfully synthesized. The optical properties of the prepared silver nanoclusters were studied. The absorption signal of Ag@SCH2CH2Ph in toluene can be found at 469 nm, and Ag@SPhF in THF shows two absorption bands at 395 and 462 nm. Ag@SG in water absorbs at 478 nm. Mie theory in combination with the Drude model clearly indicates the peaks in the spectra originate from plasmonic transitions. In addition, the damping constant as well as the dielectric constant of the surrounding medium was determined. In addition, the CD spectra of silver nanoclusters protected by the three ligands (1–3) were also studied. As expected, only the clusters of type 3 gave rise to chiroptical activity across the visible and near-ultraviolet regions. The location and strength of the optical activity suggest an electronic structure of the metal that is highly sensitive to the chiral environment imposed by the g.