Miracle-dz/UniFAR-FTUs huggingface dataset:
The Price Effects of Cash Versus In-Kind Transfers ∗

This paper examines the effect of cash versus in-kind transfers on local prices. Both types of transfers increase the demand for normal goods; in-kind transfers also increase supply, which should cause prices to fall relative to cash transfers. We test and confirm this prediction using a program in Mexico that randomly assigned villages to receive boxes of food (trucked into the village), equivalently-valued cash transfers, or no transfers. We find that prices are significantly lower under in-kind transfers compared to cash transfers; relative to the control group, in-kind transfers lead to a 4 percent fall in prices while cash transfers lead to a positive but negligible increase in prices. Prices of goods other than those transferred are also affected, but by a small amount. Thus, households’ overall purchasing power is only modestly affected by these general equilibrium effects, even in this setting where program eligibility is high, the transfer per household is sizeable, and hence the supply influx is large. The exception is in remote villages, where the price effects (both the negative effects of in-kind transfers and the positive effects of cash transfers) are considerably larger in magnitude. ∗We thank Steve Coate, Rebecca Dizon-Ross, Liran Einav, Fred Finan, Amy Finkelstein, Ilyana Kuziemko, Karthik Muralidharan, Ben Olken and seminar participants at Stanford, Houston/Rice, Harvard/MIT, Stockholm University, University of Toronto, Chicago Booth, ITAM, SEDESOL, Banco de México, Brown, Yale, Dartmouth, Berkeley, UCSD, Universidad de Chile, RAND, Maryland, Notre Dame, Case Western, University of Virginia, Chicago Fed, NBER Public Economics Program Meeting, MOVE Conference on Development, CEPR Development Economics Conference, and PACDEV for helpful comments. José Marı́a Núñez provided excellent research assistance. This material is based upon work supported by the National Science Foundation under Grant No. 1156941 to Jayachandran. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. Authors’ contact information: jcunha@nps.edu; degiorgi@stanford.edu; seema@northwestern.edu.
Association between Alanine Aminotransferase and Growth Hormone: A Retrospective Cohort Study of Short Children and Adolescents

Objective This study aimed to examine the relationship between serum alanine aminotransferase (ALT) and growth hormone (GH) in children and adolescents with short stature. Methods In this retrospective cohort study, 670 Chinese children and adolescents with short stature were included, and 253 of them received recombinant human GH (rhGH) therapy. Anthropometric and biochemical indicators were measured. GH peak levels were assessed after provocation tests with L-dopa and insulin. The subjects were divided into 3 groups according to the GH peak level. The association between the GH peak and ALT was analyzed. The change of ALT during rhGH therapy was assessed by a generalized additive mixed model. Results Serum ALT and incidence of ALT elevation were both decreased across the GH tertiles (P = 0.002, 0.012, respectively). A univariate analysis showed that the GH peak was negatively associated with ALT (β: -0.12; 95%CI: -0.22, -0.02; P = 0.023). Furthermore, multiple linear stepwise regression analysis demonstrated that the GH peak was independently related to ALT after adjusting for other confounding variables (β: -0.12; 95%CI: -0.24, -0.00; P = 0.042). Besides, mean values of the change in ALT from baseline displayed that, during the early stages of rhGH treatment, serum ALT level indicated a temporary upward trend, but it subsequently gradually decreased (β: -0.16; 95%CI: -0.23, -0.09; P < 0.001). Conclusions GH secretion level was strongly negatively correlated with ALT in short children and adolescents. And rhGH therapy could reduce ALT level over time.
XBlock-ETH: Extracting and Exploring Blockchain Data From Ethereum

Blockchain-based cryptocurrencies have received extensive attention recently. Massive data has been stored on permission-less blockchains. The analysis on massive blockchain data can bring huge business values. However, the lack of well-processed up-to-date blockchain datasets impedes big data analytics of blockchain data. To fill this gap, we collect and process the up-to-date on-chain data from Ethereum, which is one of the most popular permission-less blockchains. We name these well-processed Ethereum datasets as XBlock-ETH, which consists of the data of blockchain transactions, smart contracts, and cryptocurrencies (i.e., tokens). The basic statistics and exploration of these datasets are presented. We also outline the possible research opportunities. The datasets with the raw data and codes have been publicly released online.
The RWTH Aachen Machine Translation System for WMT 2012

This paper describes the statistical machine translation (SMT) systems developed at RWTH Aachen University for the translation task of the NAACL 2012 Seventh Workshop on Statistical Machine Translation (WMT 2012). We participated in the evaluation campaign for the French-English and German-English language pairs in both translation directions. Both hierarchical and phrase-based SMT systems are applied. A number of different techniques are evaluated, including an insertion model, different lexical smoothing methods, a discriminative reordering extension for the hierarchical system, reverse translation, and system combination. By application of these methods we achieve considerable improvements over the respective baseline systems.
Composing Complete and Partial Knowledge

We study theory revision and composition in the context of OLPFOL logic. In this logic, the representation of knowledge is split into two parts: writing definitions for completely known concepts (OLP part), and writing constraints and expressing partial knowledge on other concepts (FOL part). In a previous work, the composition of two OLP-FOL theories with nonintersecting sets of defined predicate symbols was studied. It was argued that the composition is given by the set of common models. Here, we consider the case of two OLP-FOL theories, defining the same predicate p and introducing a form of theory revision that makes possible their composition in the sense previously proposed. We introduce two operators for theory revision: the p-opening operator and the conditional p-opening operator. After applying one of these operators to both theories, the knowledge they represent about p is not complete anymore, and the theories can (under certain conditions) be composed.
Exposure Fusion

In 3D computer graphics, mesh parameterization is a key technique for digital geometry processings(DGP) such as morphing, shape blending, texture transfer, re-meshing and so on. This paper proposes a novel approach for parameterizing a mesh into another one directly. The main idea of our method is to combine a competitive learning and a leastsquare mesh techniques. It is enough to give some semantic feature correspondences between target meshes, even if they are in different shapes or in different poses. We show the effectiveness of our approach by giving some examples of its applications.
Fixation and Attention Allocation in Anesthesiology Crisis Management: An Abstraction Hierarchy Perspective

The abstraction hierarchy analysis tool developed by Vicente and Rasmussen (1992) for Ecological Interface Design (EID) provides an in depth understanding of work domain constraints and information requirements. EID and work domain analysis (WDA) have been successfully applied in several fields. However, application in the medical domain has proven to be much more difficult. This study examines the relationships between three components within the OR: the surgical team, medical equipment, and the patient. It is hypothesized that crisis management failure in the OR is due to attentional mis-allocation and can be undone by re-directing team members' attention to the appropriate level of information structure. We propose a novel structure, based on existing work domain models for the operating room, to analyze the behavior of OR teams and map their attention allocation within the abstraction hierarchy to explain fixation during medical problem solving and crisis management.
MELODY EXTRACTION FROM POLYPHONIC AUDIO SIGNAL MIREX 2010

This paper considers the proposed algorithm submitted to the Music Information Retrieval Evaluation eXchange (MIREX) 2010 “Audio Melody Extraction” task. The proposed melody extraction algorithm can be divided into three steps: (1) a spectral analysis using a variable length window, (2) a pitch candidate estimation, and (3) a pitch sequence identification. In the first step, the short-time Fourier transform (STFT) with variable length window is performed to be robust against dynamic variation of melody line. In the second step, melody pitch candidates of each frame are obtained from weights of a harmonic structure in the spectrum. Furthermore, a melody pitch range estimation is also considered to reduce false-positive and computation. In the third step, a single pitch sequence (melody line) is selected based on the general properties of melody line.
Progress on Application of Aquatic Plants in Microbial Fuel Cells

Microbial fuel cell(MFC)can degrade pollutants and simultaneously convert chemical energy to electricity.As an interdisciplinary exploration in sewage treatment which recovers environment friendly energy,it provides new technology to effectively solve energy and environment problem.Aquatic plants in microbial fuel cell have been tested which show good sewage purification effect and biological producing electrical characteristics.Recently there are two categories for use of aquatic plant as MFC.One uses plant root zone as battery anode,to use root zone secretions to solve the problem of MFC fuel,and the other directly uses low water plants algae for building biocathode MFC,to use algae photosynthesis producing oxygen and build aerobic biocathode MFC,then restore CO 2.Mechanism,regulation measure,operating conditions and technological parameters of aquatic plant in MFC were analyzed and reviewed,further study was also proposed.
Challenges and opportunities in onboarding smart-home devices

Smart-home devices have become integral to daily routines, but their onboarding procedures – setting up a newly acquired smart device into operational mode – remain understudied. The heterogeneity of smart-home devices and their onboarding procedure can easily overwhelm users when they scale up their smart-home system. While Matter, the new IoT standard, aims to unify the smart-home ecosystem, it is still evolving, resulting in mixed compliance among devices. In this paper, we study the complexity of device onboarding from users’ perspectives. We thus performed cognitive walkthroughs on 12 commercially available smart-home devices, documenting the commonality and distinctions of the onboarding process across these devices. We found that onboarding smart home devices can often be tedious and confusing. Users must devote significant time to creating an account, searching for the target device, and providing Wi-Fi credentials for each device they install. Matter-compatible devices are supposedly easier to manage, as they can be registered through one single hub independent of the vendor. Unfortunately, we found such a statement is not always true. Some devices still need their own companion apps and accounts to fully function. Based on our observations, we give recommendations about how to support a more user-friendly onboarding process.
Residential Spatial Layout Design Using Advanced Optimization Techniques

: Spatial layout design profoundly influences architectural development, yet traditional manual approaches suffer from limited solutions due to human cognitive constraints and cost-effectiveness consideration. This study explores selected advanced optimization algorithms — Simulated Annealing Algorithm, Dijkstra Algorithm, Frei Otto's Woolthread Model, Slime Mould Algorithm, and Genetic Algorithms — to enhance residential spatial layouts design. Prototypical cases of common residential planning and design challenges were utilized for the simulated experiments. Comparative analysis highlights Dijkstra's Algorithm and the Genetic Algorithm as optimal choices for path optimization and visual adjustments, contributing to the research on residential spatial layouts.
DiSh: Dynamic Shell-Script Distribution

Shell scripting remains prevalent for automation and data-processing tasks, partly due to its dynamic features— e.g. , expansion, substitution—and language agnosticism— i.e. , the ability to combine third-party commands implemented in any programming language. Unfortunately, these characteristics hinder automated shell-script distribution, often necessary for dealing with large datasets that do not fit on a single computer. This paper introduces D I S H , a system that distributes the execution of dynamic shell scripts operating on distributed filesys-tems. D I S H is designed as a shim that applies program analyses and transformations to leverage distributed computing, while delegating all execution to the underlying shell available on each computing node. As a result, D I S H does not require modifications to shell scripts and maintains compatibility with existing shells and legacy functionality. We evaluate D I S H against several options available to users today: (i) Bash, a single-node shell-interpreter baseline, (ii) P A S H , a state-of-the-art automated-parallelization system, and (iii) Hadoop Streaming, a MapReduce system that supports language-agnostic third-party components. Combined, our results demonstrate that D I S H offers significant performance gains, requires no developer effort, and handles arbitrary dynamic behaviors pervasive in real-world shell scripts.
New constraints on the cosmic mid-infrared background using TeV gamma-ray astronomy

Very high energy gamma-ray data obtained by CAT and HEGRA from active galactic nucleus Mkn 501 are used to constrain the cosmic Mid-Infrared background. While the entire infrared and submillimeter spectrum shape based on models has been fixed and the density scaled as a whole in previous studies, recent measures on the low and high energy infrared background are extensively used in this paper. In this original approach, the infrared distribution is only varied in the unexplored 3.5-100 microns region. With conservative hypothesis on the intrinsic spectra of Mkn 501, an upper limit of 4.7 nW.m-2.sr-1 between 5 and 15 microns is derived, which is very close to the lower limit inferred from deep ISOCAM cosmological surveys at 15 microns. This result is shown to be independent of the exact density of the lambda 100 microns infrared distribution within the uncertainties of the measurements. Moreover, the study presented here rules out a complete extragalactic origin for the 60 microns excess found by Finkbeiner et al. (2000).
Neighborhoods' Food Environments Revisited: Food Deserts or Food Swamps?

This study uses service area-based coverage method and Poisson regression models to assess neighborhood healthy and unhealthy food environments in the City of Edmonton, Canada. We correlate food availability with different neighborhood socio-economic status (SES). Based on different food environments, we further identify three types of vulnerable neighborhoods that can be considered food deserts, food swamps and food tundras. Results from this study can provide policy makers with tailored strategies to effectively improve food environments with limited resources. Key findings include: (1) Neighborhoods with higher rates of deprived population such as unemployed, minority and low income groups have better access to healthy foods in general; (2) Children populations are negatively associated with both healthy and unhealthy food availability; and (3) Good access to public transportation is associated with good coverage of all types of food stores.
Long-read sequencing of an advanced cancer cohort resolves rearrangements, unravels haplotypes, and reveals methylation landscapes

The Long-read POG dataset comprises a cohort of 189 patient tumours and 41 matched normal samples sequenced using the Oxford Nanopore Technologies PromethION platform. This dataset from the Personalized Oncogenomics (POG) program and the Marathon of Hope Cancer Centres Network includes accompanying DNA and RNA short-read sequence data, analytics, and clinical information. We show the potential of long-read sequencing for resolving complex cancer-related structural variants, viral integrations, and extrachromosomal circular DNA. Long-range phasing of variants facilitates the discovery of allelically differentially methylated regions (aDMRs) and allele-specific expression, including recurrent aDMRs in the cancer genes RET and CDKN2A. Germline promoter methylation in MLH1 can be directly observed in Lynch syndrome. Promoter methylation in BRCA1 and RAD51C is a likely driver behind patterns of homologous recombination deficiency where no driver mutation was found. This dataset demonstrates applications for long-read sequencing in precision medicine, and is available as a resource for developing analytical approaches using this technology.
Karakteristik Habitat dan Preferensi Pohon Sarang Orangutan (Pongo pygmaeus wurmbii) di Taman Nasional Tanjung Puting (Studi Kasus Camp Leakey)

Abstrak. Orangutan (Pongo spp) tersebar luas di Asia, namun saat ini hanya ditemukan di Pulau Kalimantan dan Sumatera. Di Kalimantan Tengah, orangutan dengan jumlah populasi tertinggi dapat ditemukan di Taman Nasional (TN) Tanjung Puting. Orangutan memiliki preferensi dalam pemilihan habitatnya dan memiliki sebaran yang merata atau berkelompok. Akibatnya, pengelolaan populasi orangutan, dan habitatnya harus mempertimbangkan preferensi habitat populasi orangutan. Tujuan penelitian ini untuk menentukan karakteristik preferensi habitat orangutan, dan mengidentifikasi faktor-faktor dominan dalam preferensi pohon sarang pada orangutan. Penelitian ini dilakukan pada bulan Februari-Juni 2008 dengan analisis vegetasi. Hasil penelitian dengan analis regresi menunjukkan faktor-faktor ekologi dominan yang menentukan habitat orangutan. Preferensi pohon sarang adalah jumlah spesies tumbuhan pakan dan struktur pohon sarang. Hal ini menunjukkan peluang keberadaan orangutan pada suatu lokasi akan meningkat dengan meningkatnya jumlah spesies tumbuhan pakan. Analisis indeks preferensial berdasarkan metode Neu (1974) menunjukkan dari 3 lokasi yang diteliti, 2 lokasi (dipterocarp dataran rendah dan hutan rawa campuran) memiliki indeks preferensial yang lebih tinggi dibandingkan lokasi yang lain. Abstract. Orangutans (Pongo spp) were once widespread in Asia but are currently found only on the islands of Borneo (Kalimantan) and Sumatra. In Central Kalimantan, orangutans with the highest population number can be found in Tanjung Puting National Park. Orangutans have preferences in their habitat and therefore tend to spread uniformly or in groups. As a consequence, the management of orangutan populations and habitat must consider their habitat preferences. The objectives of this research were to determine the characteristics of orangutan’s habitat preferences, and identify the dominant factors for nest tree preferences of orangutans. This study was conducted in February-June 2008 by using the vegetation analysis. Results of the study with multiple regression analysis showed that the dominant ecology factors which determined orangutan’s habitat and nest tree preference were the number of food plant species and structure of nest trees. This indicated that the probability of the presence of orangutans in a location would increase with an increase in the number of food plant species. Using Neu’s method of preferential index’s analysis, it was concluded that out of the 3 locations studied, 2 locations (dipterocarp low land and mix swamp forest) had preferential indices greater than the other third location. Key words: Tanjung Puting National Park, orangutan, habitat, nest tree preferences.
A robust data obfuscation approach for privacy preserving collaborative filtering

Privacy is defined as the freedom from unauthorized intrusion. The availability of personal information through online databases, such as government records, medical records, and voters lists, pose a threat to personal privacy. The concern over individual privacy has led to the development of legal codes for safeguarding privacy in several countries [56]. However, the ignorance of individuals as well as loopholes in the systems, have led to information breaches even in the presence of such rules and regulations. Protection against data privacy requires modification of the data itself. The term data obfuscation is used to refer to the class of algorithms that modify the values of the data items without distorting the usefulness of the data. The main goal of this thesis is the development of a data obfuscation technique that provides robust privacy protection with minimal loss in usability of the data. Although medical and financial services are two of the major areas where information privacy is a concern, privacy breaches are not restricted to these domains. One of the areas where the concern over data privacy is of growing interest is collaborative filtering. Collaborative filtering systems are being widely used in E-commerce applications to provide recommendations to users regarding products that might be of interest to them. The prediction accuracy of these systems is dependent on the size and accuracy of the data provided by users. However, the lack of sufficient guidelines governing the use and distribution of user data raises concerns over individual privacy. Users often provide the minimal information that is required for accessing these E-commerce services. The lack of rules governing the use and distribution of data disallows sharing of data among different communities for collaborative filtering. The goals of this thesis are (a) the definition of a standard for classifying DO techniques, (b) the development of a robust cluster preserving data obfuscation algorithm, and (c) the design and implementation of a privacy-preserving shared collaborative filtering framework using the data obfuscation algorithm.