Miracle-dz/UniFAR-FTUs huggingface dataset:
Implementing type theory in higher order constraint logic programming

In this paper, we are interested in high-level programming languages to implement the core components of an interactive theorem prover for a dependently typed language: the kernel – responsible for type-checking closed terms – and the elaborator – that manipulates open terms, that is terms containing unresolved unification variables. In this paper, we confirm that λProlog, the language developed by Miller and Nadathur since the 80s, is extremely suitable for implementing the kernel. Indeed, we easily obtain a type checker for the Calculus of Inductive Constructions (CIC). Even more, we do so in an incremental way by escalating a checker for a pure type system to the full CIC. We then turn our attention to the elaborator with the objective to obtain a simple implementation thanks to the features of the programming language. In particular, we want to use λProlog’s unification variables to model the object language ones. In this way, scope checking, carrying of assignments and occur checking are handled by the programming language. We observe that the eager generative semantics inherited from Prolog clashes with this plan. We propose an extension to λProlog that allows to control the generative semantics, suspend goals over flexible terms turning them into constraints, and finally manipulate these constraints at the meta-meta level via constraint handling rules. We implement the proposed language extension in the Embedded Lambda Prolog Interpreter system and we discuss how it can be used to extend the kernel into an elaborator for CIC.
Point cloud segmentation through spectral clustering

Spectral clustering is a powerful technique in data analysis. We extend the spectral clustering method to point cloud segmentation. By connecting each point with its neighbors and assigning the edge a weight that describes the similarity, the point cloud can be represented as a graph. Then segmentation problem can be turned into a graph min-cut problem, which is NP hard. If we cut this graph into p parts, spectral clustering provides a relaxed solution in space Rn×p. A novel approach is presented to find the neighbors of a point in the point cloud, which is adaptive to the sampling density of point cloud and is more accurate than the k-nearest neighbors on close-by surface sheets. A bilateral filter is used to guarantee that only the close points with similar normal directions having high weights. By removing redundant eigenvectors from the spectral domain, the segmentation solution is found in a lower dimensional space. We prove that this method is theoretically reasonable and experimental results show the efficiency.
Female Autonomy, Social Norms and Intimate Partner Violence against Women in Turkey

Abstract The theoretical literature asserts that intimate partner violence against women stems from inequalities within the relationship, and it strengthens both male power and control, and female subordination. Using Structural Equation Modelling, this paper addresses the two-way relationship between intimate partner violence and female autonomy in Turkey. Consistent with the theory, we find that (1) violence has a significant and negative effect on female autonomy; and (2) the incidence of violence decreases with the level of female autonomy. We also find that intimate partner violence is an increasing function of the strength of men’s commitment to social norms upholding traditional gender roles.
Personal Heart Monitoring and Rehabilitation System using Smart Phones

This paper discusses a personalized heart monitoring system using smart phones and wireless (bio) sensors. Based on several scenarios we present the functionality of a prototype we have built. The application is capable of monitoring the health of high risk cardiac patients. The smart phone application analyses in real-time sensor and environmental data and can automatically alert the ambulance and pre assigned caregivers when a heart patient is in danger. It also transmits sensor data to a healthcare centre for remote monitoring by a nurse or cardiologist. The system can be personalized and rehabilitation programs can monitor the progress of a patient. Rehabilitation programs can be used to give advice (e.g. exercise more) or to reassure the patient.
The Financial Market Effects of the Federal Reserve's Large-Scale Asset Purchases

Since December 2008, the Federal Reserve’s traditional policy instrument, the target federal funds rate, has been effectively at its lower bound of zero. In order to further ease the stance of monetary policy as the economic outlook deteriorated, the Federal Reserve purchased substantial quantities of assets with medium and long maturities. In this paper, we explain how these purchases were implemented and discuss the mechanisms through which they can affect the economy. We present evidence that the purchases led to economically meaningful and long-lasting reductions in longer-term interest rates on a range of securities, including securities that were not included in the purchase programs. These reductions in interest rates primarily reflect lower risk premiums, including term premiums, rather than lower expectations of future short-term interest rates.
Identification of Image Operations Based on Steganalytic Features

Image forensics have attracted wide attention during the past decade. Though many forensic methods have been proposed to identify image forgeries, most of them are targeted ones, since their proposed features are highly dependent on the image operation under investigation. The performance of the well-designed features for detecting the targeted operation usually degrades significantly for other operations. On the other hand, a wise attacker can perform anti-forensics to fool the existing forensic methods, making countering anti-forensics become an urgent need. In this paper, we try to find a universal feature to detect various image processing and anti-forensic operations. Based on our extensive experiments and analysis, we find that any image processing/anti-forensic operations would inevitably modify many image pixels. This would change some inherent statistics within original images, which is similar to the case of steganography. Therefore, we model image processing/anti-forensic operations as steganography problems, and propose a detection strategy by applying steganalytic features. With some advanced steganalytic features, we are able to detect various image operations and further identify their types. In our experiments, we have tested several steganalytic features on 11 different kinds of typical image processing operations and 4 kinds of anti-forensic operations. The experimental results have shown that the proposed strategy significantly outperforms the existing forensic methods in both effectiveness and universality.
A framework for the analytical performance assessment of matrix and tensor-based ESPRIT-type algorithms

In this paper we present a generic framework for the asymptotic performance analysis of subspace-based parameter estimation schemes. It is based on earlier results on an explicit first-order expansion of the estimation error in the signal subspace obtained via an SVD of the noisy observation matrix. We extend these results in a number of aspects. Firstly, we derive an explicit first-order expansion of the Higher- Order SVD (HOSVD)-based subspace estimate. Secondly, we show how to obtain explicit first-order expansions of the estimation error of ESPRIT-type algorithms and provide the expressions for matrix-based and tensor-based Standard ESPRIT and Unitary ESPRIT. Thirdly, we derive closed-form expressions for the mean square error (MSE) and show that they only depend on the second-order moments of the noise. Hence, we only need the noise to be zero mean and possess finite second order moments. Fourthly, we investigate the effect of using Structured Least Squares (SLS) to solve the overdetermined shift invariance equations in ESPRIT and provide an explicit first-order expansion as well as a closed-form MSE expression. Finally, we simplify the MSE for the special case of a single source and compute the asymptotic efficiency of the investigated ESPRIT-type algorithms in compact closed-form expressions which only depend on the array size and the effective SNR. Our results are more general than existing results on the performance analysis of ESPRIT-type algorithms since (a) we do not need any assumptions about the noise except for the mean to be zero and the second-order moments to be finite (in contrast to earlier results that require Gaussianity or second-order circular symmetry); (b) our results are asymptotic in the effective SNR, i.e., we do not require the number of samples to be large; (c) we present a framework that incorporates various ESPRIT-type algorithms in one unified manner.
DATA-DRIVEN MODELING FOR WATER QUALITY PARAMETERS PREDICTION OF THE DRAINAGE SYSTEM ASSOCIATED WITH LAKE MANZALA, EGYPT

Lake Manzala is the largest of the Egyptian lakes along the Mediterranean coast and the most productive for fisheries. It is located on the Eastern margin of the Nile Delta between the Damietta Branch of the River Nile and Port Said on the Suez Canal. Two main drains namely, Bahr El-Baker Drain system and Bahr Hadous Drain system flow into Manzala Lake and drain a considerable volume of drainage water into the lake. Water body of Lake Manzal is affected qualitatively and quantitatively by drainage water that flow into the lake. In most cases of water quality modeling, mathematical models is a helpful tool that might be used to predict the parameters of water quality. Deterministic models are commonly used to simulate the system behavior. Most of these models can only be applied to simplified cases or to situations where the models are strictly calibrated and validated, with no adequate accuracy when applied to unrestricted conditions. However most ecological systems are so complex and unstable. Data-driven models are computing methods that are capable of extracting different system states without using complex relationships. The main objective of the present study is to exploit the capabilities of the adaptive neuro-fuzzy inference system (ANFIS) for drains system quality predictions with emphasis on total phosphorus (TP) and total nitrogen (TN). Discharge, pH, total suspended solids (TSS), electrical conductivity (EC), total dissolved solids (TDS), Temperature, dissolved oxygen (DO) and turbidity (FTU) were the input parameters of the ANFIS models. The models were calibrated and validated against the measured drainage water data for the period from year 2001 to 2010. Predicted and observed values of water quality parameters were evaluated using several common evaluation criteria. Results of model performance showed that the proposed ANFIS models were capable of simulating the water quality parameters and provided reliable prediction of TP and TN. Results showed also that the proposed models could be a good tool for Onsite Water Quality evaluation.
Characterizing the motives and environmental literacy of undergraduate and graduate students who elect environmental programs – a comparison between teaching-oriented and other students

Abstract One aspect of the increasing position of sustainability in higher education is establishment of distinct interdisciplinary environment-oriented programs. The point-of-departure of this study is differentiation between teaching- and non-teaching-oriented students, in view of their different respective professional roles in society. The motives and environmental literacy (EL) of incoming students were investigated in three types of sustainability programs in Israel: undergraduate teacher-training, graduate teacher-education and graduate non-teacher programs. For all students acquiring knowledge was the major motive for studies. Undergraduate student-teachers demonstrated the least developed EL, although it is slightly higher than that found for incoming student-teachers a decade ago. Graduate teacher-students displayed strong identity as educational agents-of-change and role-models; however, their limited environmental-knowledge raises questions concerning providing knowledge foundations in undergraduate teacher-training programs, indicating the necessity to supplement this in graduate teacher-programs. Graduate non-teacher students perceive their continuing sustainability-oriented studies as a means for developing an environmental career and enter these programs relatively environmentally-literate. The implications focus on necessary components and characteristics of sustainability-programs directed to teaching- and non-teaching-oriented students. These include the necessity to strengthen the environmental-knowledge component in programs directed to teachers; and embed opportunities for professional internships within graduate programs for non-teachers seeking environmental careers.
Pick-n-mix approaches to technology supply : XML as a standard “glue” linking universalised locals

We report on our experiences in a participatory design project to develop ICTs in a hospital ward working with deliberate self-harm patients. This project involves the creation and constant re-creation of sociotechnical ensembles in which XML-related technologies may come to play vital roles. The importance of these technologies arises from the aim underlying the project of creating systems that are shaped in locally meaningful ways but reach beyond their immediate context to gain wider importance. We argue that XML is well placed to play the role of "glue" that binds multiple such systems together. We analyse the implications of localised systems development for technology supply and argue that inscriptions that are evident in XML-related standards are and will be very important for the uptake of XML technologies.
Micro-optical Components for a MEMS Integrated Display

Today, Cathode Ray Tube (CRT) and Liquid Crystal Display (LCD) are the two mainstream display technologies. Plasma display panels (PDP) are thinner than CRT displays and brighter than LCD with good contrast ratio, contributing to the rapid growth in the wall display market. However, each display technology can address only a limited market segment, according to its characteristic advantages and limitations. Microelectro-mechanical display systems are attracting a lot of attention because of their potentially low power consumption, higher contrast ratio and cost effectiveness [1]. Several optical MEMS based display technologies have been proposed such as DLP [2], GLV [3], IMod [4], Gyricon [5] and LCOS [6]. Among these technologies, the major challenge in commercialization of MEMS displays is the cost of the production and packaging. Thus, the next generation of MEMS displays must include key components developed for the improvement of device performance and the reduction of manufacturing costs. This paper summarizes the results from our previous published papers on reflective [7] and transmissive [8] optical switches, as well as microlens arrays for MEMS integrated display systems. They are three key components for MEMS, including: 1) a dual-servo-scanning mirror, which makes use of thermal and electrostatic driving principles for low voltage large static tiltingangle reflective optical switching or scanning; 2) a transmissive zigzag electrostatic microoptical switch (TMOS); 3) and a process for making microlens arrays without expensive processing costs for fabrication. The prototypes of reflective and transmissive optical switches are fabricated in the Cronos MUMPs® foundry process.
COASYM-MAC: A cooperative Asymmetric MAC protocol for Wireless Sensor Network

Link asymmetry, arisen from varying coverage distance between two adjacent nodes, poses a real challenge for designing efficient receiver initiated MAC protocol for extremely low duty-cycled wireless sensor networks (WSN). One of the viable solution to overcome this limitation is to exploit the benefit of cooperative communication. In this paper, we propose a cooperative MAC protocol for WSN that effectively reduces asymmetry by taking advantage of alternative paths between a pair of nodes with link asymmetry. Simulation results show that our proposed scheme achieves significant improvement in performance compared with Asym-MAC, a state-of-the-art MAC protocol for WSN with asymmetric links. This performance improvement is effectively demonstrated in terms of energy consumption, average delay per packet and packet reception ratio.
Evaluation of Practice Frameworks for Social Work with Children and Families: Exploring the Challenges

ABSTRACT Implementing a practice framework with a clear theoretical and practical approach to working with children and families seems a self-evident way to improve practice, but there is a paucity of evaluative research about their impact on outcomes for children and families. One reason for this lack of research may be that it is challenging. In this article, these challenges are explored in relation to fidelity, impact, attribution, and the positioning of the researcher. To generate ideas about how to conduct evaluative research, research about solution-based casework is explored, with additional insights from research about other frameworks.
Flow-Limited Authorization : Technical Report

Because information flow control mechanisms often rely on an underlying authorization mechanism, their security guarantees can be subverted by weaknesses in authorization. Conversely, the security of authorization can be subverted by information flows that leak information or that influence how authority is delegated between principals. We argue that interactions between information flow and authorization create security vulnerabilities that have not been fully identified or addressed in prior work. We explore how the security of decentralized information flow control (DIFC) is affected by three aspects of its underlying authorization mechanism: first, delegation of authority between principals; second, revocation of previously delegated authority; third, information flows created by the authorization mechanisms themselves. It is no surprise that revocation poses challenges, but we show that even delegation is problematic because it enables unauthorized downgrading. Our solution is a new security model, the Flow-Limited Authorization Model (FLAM), which offers a new, integrated approach to authorization and information flow control. FLAM ensures robust authorization, a novel security condition for authorization queries that ensures attackers cannot influence authorization decisions or learn confidential trust relationships. We discuss our prototype implementation and its algorithm for proof search.
Pretty Fast Analysis: An embarrassingly parallel algorithm for biological simulation analysis

A parallel code has been written in FORTRAN90, C, and MPI for the analysis of biological simulation data. Using a master/slave algorithm, the software operates on AMBER generated trajectory data using either UNIX or MPI file IO, and it supports up to 15 simultaneous function calls. This software has been performance tested on the Ranger Supercomputer on trajectory data of an aqueous bacterial reaction center micelle. Although the parallel reading is poor, the analysis algorithm itself shows embarrassingly parallel speedup up to 1024 compute nodes. At this CPU count the overall scaling of the software compares well NAMD's best reported speedup, and outperforms AMBER's best known scaling by a factor of 3, while using only a small number of function calls and a short trajectory length.
Genome-Wide Studies of Histone Demethylation Catalysed by the Fission Yeast Homologues of Mammalian LSD1

In order to gain a more global view of the activity of histone demethylases, we report here genome-wide studies of the fission yeast SWIRM and polyamine oxidase (PAO) domain homologues of mammalian LSD1. Consistent with previous work we find that the two S. pombe proteins, which we name Swm1 and Swm2 (after SWIRM1 and SWIRM2), associate together in a complex. However, we find that this complex specifically demethylates lysine 9 in histone H3 (H3K9) and both up- and down-regulates expression of different groups of genes. Using chromatin-immunoprecipitation, to isolate fragments of chromatin containing either H3K4me2 or H3K9me2, and DNA microarray analysis (ChIP-chip), we have studied genome-wide changes in patterns of histone methylation, and their correlation with gene expression, upon deletion of the swm1+ gene. Using hyper-geometric probability comparisons we uncover genetic links between lysine-specific demethylases, the histone deacetylase Clr6, and the chromatin remodeller Hrp1. The data presented here demonstrate that in fission yeast the SWIRM/PAO domain proteins Swm1 and Swm2 are associated in complexes that can remove methyl groups from lysine 9 methylated histone H3. In vitro, we show that bacterially expressed Swm1 also possesses lysine 9 demethylase activity. In vivo, loss of Swm1 increases the global levels of both H3K9me2 and H3K4me2. A significant accumulation of H3K4me2 is observed at genes that are up-regulated in a swm1 deletion strain. In addition, H3K9me2 accumulates at some genes known to be direct Swm1/2 targets that are down-regulated in the swm1Δ strain. The in vivo data indicate that Swm1 acts in concert with the HDAC Clr6 and the chromatin remodeller Hrp1 to repress gene expression. In addition, our in vitro analyses suggest that the H3K9 demethylase activity requires an unidentified post-translational modification to allow it to act. Thus, our results highlight complex interactions between histone demethylase, deacetylase and chromatin remodelling activities in the regulation of gene expression.
A correlation between EGFR gene mutation status and bronchioloalveolar carcinoma features in Japanese patients with adenocarcinoma.

BACKGROUND The presence of epidermal growth factor receptor (EGFR) mutations in gefitinib-naive lung cancer patients has been reported to be higher in females, in non-smokers, in Japanese, and in adenocarcinoma patients, especially in bronchioloalveolar carcinoma (BAC). To further investigate the prevalence of EGFR mutations in relation to pathological factors, we evaluated EGFR mutations in series of Japanese adenocarcinoma patients who had never been treated with gefitinib. METHODS In the previous studies, we examined mutation status in the tyrosine kinase domain of EGFR, exon18 through exon21, in 112 primary lung adenocarcinoma samples. Using these data, adenocarcinomas were histologically classified according to the presence or absence of bronchioloalveolar components. RESULTS Among 112 patients, 48 had adenocarcinoma with BAC components. Those with adenocarcinomas with BAC components had higher frequency of EGFR mutation (28/48, 58%) than those with non-BAC adenocarcinoma (24/64, 37%, P = 0.036). Male patients had the same trend; 12/23 (52%) male patients with adenocarcinoma with BAC components and 10/47 (21%) of those with non-BAC adenocarcinoma had EGFR mutation (P = 0.0135) but there was no correlation between the EGFR mutation status and with/without BAC components in 42 female patients (P = 0.30). Among 11 male non-smokers, patients with adenocarcinoma with BAC components had a tendency to have EGFR mutation more frequently than those with non-BAC adenocarcinoma (P = 0.061). In clear contrast, the frequency of EGFR mutation did not differ significantly between male smoker patients with adenocarcinoma with BAC components and those with non-BAC. Among patients with adenocarcinoma with BAC components, those with adenocarcinoma with EGFR gene mutation had a significantly better 5 year survival than those with adenocarcinoma with wild-type (85.7 versus 46.0%, P = 0.0017). CONCLUSIONS Adenocarcinomas with BAC components in male non-smokers seem to predict the presence of EGFR mutation. Half of female adenocarcinoma patients with EGFR mutation exhibit adenocarcinomas with non-BAC suggesting a different behavior from those in males. The prognosis of patients with adenocarcinoma with BAC components with EGFR gene mutation is predicted to be better than that of patients with adenocarcinoma with BAC components with wild-type EGFR gene.