Miracle-dz/UniFAR-FTUs huggingface dataset:
CLASS: Contemplative landscape automated scoring system

This paper presents an interdisciplinary study joining insights of landscape architecture and computer vision. In this work we used a dataset of contemplative landscape images that was collected and evaluated by experts in landscape architecture. We used the dataset to develop nine k-means clustering and one K-nearest neighbors models that are able to score landscape images based on seven different landscape image features (layers, landform, vegetation, color and light, compatibility, archetypal elements, character of peace and silence) that were identified as contributing to the overall contemplativeness of a landscape. Finally, we chose the combination of models that would produce the best combined contemplativeness score and created CLASS a scoring system that can evaluate the contemplativeness of landscape images with scores similar to those of experts.
The Design of a Synthesis Tool for Interrupt-based Real Time Embedded Software

There is a general lack of CAD tools for real-time embedded software, thus we have developed a software synthesis tool with a graphical user interface for real-time embedded systems. We propose an Interrupt Time Petri Nets (ITPN) model for real-time embedded software requirements modeling. ITPN can handle both interrupt behavior and real-time constraints on tasks in a real-time embedded system. An Interrupt-Based Quasi-Dynamic Scheduling (IQDS) algorithm is proposed to find valid task schedules satisfying interrupt behavior specifications and real-time constraints in a real time embedded system. We use a Code Generation algorithm to produce 8051 micro-controller C program code. The graphical user interface makes our tool more user-friendly. This tool supports the Windows OS environment and can be used for system model input and easy setting of system parameters. Finally, we use two industrial examples to illustrate the correctness of our methodology and the increase in productivity provided by our real-time embedded software synthesis tool.
ESTScan: A Program for Detecting, Evaluating, and Reconstructing Potential Coding Regions in EST Sequences

One of the problems associated with the large-scale analysis of unannotated, low quality EST sequences is the detection of coding regions and the correction of frameshift errors that they often contain. We introduce a new type of hidden Markov model that explicitly deals with the possibility of errors in the sequence to analyze, and incorporates a method for correcting these errors. This model was implemented in an efficient and robust program, ESTScan. We show that ESTScan can detect and extract coding regions from low-quality sequences with high selectivity and sensitivity, and is able to accurately correct frameshift errors. In the framework of genome sequencing projects, ESTScan could become a very useful tool for gene discovery, for quality control, and for the assembly of contigs representing the coding regions of genes.
A Role for Protein Kinase C-Dependent Upregulation of Adrenomedullin in the Development of Morphine Tolerance in Male Rats

Adrenomedullin (AM) belongs to calcitonin gene-related peptide (CGRP) family and is a pronociceptive mediator. This study investigated whether AM plays a role in the development of tolerance to morphine-induced analgesia. Repetitive intrathecal injection of morphine increased the expression of AM-like immunoreactivity (AM-IR) in the spinal dorsal horn and dorsal root ganglion (DRG) neurons. Ganglion explant culture study showed that this upregulation of AM-IR was μ-opioid receptor dependent through the use of another agonist, fentanyl, and a selective antagonist, CTAP (d-Phe-Cys-Tyr-d-Trp-Arg-Thr-Pen-Thr-NH2). The coadministration of the selective AM receptor antagonist AM22-52 markedly attenuated the development of morphine tolerance, associated thermal hyperalgesia, and increase in AM-IR. A likely autocrine mechanism is supported by the finding that AM-IR is colocalized with AM receptor components in DRG neurons. Furthermore, opiate-induced increase in AM content was blocked by protein kinase C (PKC) inhibitors, whereas a PKC activator increased AM synthesis and release. A treatment with AM22-52 also inhibited increases in the expression of CGRP-IR in the spinal cord and DRGs as well as in culture ganglion explants, whereas exposure to CGRP failed to alter AM content. Together, these results reveal that a sustained opiate treatment induces an upregulation of AM through the activation of μ-opioid receptors and the PKC signaling pathway. This phenomenon contributes to the development of tolerance to the antinociceptive effects of opiates at least partially via the upregulation of CGRP. Targeting AM and its receptors should be considered as a novel approach to preserve the analgesic potency of opiates during their chronic use.
Clinical Outcomes and Prognosis of Recurrent Thymoma Management

Introduction: Clinical outcomes and prognosis of recurrent thymoma are not well known because of its rarity and indolent clinical course. This study was designed to determine the clinical outcomes and prognosis of recurrent thymoma. Methods: Between 1986 and 2009, 41 of 305 patients who underwent resection for thymoma had recurrence. We reviewed those patients retrospectively. Results: Of 15 patients who underwent re-resection for recurrent thymoma, 13 patients (87%) achieved complete re-resection. Of 26 patients who did not undergo re-resection, 11 patients received chemotherapy, five received chemoradiotherapy, one received another treatment, and nine patients did not receive any treatment. World Health Organization histological types AB or B1 and complete re-resection were positive prognostic factors. The complete re-resection group had better survival after recurrence than the non/incomplete re-resection group (5-year survival rate: 90.9% versus 44.7%, p = 0.014). The complete re-resection group had comparable survival after initial resection of thymoma to the patients without recurrence (5-year, 10-year survival: 91.7%, 91.7% versus 90.7%, 86.5%, p = 0.618) and better survival compared with the non/incomplete re-resection group (5-year, 10-year survival: 91.7%, 91.7% versus 81.6%, 56.7%, p = 0.018). Conclusions: World Health Organization histologic types AB or B1 and complete re-resection are favorable prognostic factors of recurrent thymoma. In particular, complete re-resection of recurrent thymoma contributes to better survival than other management. Therefore, we suggest that long-term surveillance extended at least 20 years may be essential for early detection of recurrence to increase the chance of complete re-resection of recurrent thymoma.
Application of Infrared Method for Water Detection in Karst Tunnel

Water rush and mud rush are two major problems during the process of tunnel construction, which can lead to big troubles. Advanced geological prediction should be carried out to prevent the emergency of water rush and mud rush during the construction in the karst and water-rich areas. Infrared detection technology is a way to detect the hidden water. In this paper, basic principles of model HY-304 infrared detection meter are described, and it is applied in Shuangbei Tunnel. By analyzing the predicted results and comparing it with the situation of excavation, the instrument is feasible as to water rush in karst areas and infrared detection technology has a great opportunity to be applied in the tunnel engineering under complex geological conditions.
Lower bounds for algebraic computation trees

A topological method is given for obtaining lower bounds for the height of algebraic computation trees, and algebraic decision trees. Using this method we are able to generalize, and present in a uniform and easy way, almost all the known nonlinear lower bounds for algebraic computations. Applying the method to decision trees we extend all the apparently known lower bounds for linear decision trees to bounded degree algebraic decision trees, thus answering the open questions raised by Steele and Yao [20]. We also show how this new method can be used to establish lower bounds on the complexity of constructions with ruler and compass in plane Euclidean geometry.
Dynamic adaptation of broad phase collision detection algorithms

In this paper we present a new technique to dynamically adapt the first step (broad phase) of the collision detection process on hardware architecture during simulation. Our approach enables to face the unpredictable evolution of the simulation scenario (this includes addition of complex objects, deletion, split into several objects, …). Our technique of dynamic adaptation is performed on sequential CPU, multi-core, single GPU and multi-GPU architectures. We propose to use off-line simulations to determine fields of optimal performance for broad phase algorithms and use them during in-line simulation. This is achieved by a features analysis of algorithmic performances on different architectures. In this way we ensure the real time adaptation of the broad-phase algorithm during the simulation, switching it to a more appropriate candidate. We also present a study on how graphics hardware parameters (number of cores, bandwidth, …) can influence algorithmic performance. The goal of this analysis is to know if it is possible to find a link between variations of algorithms performances and hardware parameters. We test and compare our model on 1, 2, 4 and 8 cores architectures and also on 1 Quadro FX 3600M, 2 Quadro FX 4600 and 4 Quadro FX 5800. Our results show that using this technique during the collision detection process provides better performance throughout the simulation and enables to face unpredictable scenarios evolution in large-scale virtual environments.
Public Policy for the Poor ? A Randomized Ten-Month Evaluation of the Mexican Universal Health Insurance Program

7 Conestadistica 2 Abstract Background In what may be the largest randomized health policy experiment to date, we evaluate aspects of Seguro Popular, a program to deliver health insurance, regular and preventive medical care, pharmaceuticals, and health facilities to 50 million uninsured Mexicans. Methods We randomized treatment within 74 matched pairs of " health clusters'' (health facility catchment areas) representing 118,569 households in 7 states, and measured outcomes in a Summer 2005 baseline survey and follow-up survey 10 months later in 50 pairs (n = 32,515). Treatment included encouragement to enroll and health insurance. Participant states also received funds to improve health facilities and to provide medications for services in treated clusters. We estimated intent-to-treat (ITT) and complier average causal effects (CACE) nonparametrically. Findings ITT estimates indicate a reduction in catastrophic expenditures by 1.9 percentage points (95% CI 0.14–3.66), a 22.6% reduction from baseline. The effect among poorer households was 3.0 points (95% CI 0.46–5.54) and among experimental compliers was 6. Contrary to expectations and prior observational research, we found no effects on medication spending, health outcomes, or utilization. Interpretation Program resources reached the poor. We failed to detect some other positive effects from the program, possibly due to the short treatment period. Further experimentation and follow up should continue to ascertain the program's ultimate effects. [Words: 249] 3 Introduction Health system reforms often fail to provide the poor with access to quality care
Extinction performance of superfine graphite smoke to 10.6 μm laser emission

The mass extinction coefficient of superfine graphite smoke to 10. 6μm laser emission produced by CO2 gas laser and the granularity distribution of the smoke particles at different time have been tested in a middle-size smoke chamber. The absorption, scattering and extinction efficiency factors of graphite smoke with different diameters to 10. 6μm laser emission have been calculated according to Mie scattering theory and the curves of extinction factors varied with wavelength or particle diameter have been drawn too. Experimental results have shown that the superfine graphite smoke has a good extinction performance to 10. 6μm laser emission and that the average mass extinction coefficient of the smoke to 10. 6μm laser emission is 1.214m2/g. By the analysis, the optimal scattering diameter of graphite smoke to 10. 6μm laser emission is 9μm while the optimal absorption diameter is 2. 0μm and the optimal extinction diameter is 3. 0μm. If the scattering diameter of the graphite smoke is smaller than the wavelength of incident laser emission, the extinction effect is dependent on the absorption. The scattering function increases with the enlargement of smoke particle diameter. In addition, the superfine graphite is difficult to effectively diffuse and form a thick concentration in air. The average diameter of graphite smoke particles gradually decreases with the time increment after forming the smoke.
A 400 MHz Wireless Neural Signal Processing IC With 625 × On-Chip Data Reduction and Reconfigurable BFSK / QPSK Transmitter Based on Sequential Injection Locking

An 8-channel wireless neural signal processing IC, which can perform real-time spike detection, alignment, and feature extraction, and wireless data transmission is proposed. A reconfigurable BFSK/QPSK transmitter (TX) at MICS/MedRadio band is incorporated to support different data rate requirement. By using an Exponential Component-Polynomial Component (ECPC) spike processing unit with an incremental principal component analysis (IPCA) engine, the detection of neural spikes with poor SNR is possible while achieving 625× data reduction. For the TX, a dual-channel at 401 MHz and 403.8 MHz are supported by applying sequential injection locked techniques while attaining phase noise of −102 dBc/Hz at 100 kHz offset. From the measurement, error vector magnitude (EVM) of 4.60%/9.55% with power amplifier (PA) output power of −15 dBm is achieved for the QPSK at 8 Mbps and the BFSK at 12.5 kbps. Fabricated in 65 nm CMOS with an active area of 1 mm2 , the design consumes a total current of 5∼5.6 mA with a maximum energy efficiency of 0.7 nJ/b.
Knowledge transfer in learning to recognize visual objects classes

— Learning to recognize of object classes is one of the most important functionalities of vision. It is estimated that humans are able to learn tens of thousands of visual categories in their life. Given the photometric and geometric variabilities displayed by objects as well as the high degree of intra-class variabilities, we hypothesize that humans achieve such a feat by using knowledge and information cumulated throughout the learning process. In recent years, a handful of pioneering papers have applied various forms of knowledge transfer algorithms to the problem of learning object classes. We ﬁrst review some of these papers by loosely grouping them into three categories: transfer through prior parameters, transfer through shared features or parts, and transfer through contextual information. In the second half of the paper, we detail a recent algorithm proposed by the author. This incremental learning scheme uses information from object classes previously learned in the form of prior models to train a new object class model. Training images can be presented in an incremental way. We present experimental results tested with this model on a large number of object categories.
Colour Constancy: Biologically-inspired Contrast Variant Pooling Mechanism

Pooling is a ubiquitous operation in image processing algorithms that allows for higher-level processes to collect relevant low-level features from a region of interest. Currently, max-pooling is one of the most commonly used operators in the computational literature. However, it can lack robustness to outliers due to the fact that it relies merely on the peak of a function. Pooling mechanisms are also present in the primate visual cortex where neurons of higher cortical areas pool signals from lower ones. The receptive fields of these neurons have been shown to vary according to the contrast by aggregating signals over a larger region in the presence of low contrast stimuli. We hypothesise that this contrast-variant-pooling mechanism can address some of the shortcomings of max-pooling. We modelled this contrast variation through a histogram clipping in which the percentage of pooled signal is inversely proportional to the local contrast of an image. We tested our hypothesis by applying it to the phenomenon of colour constancy where a number of popular algorithms utilise a max-pooling step (e.g. White-Patch, Grey-Edge and Double-Opponency). For each of these methods, we investigated the consequences of replacing their original max-pooling by the proposed contrast-variant-pooling. Our experiments on three colour constancy benchmark datasets suggest that previous results can significantly improve by adopting a contrast-variant-pooling mechanism.
Identifying user attributes through non-i.i.d. multi-instance learning

User attribute is an essential factor for personalized recommendation and targeted advertising. Therefore, there have been a number of studies to identify user attributes automatically from SNS postings, since the postings reveal various attributes of writers. Many kinds of machine learning methods have been applied to automatic identification of user attributes as a candidate solution, but they suffer from two major problems. First, there are many postings in SNS that do not deliver any information about writers. Then, learning from SNS postings results in a biased model by these irrelevant postings. Second, the postings of a SNS user are somewhat related one another. However, most machine learning methods ignore this information, since they assume that data are independently and identically distributed. In order to solve these problems in user attribute identification, this paper proposes a novel method based on non-i.i. d. multi-instance learning. Since multi-instance learning treats all postings by a user as a bag and learns user attribute identification with such bags, not with postings, the first problem is solved. In addition, the proposed method assumes that the postings by a single user have a structure. By incorporating this assumption into the multi-instance learning, the second problem is solved. Our experimental results show that consideration of these two problems in automatic user attribute identification results in performance improvement.
Dry release of metal structures in oxygen plasma: process characterization and optimization

A surface micromachining fabrication scheme suitable for fabrication of free-standing metallic structures is presented. The technique is based on using conventional photoresist as a sacrificial layer, on which a metal structural layer is evaporated and patterned. The resulting structures are subsequently dry released in an isotropic oxygen plasma. For the HPR504 and HiPR6517 photoresists, a lateral underetching rate (at a power of 1000 W) of up to 1 was obtained. Structures with lateral dimensions of at least up to can be released as no etch-rate saturation for underetching beyond 20 m was observed. The process has been tested using Al as a structural layer, but any metal that can be evaporated or sputtered can be used. The presented dry-release technique is fully compatible with standard silicon IC processing and can be applied as a post-processing module. The technique eliminates any sticking problem and simplifies processing as compared to wet-etching release.
Providing Support for Legacy IPv4 Applications in IPv6 Network with Network Aware Mobility

In the past years there has been substantial amount of research focused on the transition mechanisms to allow the Internet to gradually evolve into a fully fledged IPv6 network. With the prevalence of smartphones, internet tablets and netbooks, a large portion of the end users has become truly mobile. Now, that all of the remaining IPv4 addresses have been allocated, the transition from IPv4 to IPv6 is becoming reality also for the mobility management. In this paper we examine the mobility aspect of the transition using real world measurements with a tunneling based transition scheme on our network aware Mobile IPv6 testbed.
A high voltage split source voltage multiplier with increased output voltage

Building on the Half-Wave Cockcroft-Walton voltage multiplier, a topology is proposed that consists of several voltage multiplying sections fed separately at their inputs and whose output voltages are summated across the load. The proposed topology can attain over m times higher voltage gain (m being the splitting level). The theory is supported by simulations and experiments. For instance, in a simple experiment, the load voltage has increased from 2.8 kV to 6.6 kV due to splitting the circuit into 3 sections (m=3).
Impact of Personal Software Process on Software Quality

Today, concern for quality has become an international movement. Even though most industrial organizations have now adopted modern quality principles, the software community has continued to rely on testing as the principal quality management method. Different decades have different trends in software engineering. The Personal Software Process (PSP) is an evolutionary series of personal software engineering techniques that an engineer learns and practices. A software process is nothing without the individual programmer. PSP a datadriven process customized to teaching individuals about their programming styles, helping software engineers further develop their skills in developing quality software. In this paper I explain the Personal Software Process definition, principles, design, advantages and opportunities apart from discussing about PSP as a framework of techniques to help engineers and their organizations improve their performance while simultaneously increasing product quality focusing on the incorporation of PSP concepts in software development practice.
Trade Finance and the Great Trade Collapse

Economic models that do not incorporate financial frictions only explain about 70 to 80 percent of the decline in world trade that occurred in the 2008-2009 crisis. We review evidence that shows financial factors also contributed to the great trade collapse and uncover two new stylized facts in support of it. First, we show that the prices of manufactured exports rose relative to domestic prices during the crisis. Second, we show that US seaborne exports and imports, which are likely to be more sensitive to trade finance problems, saw their prices rise relative to goods shipped by air or land.
Rheotens‐mastercurves and drawability of polymer melts

In a Rheotens experiment, the tensile force needed for elongation of an extruded filament is measured as a function of the draw ratio. For thermo-rheologically simple polymer melts, the existence of Rheotens-mastercurves is proven. Rheotens-mastercurves are invariant with respect to changes in melt temperature. Also, for polymer melts with different average molar masses, but similar molar mass distribution and branching structure, Rheotens-mastercurves are invariant to changes in the average molar mass. It is shown, by testing several polyethylenes with different molar mass distribution and different long-chain branching, that Rheotens-mastercurves allow a direct and quantitative assessment of the drawability of polymer melts under actual processing conditions, i.e. under the action of a constant tensile force and including the effects of the rheological prehistory in the extrusion die.