Miracle-dz/UniFAR-FTUs huggingface dataset:
Controlling user interface objects through pre- and postconditions

We have augmented user interface objects (i.e. windows, menus, buttons, sliders, ets.) with preconditions that determine their visibility and their enabled/disabled status and postconditions that are asserted when certain actions are performed on the object. Postconditions are associated with each functionally different action on the object. Attaching pre- and postconditions to interface objects provides several useful features, such as selective enabling of controls, rapid prototyping, and automatic generation of explanations and help text.
165 FACTORS AFFECTING KNOWLEDGE SHARING IN PUBLIC ORGANIZATIONS IN MALAYSIA

Knowledge sharing is an inevitable activity that underpins the business of knowledge management. It is a crucial activity since knowledge bears no value if it is not distributed and shared. However, the question of whether knowledge sharing does really exist in public organizations and factors affecting the practice are yet to be known. This paper reviews other research in the area in order to determine factors that affect knowledge sharing in the public sector in Malaysia. Synthesizing from the literature, this paper proposes a theoretical framework that takes into consideration the individual, organizational and technological dimensions that might affect knowledge sharing in Malaysia public sector.
A 3-Lead ECG-on-Chip with QRS Detection and Lossless Compression for Wireless Sensors

This brief presents the design of a low-power 3-lead electrocardiogram (ECG)-on-chip with integrated real-time QRS detection and lossless data compression for wearable wireless ECG sensors. Data compression and QRS detection can reduce the sensor power by up to 2-5 times. A joint QRS detection and lossless data compression circuit allows computational resources to be shared among multiple functions, thus lowering the overall system power. The proposed technique achieves an average compression ratio of 2.15 times on standard test data. The QRS detector achieves a sensitivity (Se) of 99.58% and positive productivity (+P) of 99.57% @ 256 Hz when tested with the MIT/BIH database. Implemented in 0.35 μm process, the circuit consumes 0.96 μW @ 2.4 V with a core area of 1.56 mm2 for two-channel ECG compression and QRS detection. Small size and ultralow-power consumption makes the chip suitable for usage in wearable/ambulatory ECG sensors.
Drug Discovery Using Support Vector Machines. The Case Studies of Drug-likeness, Agrochemical-likeness, and Enzyme Inhibition Predictions

Support Vector Machines (SVM) is a powerful classification and regression tool that is becoming increasingly popular in various machine learning applications. We tested the ability of SVM, in comparison with well-known neural network techniques, to predict drug-likeness and agrochemical-likeness for large compound collections. For both kinds of data, SVM outperforms various neural networks using the same set of descriptors. We also used SVM for estimating the activity of Carbonic Anhydrase II (CA II) enzyme inhibitors and found that the prediction quality of our SVM model is better than that reported earlier for conventional QSAR. Model characteristics and data set features were studied in detail.
Large-Scale Features of the Novorossiysk Bora

On the basis of the reanalysis data with high spatial resolution and 36 years temporal coverage the spatial structure of wind speed and temperature fields in the Black Sea region for bora events in winter months was assessed. It is shown that bora development is followed by a formation of large-scale cyclonic circulation in the southeast part of the Black Sea. The airflow of the northwest edge of high Caucasus Mountains leads to the wind speed cyclonic vorticity over the sea; high Anatolian mountains block propagation of the air flows to the south and, thus, they jointly form a large-scale closed circulation cell. Regression dependences between the wind speed and temperature in Novorossiysk region are studied; they show that in winter strong northeast winds correspond to frontal-type bora activity which is accompanied by the air temperature decrease. The important feature of the temperature field during bora is revealed at that: temperature in the sea coastal area exceeds the one in the mainland foothill part of the region. For studying the physical mechanism of this phenomenon the atmospheric circulation computation (using WRF-ARW model) for specific Novorossiysk region bora event, which provided a detailed consideration of vertical structure components of wind speed and potential temperature in the coastal zone, above the sea, above the mountains and in the foothill mainland of the region, was carried out. It is shown that the mechanism of higher temperature formation in the sea coastal area is related to the air blocking above the windward slope of the mountain ridge and its replacement with warmer air from the upper layers of the atmosphere at the leeward slope.
Global software development

Introduction Global Software Development (GSD) is increasingly becoming the normal practice in the software industry, readily evidenced by U.S. estimates that the value of the offshore software development market has increased 25-fold over the past 10 years, to the extent that one-quarter of U.S. spending on application development, integration and management services is expected to go off-shore according to recent predictions. There are many potential benefits that can arise from GSD. The most frequently cited one is that of reduced development costs due to the salary savings possible. Also, GSD can lead to reduced development duration due to greater time zone effectiveness as companies practice the so-called 'follow-the-sun' software development model. GSD also affords new opportunities for cross-site modularization of development work, potential access to a larger and better-skilled developer pool, and the possibility of greater innovation, learning and transfer of best practices. Finally, GSD can facilitate closer proximity to markets and customers. However, GSD also introduces a number of challenges in relation to communication, coordination and control of the development process. These arise due to the distances involved in three dimensions -- geographical, temporal, and socio-cultural (See Figure 1). As a consequence, much research and practice has focused on trying to find ways to overcome the GSD challenges identified in Figure 1. In the literature to date, the potential benefits of GSD are usually just mentioned very briefly, if they are mentioned at all, and the realization of these benefits seems to be more or less taken for granted. The primary focus instead is on how the problems inherent in GSD might be addressed. Here, we reverse this trend and focus instead on the benefits and the extent to which they are actually being realized in practice in three global companies practicing GSD.
Geochemical constraints on the origin of sulfide mineralization in the Duke Island Complex, southeastern Alaska

Magmatic Cu‐Ni‐PGE sulfide mineralization associated with mafic to ultramafic igneous rocks is rare in convergent plate settings. However, recent exploration in the Duke Island Complex of southeastern Alaska has detected horizons of sulfide mineralization primarily in the olivine clinopyroxenite unit. The composition of the sulfides, recalculated to 100% sulfide, averages 0.48% Ni and 1.4% Cu. The Duke Island Complex was generated by the emplacement of multiple pulses of variably fractionated magma ranging in composition from picrite to ankaramite that originated in deeper staging chambers. The presence of sulfides in the complex indicates that fO2 conditions were more reduced than those commonly ascribed to arc‐related magmas. The mass of sulfide mineralization together with the sulfur isotopic values indicates that external sulfur was added to the parent magmas at staging chambers. Os isotopic data from sulfides and C isotopic compositions of graphite in the olivine clinopyroxenites also indicate that the parental magmas were contaminated by crustal material. However, oxygen isotopic values of clinopyroxene together with the REE data suggest that bulk assimilation of country rocks has not occurred and the contamination was selective, involving C‐ and S‐bearing fluids or graphitic sulfides. The observed enrichment in Cu and S isotopic values of the sulfides is best explained by assimilation of sulfides from metal‐bearing rock types such as black shales or volcanogenic massive sulfide deposits that occur in terranes above the mantle wedge.
In vivo epigenetic effects induced by engineered nanomaterials: A case study of copper oxide and laser printer-emitted engineered nanoparticles

Abstract Evidence continues to grow on potential environmental health hazards associated with engineered nanomaterials (ENMs). While the geno- and cytotoxic effects of ENMs have been investigated, their potential to target the epigenome remains largely unknown. The aim of this study is two-fold: 1) determining whether or not industry relevant ENMs can affect the epigenome in vivo and 2) validating a recently developed in vitro epigenetic screening platform for inhaled ENMs. Laser printer-emitted engineered nanoparticles (PEPs) released from nano-enabled toners during consumer use and copper oxide (CuO) were chosen since these particles induced significant epigenetic changes in a recent in vitro companion study. In this study, the epigenetic alterations in lung tissue, alveolar macrophages and peripheral blood from intratracheally instilled mice were evaluated. The methylation of global DNA and transposable elements (TEs), the expression of the DNA methylation machinery and TEs, in addition to general toxicological effects in the lung were assessed. CuO exhibited higher cell-damaging potential to the lung, while PEPs showed a greater ability to target the epigenome. Alterations in the methylation status of global DNA and TEs, and expression of TEs and DNA machinery in mouse lung were observed after exposure to CuO and PEPs. Additionally, epigenetic changes were detected in the peripheral blood after PEPs exposure. Altogether, CuO and PEPs can induce epigenetic alterations in a mouse experimental model, which in turn confirms that the recently developed in vitro epigenetic platform using macrophage and epithelial cell lines can be successfully utilized in the epigenetic screening of ENMs.
Formulation of the line voltage THD, case I: Multilevel inverter with equal DC sources

A new generation of DC to AC inverters which is called Multilevel Inverter, has many industrial applications, especially in high-voltage and high-power. In spite of nearly sinusoidal waveform, multilevel inverters produce noticeable harmonic content. THD is normally used as a benchmark to evaluate harmonic contents. THD is one of important factors to produce losses in devices such as induction motors, transformers and etc. Also the Losses play an important role in determining the size of distribution cables, so calculation of the exact amount of THD is important. In previous studies, a formula to calculate exact THD of phase voltage has been emerged for multilevel inverter with equal DC sources. In this paper, line to line voltage THD formula for 3 and 5-level inverter instead of the past approximate methods is offered. For writing codes and simulations MATLAB software is used.
A linear assisted DC/DC converter for Envelope Tracking and Envelope Elimination and Restoration applications

In recent years, there has been a great effort in the development of fast and efficient DC/DC converters in order to follow the envelope of communication signals for increasing the efficiency of Radio Frequency Power Amplifiers by using techniques such as Envelope Tracking and Envelope Elimination and Restoration. However the bandwidth and slew rate required by modern communication signals is higher than the maximum slew-rate achievable by switching DC/DC converters made for these purpose. The slew rate of these switching DC/DC converter can be improved by combining it with the use of a linear stage, thus establishing a trade-off between slew rate and overall efficiency. This paper presents a simple way of combining the use of both a switching DC/DC converter, the Multiple Input Buck Converter, and a linear stage to obtain slew-rates above 100 V/µs, with a moderate decrease in the overall efficiency (81% efficiency tracking the envelope of an EDGE standard signal). Finally, a prototype of the complete system (including the digital control for both stages) is presented in this paper.
Emodin Suppresses Migration and Invasion through the Modulation of CXCR4 Expression in an Orthotopic Model of Human Hepatocellular Carcinoma

Accumulating evidence(s) indicate that CXCL12-CXCR4 signaling cascade plays an important role in the process of invasion and metastasis that accounts for more than 80% of deaths in hepatocellular carcinoma (HCC) patients. Thus, identification of novel agents that can downregulate CXCR4 expression and its associated functions have a great potential in the treatment of metastatic HCC. In the present report, we investigated an anthraquinone derivative, emodin for its ability to affect CXCR4 expression as well as function in HCC cells. We observed that emodin downregulated the expression of CXCR4 in a dose-and time-dependent manner in HCC cells. Treatment with pharmacological proteasome and lysosomal inhibitors did not have substantial effect on emodin-induced decrease in CXCR4 expression. When investigated for the molecular mechanism(s), it was observed that the suppression of CXCR4 expression was due to downregulation of mRNA expression, inhibition of NF-κB activation, and abrogation of chromatin immunoprecipitation activity. Inhibition of CXCR4 expression by emodin further correlated with the suppression of CXCL12-induced migration and invasion in HCC cell lines. In addition, emodin treatment significantly suppressed metastasis to the lungs in an orthotopic HCC mice model and CXCR4 expression in tumor tissues. Overall, our results show that emodin exerts its anti-metastatic effect through the downregulation of CXCR4 expression and thus has the potential for the treatment of HCC.
Machine learning to estimate soil moisture from geophysical measurements of electrical conductivity

ABSTRACT Soil water content (θ) is a key variable in different earth science disciplines since it mediates the water and energy exchange between the surface and atmosphere. Electrical and electromagnetic geophysical techniques have been widely used to estimate soil electrical conductivity (σ) and soil moisture. However, obtaining the σ−θ relationship is not straightforward due to the non‐linearity and also dependency on many different soil and environmental properties. The purpose of this paper is to determine if artificial neural network is an appropriate machine learning technique for relating electrical conductivity to soil water content. In this respect, time‐lapse electrical resistivity tomography measurements were carried out along a transect in the Chicken Creek catchment (Brandenburg, Germany). To ensure proper retrieval of the σ and θ, reference values were measured near the beginning of the transect via an excavated pit using 5TE capacitance sensors installed at different depths. We explored robustness and pertinence of the artificial neural network approach in comparison with Rhoades model (as a commonly used petrophysical relationship) to convert the inversely estimated σ from electrical resistivity tomography to the θ. The proposed approach was successfully validated and benchmarked by comparing the estimated values with the reference data. This study showed the superiority of the artificial neural network approach to the Rhoades model to obtain σ−θ relationship. In particular, artificial neural network allowed for more accurate estimation of the temporal wetting front than the petrophysical model. The proposed methodology thus offers a great promise for deriving spatiotemporal soil moisture patterns from geophysical data and obtaining the in situσ−θ relationship, taking into account the non‐linear variations of the soil moisture.
Spatial multi criteria approach for tsunami risk assessment

Tsunami risk is defined as mathematical product between vulnerability and hazard. Tsunami risk also refers to the estimated loss from a given hazard to a given element at risk, and it is defined as a combination of tsunami hazard, tsunami vulnerability, exposure, and event probability. Besides tsunami vulnerability, tsunami risk is assessed by a number of criteria. This study applies the combination of element at risk to assess tsunami risk area along coastal area of East Java Indonesia. The study introduces the spatial multi-criteria analysis into tsunami risk assessment along with the existing perspective evolving the role of GIS. In this study, the existing vulnerability parameter was analysed and evaluated. The analysis was done using GIS-based spatial multi criteria approach. All parameter were analysed through weighted overlay using analytical hierarchy process and geospatial analysis. The results are provided as thematic maps of tsunami vulnerability map and tsunami risk map. Tsunami risk maps as a result from this study illustrate five levels of risk from very low to very high based on geospatial analysis. It describes that coastal area with low elevation was at high risk to tsunami, similar to that indicated in tsunami vulnerability map. Coastal area with high density of vegetation describes a low level tsunami risk. The existence of river and other water stream along coastal area are also important parameters in generating tsunami risk map. Risk map highlights the coastal areas with a strong need for evacuation capacities, including evacuation route and evacuation building.
Localized matrix factorization for recommendation based on matrix block diagonal forms

Matrix factorization on user-item rating matrices has achieved significant success in collaborative filtering based recommendation tasks. However, it also encounters the problems of data sparsity and scalability when applied in real-world recommender systems. In this paper, we present the Localized Matrix Factorization (LMF) framework, which attempts to meet the challenges of sparsity and scalability by factorizing Block Diagonal Form (BDF) matrices. In the LMF framework, a large sparse matrix is first transformed into Recursive Bordered Block Diagonal Form (RBBDF), which is an intuitionally interpretable structure for user-item rating matrices. Smaller and denser submatrices are then extracted from this RBBDF matrix to construct a BDF matrix for more effective collaborative prediction. We show formally that the LMF framework is suitable for matrix factorization and that any decomposable matrix factorization algorithm can be integrated into this framework. It has the potential to improve prediction accuracy by factorizing smaller and denser submatrices independently, which is also suitable for parallelization and contributes to system scalability at the same time. Experimental results based on a number of real-world public-access benchmarks show the effectiveness and efficiency of the proposed LMF framework.
Detecting Emotions in Mandarin Speech

The importance of automatically recognizing emotions in human speech has grown with the increasing role of spoken language interfaces in human-computer interaction applications. In this paper, a Mandarin speech based emotion classification method is presented. Five primary human emotions, including anger, boredom, happiness, neutral and sadness, are investigated. Combining different feature streams to obtain a more accurate result is a well-known statistical technique. For speech emotion recognition, we combined 16 LPC coefficients, 12 LPCC components, 16 LFPC components, 16 PLP coefficients, 20 MFCC components and jitter as the basic features to form the feature vector. Two corpora were employed. The recognizer presented in this paper is based on three classification techniques: LDA, K-NN and HMMs. Results show that the selected features are robust and effective for the emotion recognition in the valence and arousal dimensions of the two corpora. Using the HMMs emotion classification method, an average accuracy of 88.7% was achieved.
Analytical solutions for optimal photon absorption into inhomogeneous spin memories

We investigate for optimal photon absorption a quantum electrodynamical model of an inhomogeneously-broadened spin ensemble coupled to a single-mode cavity. We consider a one-photon input pulse and obtain a simple one-parameter form for its optimal shape for absorption in the spin ensemble. Solutions to this problem are developed without using perturbation theory concerning the spin ensemble. Furthermore, we exploit the possibility of modulating the frequency and coupling rate of the resonator. We show some optimal scenarios and demonstrate the usefulness of our approach for the design of efficient quantum memories. In particular, we find the optimal cooperativity for different parameters and identify cases where absorption with a success probability larger than $99\%$ is achieved.
Open-Ended Coaxial Waveguide for Conical-Beam Radiation

This communication demonstrates that an open-ended coaxial waveguide can be a good aperture antenna for generating conical-beam radiation. Design equations are derived to obtain the radii of inner and outer conductors of a coaxial waveguide radiating into a half free space. A design example is provided to verify the design concept and derived equations. Simulated and measured results of a fabricated aperture antenna are presented and compared to demonstrate its conical-beam radiation performance.
Activation of Rad53 kinase in response to DNA damage and its effect in modulating phosphorylation of the lagging strand DNA polymerase

The Saccharomyces cerevisiae Rad53 protein kinase is required for the execution of checkpoint arrest at multiple stages of the cell cycle. We found that Rad53 autophosphorylation activity depends on in trans phosphorylation mediated by Mec1 and does not require physical association with other proteins. Uncoupling in trans phosphorylation from autophosphorylation using a rad53 kinase‐defective mutant results in a dominant‐negative checkpoint defect. Activation of Rad53 in response to DNA damage in G1 requires the Rad9, Mec3, Ddc1, Rad17 and Rad24 checkpoint factors, while this dependence is greatly reduced in S phase cells. Furthermore, during recovery from checkpoint activation, Rad53 activity decreases through a process that does not require protein synthesis. We also found that Rad53 modulates the lagging strand replication apparatus by controlling phosphorylation of the DNA polymerase α‐primase complex in response to intra‐S DNA damage.
Idea Inheritance, Originality, and Collective Innovation

In order to create new products, inventors search and combine previous ideas. Few studies have examined the characteristics of search that lead to new products; most have focused on patent citations, which are often retrospective and may not reflect the usefulness of inventions.Through the analysis of collaborations in an online virtual community, the impact of originality on popularity and practicality is tested. These tests in turn are based on a method for measuring the distance between 3D shapes. In sum, this paper presents a new method for gauging innovation, and suggests ways of further understanding the role technology plays in encouraging creativity. From an organization perspective, this work provides insights into the creative process, and in particular the open innovation process, in which thousands of individuals together evolve designs, without belonging to the same corporate structure, without claiming IP rights, without exchanging money.