Miracle-dz/UniFAR-FTUs huggingface dataset:
IONIC LIQUID ASSISTED THE PREPARATION OF ANATASE TiO 2 WITH HIGH SURFACE AREA AND POROUS STRUCTURE

The porous anatase TiO2 with high surface area and uniform pore structure were synthesized at low temperature and ambient pressure with tetrabutyl titanate as precursor, ionic liquid [C6mim]Br as template. The obtained materials were characterized by Fourier transform (FT-IR) spectra, energy dispersive X-ray (EDX) spectroscopy, powder X-ray diffraction (XRD), Brunauer-Emmett-Teller (BET), scanning electron microscopy (SEM) and transmission electron micrographs (TEM). The results showed that the ionic liquid [C6mim]Br, as a effective template, encouraged the formation of anatase crystal by sol-gel method, meanwhile the anatase TiO2 formed high surface area and porous structure. Furthermore, it enhanced the photocatalytic activity in the degradation of reactive brilliant blue KN-R (RBB).
Uncovering theMechanisms ofAffectiveBiases inPerception

The emotional significance of sensory events may influence attention in a reflexive manner, but these effects vary across paradigms and participants. Recent research indicates that specific circuits in the brain may serve to amplify neural responses to emotional stimuli, a modulation similar to attentional effects usually driven by endogenous goals. However, this modulation involves distinct sources in emotional systems such as the amygdala, and may thus operate partly independent of top-down control by attentional systems in frontoparietal cortices. It remains to be clarified to what degree these emotional effects are influenced by specific perceptual and emotional dimensions, automaticity and attentional resources, task goals or expectations, and individual personality traits.
Towards Systemic Evaluation of the Business Value of IT

Evaluating the IT business value is a challenging combination of managing the complexity of value phenomenon and the complexity of broad IT impacts. This study analyses the focal characteristics of IT business value evaluation and proposes a research agenda towards systemic evaluation approach. The systemic approach combines concepts of goal driven perspective for benefits, value as a combination of benefits and costs, and the lifecycle view of potential and realised value. These concepts are integrated through system dynamics modelling to understand the IT impact structures and dynamic value creating behaviour emerging from the structures. Finally, systemic approach should be supported by evaluation workflow practices that facilitate seamless data retrieval for the evaluation process, and the integration of evaluation outputs within the organisation.
Precarious or Decent Work? Perceived Working Conditions and Life Satisfaction of SME Workers in Sylhet, Bangladesh

This study measures key indicators of perceived precarity and decent working conditions and their relative effects on life satisfaction of workers in small and medium-sized enterprises. Using a random sample survey, we interviewed 103 workers in four districts of Sylhet division in Bangladesh. Utilizing Smart PLS application for structural equation modeling, we iterated the samples 1000 times which resulted in a new sample size standing at 499. We used a Likert-type five-point scaling technique, with appropriate items related to the latent constructs of the model, for path analysis. We found perceived precariousness has the highest causal relations with a path coefficient of 0.706 with social dialogue (an indicator of decent working conditions) followed by 0.539 with working hour issue, 0.345 with life satisfaction and 0.301 with the unacceptable work issue. The importance-performance map analysis confirms that perceived precarity is the most critical construct for worker’s life satisfaction. Thus, in a ceteris paribus situation, an increase of one point in the performance on the perceived precarity is expected to increase in the performance on the life satisfaction by a total effect level of 0.428. Therefore, we recommend further attention should be paid by the policymakers to the issue of consciousness of the precarity at the workplace for a better life satisfaction of workers.
Geometrical Detection Algorithm for MIMO Systems

The channel capacity and error-rate performance of MIMO systems could be improved by increasing the number of transmit antennas and receive antennas and the size of constellation used for modulation (Foschini and Gans, 1998). A main bottleneck that restricts the practical application of MIMO system is the unsatisfactory performance of the decoding algorithms, due to either high computational complexity required or poor symbol error-rate (SER) performance. Maximum-likelihood (ML) decoding which employs an exhaustive search strategy under the minimum Euclidean-distance principle can exploit all the available diversity and provide the optimum SER performance. However, its complexity increases exponentially with the number of antennas and the size of constellation used. Thus, for many cases, it is impractical to implement. Several sub-optimum decoding algorithms such as equalization-based zero-forcing (ZF) and minimum-mean-square-error (MMSE) detectors and nulling-and-cancelling detectors (NC) have been proposed for MIMO systems (Paulraj, Nabar and Gore, 2003). Although their computation complexities are dramatically less, these decoding algorithms have severe degradations in SER performances. Sphere decoding (SD) (Viterbo and Boutros, 1999) is another search-based algorithm. Unlike the exhaustive search engaged in ML decoding, SD confines the searching zone to be inside some hyper sphere constructed in the space spanned by the received lattice points. It can offer optimum SER performance with reasonable complexity. Several searching strategies such as Fincke-Pohst (Fincke and Pohst, 1985) and Schnorr-Euchner (Schnorr and Euchner, 1994) have been developed to further improve the searching efficiency in SD. Since the minimum Euclidean-distance principle could result in an optimum SER performance, the purpose of this chapter is to introduce another perspective of reconsidering this principle from the transmit lattice space. In the space spanned by the transmit lattice points, the Euclidean distance in ML decoding is found to be related to a series of concentric hyper ellipsoids. Searching the lattice point with the minimum Euclidean distance from the received signal vector is equivalent to searching the lattice point that is passed through by the smallest hyper ellipsoid. Decoding algorithms following this perspective are often called geometrical detection (Artes, Seethaler and Hlawatsch, 2003). In this Chapter, the geometrical analysis of signal decoding for MIMO channels is presented. Then, the ellipsoid searching decoding algorithm (Shao, Cheung and Yuk, 2009) is described. It is an add-on detection algorithm to standard suboptimal detection schemes
Three-Layer Composite Coding for Index Coding

We extend the composite coding (CC) scheme for the index coding problem from two layers to more layers of random binning. We explicitly introduce the three-layer composite coding (TLCC) scheme and provide the achievable rate region and the error analysis for it. We present a concrete non-trivial example with $n = 7$ messages where the TLCC strictly outperforms the CC scheme. We also present a number of simplification methods for the TLCC scheme towards better understanding of the scheme, as well as significantly reducing its computational complexity. We further prove that even a simplified version of the TLCC, which can be possibly weaker than the TLCC, still subsumes the CC scheme.
Using Sediment Particle Size Class Analysis to Better Understand Urban Land-Use Effects

A nested-scale experimental watershed study design was used to demonstrate rainfall-runoff and sediment particle size class variability in a representative urbanizing watershed in central Missouri, USA. On average, sediment particle size classes were almost twice as large (2.0 to 500µm size range) in headwaters, relative to an urban setting. Eighty percent of total sediment in the headwaters was between 216 and 357 µm but only 40% in the urban setting. A 13.2 mm rainfall event resulted in a doubling of streamflow 1.4 m 3 /s to 2.9 m 3 /s but resulted in more than quadrupling the concentration of particle size classes ranging from 0.2 to 67.65 μm. Results illustrates the need to better understand fine particle suspended sediment concentrations in surface runoff from urbanizing systems relative to that flowing from agricultural and/or forest environments. Future work holds important implications for understanding the effects of urbanization on sediment loading, aquatic ecosystem health, and water quality.
Human Action Recognition Based on Dense Sampling of Motion Boundary and Histogram of Motion Gradient

In order to realize accurate recognition of human action, feature expression of motion information is a very crucial step. Aiming at the problem that the dense sampling used for action recognition will be affected by interference factors, such as camera motion and background information redundancy, this paper proposes the human action recognition method based on dense sampling of motion boundary and motion gradient histogram. Firstly, the dense sampling strategy based on motion boundary is incorporated into the improved dense sampling to eliminate a large number of invalid sampling points and reduce the number of trajectories. Next, in order to fully excavate the internal relationship of human movement between time and space, histograms of motion gradients based on time and space derivation is introduced to capture motion information in video, which is integrated with dense features to enhance the feature expression. The experiment results on two challenging datasets show that the proposed method improves the human action recognition accuracy effectively in the case of accelerating the speed of algorithm.
Feature engineering in big data for detection of information systems misuse

The increasing availability of very large volumes of digital data (i.e. Big Data) enables many interesting research streams on a wide variety of phenomena. However, there has been a paucity of Big Data sets in the area of cybersecurity in information systems, as organizations are reluctant to share data that may provide too much unrestricted visibility into their operations. In this study, we explore the use of a real-life, anonymized, very large dataset containing user behavior – as captured in log files – including both regular usage as well as misuse, typifying the dynamics found in a situation with compromised user credentials. Through the experiment, we validate that the existence of a large user behavior dataset in itself does not necessarily guarantee that abnormal behaviors can be found. It is essential that researchers apply deep domain knowledge, critical thinking and practical focus to ensure the data can produce the knowledge required for the ultimate objective of detecting an insider’s threat. In this paper we develop, formulate and calculate the features that best represent user behavior in the underlying information systems, maintaining a parsimonious balance between complexity, resource demands and detection effectiveness. We test the use of a classification model that proves the usefulness and aplicability of the features extracted.
Secondary Schools Principals and Their Job Satisfaction: A Test of Process Theories.

The study aims to test the validity of process theories on the job satisfaction of previously disadvantaged Secondary School principals in the North West province. A mixed-method approach consisting of both quantitative and qualitative methods was used for the study. A questionnaire was administered during the quantitative phase with a sample that comprised thirty Secondary School principals purposefully selected from rural and township schools. The second part of the research was qualitative. Structured interviews were conducted with eight purposefully selected principals from the original sample of thirty. The theoretical framework of the research was based on the process theories. The results show that principals in the study felt that the rewards they obtain as a form of output were not equitable to their efforts (input). Finally, the researcher made a number of propositions and recommendations to school managers on ways to enhance job satisfaction of school principals.
Risk Factors for Allergy in Secondary School Girls

Ambient air is identified by the World Health Organization as a high public health priority, since air pollution associated with increase in mortality and morbidity of disease [1,2]. Respiratory disorders are the most important health problems in Iraq [3] The reported studies indicated a high prevalence rate of allergic diseases in Iraqi population. [4] In addition, respiratory infection in children represent one of the major infectious problems in Iraq [5]. The community health research that were performed by Tikrit University College of Medicine [TUCOM] have estimated that more than a fourth of Iraqi children with asthma report weekly wheeze and cough. Two-thirds of report school absences and one-third report frequent sleep disturbances due to asthma. [5]
Autophagic Regulation of Retinal Pigment Epithelium Homeostasis

Retinal pigment epithelium (RPE) is a single layer of hexagonal pigmented cells located in the outmost part of the neurosensory retina. RPE cells are vital for the health of retina. Dysfunction of RPE resulted from consistent exposures to oxidative stress has been reportedly to cause retinal degenerations, such as age-related macular degeneration (AMD). RPE cells exert different types autophagy to maintain retina hemostasis. This review summarizes molecular and cellular autophagic mechanisms that are revealed in RPE to respond to stress. The evidence in support of autophagy dysfunction or aging that result in diseases is also discussed.
Vulnerability Assessment in Quantitative Risk Management Methodologies - State-of-the-Art and Challenges

The ubiquitous use of information and communication technologies has resulted in more dependency on digital infrastructures. The proliferation of information systems and communication networks had certainly enabled a substantial progress in many aspects of the daily life but it also had opened the possibilities for malicious users to exploit their weaknesses. Thus, there are new risk factors that have huge implications such as economic dependency on the information and communication systems security (CSI, 2010). Vulnerability assessment is one key step in the quantitative risk management approach. Nowadays, analyzing information system vulnerabilities is one of the main operations in a day-to-day workload of security professionals and a crucial step in a quantitative risk management lifecycle. Mitre’s CVE/CWE databases (Mitre, 2012) and OSVDB database (OSVDB, 2013) are examples of libraries whose large use among security products, aimed at big companies and organizations, shows the importance of vulnerability assessment in the risk management task. Assessing information system vulnerabilities enables security professionals to design accurate threat scenarios based on concrete data. The complexity of several risk analysis tasks is due to the identification of security weaknesses and vulnerabilities. This operation is either disregarded, leading to a wide spectrum of threats that are very complex to assess and quantify, or relies on complex methodologies which are rarely assisted by a software solution. The present paper provides a state-of-the-art of the vulnerability assessment step in quantitative risk analysis methods. These methods have been using different vulnerability assessment techniques. It should be noted that some methods do not even have a vulnerability assessment step. The techniques proposed by risk analysis methodologies have several shortcomings: (a) a limited vulnerability spectrum, (b) reliance on mathematical abstractions which may fail to translate the reality of the security level of an information system, (c) approximations which may not provide an accurate quantification of risks.
Spectroscopic characterization of 250-μm-selected hyper-luminous star-forming galaxies

We present near-infrared (near-IR) spectroscopic observations from Very Large Telescope Infrared Spectrometer And Array Camera (ISAAC) of 13 250-μm luminous galaxies in the Chandra Deep Field-South, seven of which have confirmed redshifts which average to (z) = 2.0 ± 0.4. Another two sources of the 13 have tentative z > 1 identifications. Eight of the nine redshifts were identified with Hα detection in H and K bands, three of which are confirmed redshifts from previous spectroscopic surveys. We use their near-IR spectra to measure Hα linewidths and luminosities, which average to 415 ± 20 km s ―1 and 3 x 10 35 W (implying SFR Hα ∼ 200 M ⊙ yr ―1 ), both similar to the Hα properties of submillimetre galaxies (SMGs). Just like SMGs, 250-μm-luminous galaxies have large Hα to far-infrared (FIR) extinction factors such that the Hα star formation rates (SFRs) underestimate the FIR SFRs by approximately eight to 80 times. FIR photometric points observed from 24 to 870 μm are used to constrain the spectral energy distributions even though uncertainty caused by FIR confusion in the Balloon-borne Large-Aperture Submillimeter Telescope (BLAST) bands is significant. The population has a mean dust temperature of T d = 52 ± 6 K, emissivity β = 1.73 ± 0.13 and FIR luminosity L FIR = 3 × 10 13 L ⊙ . Although selection at 250 μm allows for the detection of much hotter dust-dominated hyper-luminous infrared galaxies (HyLIRGs) than SMG selection (at 850 μm), we do not find any ≳60-K 'hot-dust' HyLIRGs. We have shown that near-IR spectroscopy combined with good photometric redshifts is an efficient way to spectroscopically identify and characterize these rare, extreme systems, hundreds of which are being discovered by the newest generation of IR observatories including the Herschel Space Observatory.
Environmental factors affecting maerl bed structure in Brittany (France)

This study used a large spatial scale approach in order to better quantify the relationships between maerl bed structure and a selection of potentially forcing physical factors. Data on maerl bed structure and morpho-sedimentary characteristics were obtained from recent oceanographic surveys using underwater video recording and grab sampling. Considering the difficulties in carrying out real-time monitoring of highly variable hydrodynamic and physicochemical factors, these were generated by three-dimensional numerical models with high spatial and temporal resolution. The BIOENV procedure indicated that variation in the percentage cover of thalli can best be explained (correlation = 0.76) by a combination of annual mean salinity, annual mean nitrate concentration and annual mean current velocity, while the variation in the proportion of living thalli can best be explained (correlation = 0.47) by a combination of depth and mud content. Linear relationships showed that the percentage cover of maerl thalli was positively correlated with nitrate concentration (R2 = 0.78, P < 0.01) and negatively correlated with salinity (R2 = 0.81, P < 0.01), suggesting a strong effect of estuarine discharge on maerl bed structure, and also negatively correlated with current velocity (R2 = 0.81, P < 0.01). When maerl beds were deeper than 10 m, the proportion of living thalli was always below 30% but when they were shallower than 10 m, it varied between 4 and 100%, and was negatively correlated with mud content (R2 = 0.53, P < 0.01). On the other hand, when mud content was below 10%, the proportion of living thalli showed a negative correlation with depth (R2 = 0.84, P < 0.01). This large spatial scale explanation of maerl bed heterogeneity provides a realistic physical characterization of these ecologically interesting benthic habitats and usable findings for their conservation and management.
IDENTIFICATION AND COMPARATIVE GENOMIC ANALYSIS OF SIGNALING AND REGULATORY COMPONENTS IN THE DIATOM THALASSIOSIRA PSEUDONANA 1

Diatoms are unicellular brown algae that likely arose from the endocytobiosis of a red alga into a single‐celled heterotroph and that constitute an algal class of major importance in phytoplankton communities around the globe. The first whole‐genome sequence from a diatom species, Thalassiosira pseudonana Hasle et Heimdal, was recently reported, and features that are central to diatom physiology and ecology, such as silicon and nitrogen metabolism, iron uptake, and carbon concentration mechanisms, were described. Following this initial study, the basic cellular systems controlling cell signaling, gene expression, cytoskeletal structures, and response to stress have been cataloged in an attempt to obtain a global view of the molecular foundations that sustain such an ecologically successful group of organisms. Comparative analysis with several microbial, plant, and metazoan complete genome sequences allowed the identification of putative membrane receptors, signaling proteins, and other components of central interest to diatom ecophysiology and evolution. Thalassiosira pseudonana likely perceives light through a novel phytochrome and several cryptochrome photoreceptors; it may lack the conserved RHO small‐GTPase subfamily of cell‐polarity regulators, despite undergoing polarized cell‐wall synthesis; and it possesses an unusually large number of heat‐shock transcription factors, which may indicate the central importance of transcriptional responses to environmental stress. The availability of the complete gene repertoire will permit a detailed biochemical and genetic analysis of how diatoms prosper in aquatic environments and will contribute to the understanding of eukaryotic evolution.
Monitoring Insecticide Resistance Development in Beet Armyworm, Spodoptera exigua (Hübner) (Lepidoptera: Noctuidae)

Field collected larvae of beet armyworm, Spodoptera exigua (Hubner) were reared and evaluated for resistance against cypermethrin 10 EC, neem extract (Azadirachtin 0.1%) and Bacillus thuringiensis Berliner var. kurstaki (53,000 SU per mg) for 12 generations under laboratory condition by using leaf dip bioassay. Cypermethrin showed LC50 value of 251 ppm at F1 generation and decreased gradually to onward generations resulting LC50 value of 90 ppm at F12 generation for non-selection, whereas LC50 increased rapidly with a value of 8625 ppm at F12 generation under selection pressure. Neem extract exhibited LC50 value ranging from 3.98 ppm to 9.99 ppm for non-selection, whereas under selection pressure LC50 ranged from 4.38 ppm to 13.04 ppm throughout the generations. Bacillus thuringiensis var. kurstaki showed LC50 value which ranged from 7.3 × 106 SU/L to 15.9 × 106 SU/L for non-selection, and selection for resistance monitoring gave LC50 value ranged from 7.6 × 106 SU/L to 73.9 × 106 SU/L . Compared with non-selection strain, selection strain exhibited 95.83-fold, 1.44-fold and 5.6-fold increase in the LC50 for 12 generations against cypermethrin, neem extract and Bacillus thuringiensis var. kurstaki, respectively.