Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of Single and Multiple Specimen Suction Control Oedometer Testing on the Measurement of the Soil–Water Characteristic Curve

Devices that simultaneously facilitate controlling suction and applying a net stress on soil specimen provide soil–water characteristic curves (SWCCs) in terms of both the water content and degree of saturation, and volumetric deformations at various applied suctions. Such tests determine the water content of soil specimens based on the measured water volume changes at various applied suctions. However, studies have shown disagreements between the water volume–based calculated water content and the actual water content of soil specimens determined by the oven-drying method. Testing multiple soil specimens at predetermined suctions and measuring water content by the oven-drying method can overcome this but are a time-consuming approach. In this study, the impact of testing single and multiple soil specimens on the subsequently determined suction-water content and suction-degree of saturation SWCCs for the wetting process were studied. Statically compacted specimens of a sandy clay were used for establishing SWCCs using a suction control oedometer. Differences were noted between the calculated and measured water content and degree of saturation for an applied suction range of 0 to 95 kPa. Differences were noted between the SWCC fitting parameters obtained from the test results of single and multiple soil specimens. Statistical analysis suggested the differences between the results from single and multiple soil specimens testing were not significant. Corrections applied to the water volume change measurements were found to minimize these differences.
Disinfection Properties of Conventional White LED Illumination and Their Potential Increase by Violet LEDs for Applications in Medical and Domestic Environments

The antimicrobial impact of visible violet and blue light has been known for more than a century but hardly been applied for purposeful pathogen reduction or prevention. The disinfecting properties of wide-spread warm-white and cool-white light emitting diodes (LEDs) are investigated by irradiation of staphylococci with different LEDs and varying doses. Additionally, the combination of a white and a violet LED illumination is examined. Both white LEDs exhibit an antimicrobial effect, which seems to be dominated by the blue parts of the LED emissions. Unfortunately, the antimicrobial effect is weak in realistic illumination applications. Additional violet LEDs can significantly enhance this impact without a large change in human color perception. This allows reasonable applications in certain medical and domestic environments without endangering humans.
Electronic band structure engineering in InAs/InSbAs and InSb/InSbAs superlattice heterostructures

We report a detailed ab initio study of two superlattice heterostructures, one component of which is a unit cell of CuPt ordered InSb_(0.5)As_(0.5). This alloy part of the heterostructures is a topological semimetal. The other component of each system is a semiconductor, zincblende-InSb, and wurtzite-InAs. Both heterostructures are semiconductors. Our theoretical analysis predicts that the variation in the thickness of the InSb layer in InSb/InSb_(0.5)As_(0.5) heterostructure renders altered band gaps with different characteristics (i.e. direct or indirect). The study holds promise for fabricating heterostructures, in which the modulation of the thickness of the layers changes the number of carrier pockets in these systems.
A Novel Decomposition Model for Visual Rail Surface Inspection

Rail surface inspection plays a pivotal role in large-scale railway construction and development. However, accurately identifying possible defects involving a large variety of visual appearances and their dynamic illuminations remains challenging. In this paper, we fully explore and use the essential attributes of our defect structure data and the inherent temporal and spatial characteristics of the track to establish a general theoretical framework for practical applications. As such, our framework can overcome the bottleneck associated with machine vision inspection technology in complex rail environments. In particular, we consider a differential regular term for background rather than a traditional low-rank constraint to ensure that the model can tolerate dynamic background changes without losing sensitivity when detecting defects. To better capture the compactness and completeness of a defect, we introduce a tree-shaped hierarchical structure of sparse induction norms to encode the spatial structure of the defect area. The proposed model is evaluated with respect to two newly released Type-I/II rail surfaces discrete defects (RSDD) data sets and a practical rail line. Qualitative and quantitative evaluations show that the decomposition model can handle the dynamics of the track surface well and that the model can be used for structural detection of the defect area.
Plasma Medicine Technologies

This Special Issue, entitled “Plasma Medicine Technologies”, covers the latest remarkable developments in the field of plasma bioscience and medicine. Plasma medicine is an interdisciplinary field that combines the principles of plasma physics, material science, bioscience, and medicine, towards the development of therapeutic strategies. A study on plasma medicine has yielded the development of new treatment opportunities in medical and dental sciences. An important aspect of this issue is the presentation of research underlying new therapeutic methods that are useful in medicine, dentistry, sterilization, and, in the current scenario, that challenge perspectives in biomedical sciences. This issue is focused on basic research on the characterization of the bioplasma sources applicable to living cells, especially to the human body, and fundamental research on the mutual interactions between bioplasma and organic–inorganic liquids, and bio or nanomaterials.
Inmplode: A framework to interpret multiple related rule‐based models

There is a growing trend to split problems into separate subproblems and develop separate models for each (e.g., different churn models for separate customer segments; different failure prediction models for separate university courses, etc.). While it may lead to better predictive models, the use of multiple models makes interpretability more challenging. In this paper, we address the problem of synthesizing the knowledge contained in a set of models without a significant loss of prediction performance. We focus on decision tree models because their interpretability makes them suitable for problems involving knowledge extraction. We detail the process, identifying alternative methods to address the different phases involved. An extensive set of experiments is carried out on the problem of predicting the failure of students in courses at the University of Porto. We assess the effect of using different methods for the operations of the methodology, both in terms of the knowledge extracted as well as the accuracy of the combined models.
Chemical synthesis of stimuli-responsive guide RNA for conditional control of CRISPR-Cas9 gene editing

CRISPR-Cas9 promotes changes in identity or abundance of nucleic acids in live cells and is a programmable modality of broad biotechnological and therapeutic interest. To reduce off-target effects, tools for conditional control of CRISPR-Cas9 functions are under active research, such as stimuli-responsive guide RNA (gRNA). However, the types of physiologically relevant stimuli that can trigger gRNA are largely limited due to the lack of a versatile synthetic approach in chemistry to introduce diverse labile modifications into gRNA. In this work, we developed such a general method to prepare stimuli-responsive gRNA based on site-specific derivatization of 2′-O-methylribonucleotide phosphorothioate (PS-2′-OMe). We demonstrated CRISPR-Cas9-mediated gene editing in human cells triggered by oxidative stress and visible light, respectively. Our study tackles the synthetic challenge and paves the way for chemically modified RNA to play more active roles in gene therapy.
Line-of-Sight Winds and Doppler Effect Smearing in ACE-FTS Solar Occultation Measurements

Line-of-sight wind profiles are derived from Doppler shifts in infrared solar occultation measurements from the Atmospheric Chemistry Experiment Fourier transform spectrometers (ACE-FTS), the primary instrument on SCISAT, a satellite-based mission for monitoring the Earth’s atmosphere. Comparisons suggest a possible eastward bias from 20 m/s to 30 m/s in ACE-FTS results above 80 km relative to some datasets but no persistent bias relative to other datasets. For instruments operating in a limb geometry, looking through a wide range of altitudes, smearing of the Doppler effect along the line of sight can impact the measured signal, particularly for saturated absorption lines. Implications of Doppler effect smearing are investigated for forward model calculations and volume mixing ratio retrievals. Effects are generally small enough to be safely ignored, except for molecules having a large overhang in their volume mixing ratio profile, such as carbon monoxide.
Brazil’s marine protected areas fail to meet global conservation goals

Reducing species extinctions and expanding protected areas are key goals of the Convention on Biological Diversity (CBD). To meet these goals, nations should assure a minimum protection of all ecoregions (Target 11) and preserve the most threatened species (Target 12). While the total extent of marine protected areas (MPAs) in Brazil has increased sharply, little is known about MPAs’ capacity in representing the country´s commitments for global conservation goals. Here, we evaluated how well the current system of MPAs represents the geographic range of 118 threatened marine vertebrate species and the eight marine ecoregions in Brazil. We also investigated where unprotected or poorly protected species are concentrated, and whether existing MPAs are prioritizing the species most at risk. Results revealed that half of marine ecoregions have <10% of their area under protection, and therefore that Brazil has failed to meet CBD Aichi Target 11. About 3% of the threatened marine vertebrates remain completely unprotected by MPAs, and most (88.1%) species have less than 10% of their ranges covered by no‐take MPAs. Moreover, coverage provided by MPAs is strongly biased toward species under low threat levels. Our mapping of current conservation gaps highlights where establishing new MPAs could improve the protection of imperilled species and contribute to achieve global conservation goals.
Nestling diet of the Algerian Nuthatch Sitta ledanti, an endemic threatened bird in Babors’ Kabylia region (north-eastern Algeria)

The Algerian Nuthatch is an endemic and protected bird species in Algeria, and its different habitats are threatened by fires and others human actions; the species is therefore considered ‘Endangered’. A faecal samples analysis of the species’ nestlings was done to determine their diet. The nestling faecal samples were collected during the breeding season of 2019 in the Tamentout deciduous forest in the region of Babors’ Kabylia (north-east Algeria). The faecal samples analysis allowed us to count 686 individuals belonging to 39 different prey taxa. They belong to two arthropods classes and six orders. Insects (95.4%) were more dominant compared with spiders (4.96%). Beetles were most diverse, with 22 prey taxa and 293 individuals. Dermaptera (earwigs) were represented by only two prey taxa and 265 individuals, with the European Earwig Forficula auricularia recorded 253 times. A correlation was also found between the prey sizes and energy intake. Costello’s charts indicated five potential prey including Forficula auricularia, Oxythyrea funesta and Anthaxia sp. were the most consumed. The niche breadth calculation (0.017) revealed that the Algerian Nuthatch specialises on some prey items such as Forficula auricularia to feed its nestlings. The most prized prey species had sizes between 14.5 mm and 19 mm, Forficula auricularia has a size of 15 mm.
A microstrip bandpass filter with tunable bandwidth and center frequency

This paper presents a bandwidth and center frequency tunable bandpass filter with wide tuning range. The proposed filter employs two cascade cross‐shaped resonators. The cross‐shaped resonator can generate two independent tunable transmission zeros by introducing two microwave varactors. The center frequency and bandwidth can be tuned by adjusting the DC bias voltages applied to the varactors. For demonstration, a filter example was designed, fabricated and measured. The tuning 3‐dB bandwidth from 20% to 30% is achieved when the center frequency is tuned from 3.5 to 5 GHz. Meanwhile the insertion loss is less than 4 dB with a high selectivity. The size of the filter is 0. 32λg × 0. 36λg where λg is the guided‐wavelength at the center frequency.
A Relation-Augmented Embedded Graph Attention Network for Remote Sensing Object Detection

Multiclass geospatial object detection in high spatial resolution remote sensing imagery (HSRI) is still a challenging task. The main reason is that the objects in HRSI are location-variable and semantic-confusable, which results in the difficulties in differentiating the complicated spatial patterns and deriving the implicitly semantic labels among different categories of objects. In this article, we propose a relation-augmented embedded graph attention network (EGAT), which enables the full exploitation of the underlying spatial and semantic relations among objects for improving the detection performance. Specifically, we first construct two sets of spatial and semantic graphs of objects–objects for object relations modeling. Second, a Siamese architecture-based embedding spatial and semantic graph attention network is designed for relations reasoning, which is implemented by introducing the long short-term memory (LSTM) mechanism into the EGAT, for learning the relations among different categories of intraobjects and interobjects. Driven by the spatial and semantic LSTM, the EGAT-LSTM can adaptively focus on the critical information of reason graphs for spatial–semantic correlation discrimination in the embedding non-Euclidean feature space. By this way, the EGAT-LSTM can effectively capture the global and local spatial–semantic relationships of objects–objects, and then produce relations-augmented features for improving the performance of object detection. We conduct comprehensive experiments on three public datasets for multiclass geospatial object detection. Our method achieves state-of-the-art performance, which demonstrates the superiority and effectiveness of the proposed method.
Survival of the Recidivistic? Revealing Factors Associated with the Criminal Career Length of Multiple Homicide Offenders

Relying on a sample of 1,381 US-based multiple homicide offenders (MHOs), we study the duration of the careers of this extremely violent category of offenders through Kaplan–Meier estimation and Cox Proportional Hazard regression. We investigate the characteristics of such careers in terms of length and we provide an inferential analysis investigating correlates of career duration. The models indicate that MHOs employing multiple methods, younger MHOs and MHOs that acted in more than one US state have higher odds of longer careers. When controlling for career-based attributes, female MHOs are also correlated with longer careers.
Biological Activity of Wastewater Assessed Using in Vitro Cell-Based Assays

Bioanalytical tools, namely in vitro bioassays, can be employed in tandem with chemical analyses to assess the efficacy of wastewater treatment and the potential for adverse effects from the discharges of wastewater into receiving waters. In the present study, samples of untreated wastewater (i.e. influent) and treated wastewater (i.e. effluent) were collected from two wastewater treatment plants and a wastewater treatment lagoon serving municipalities in southern Ontario, Canada. In addition, grab samples of surface water were collected downstream of the lagoon discharge. After solid phase extraction (SPE) using ion-exchange columns for basic/neutral and acidic compounds, respectively, the extracts were analyzed for a suite of 16 indicator compounds. The two SPE extracts were combined for analysis of biological responses in four in vitro cell-based bioassays. The concentrations of several indicator compounds, including the estrogens, 17β-estradiol and 17α-ethinylestradiol, were below the limits of detection. However, androstenedione and estrone were detected in several influent samples. The concentrations of these steroid hormones and some of the other indicator compounds declined during treatment but acesulfame K, carbamazepine, trimethoprim and DEET persisted in the effluent. The MTS- CellTiter 96® AQueous One Solution Cell Proliferation Assay (MTS) indicated that cell viability was not affected by exposure to the extracts. The Qiagen Nuclear Receptors 10-Pathway Reporter Array indicated that several cellular pathways were upregulated, with the greatest upregulation observed with the estrogen receptor (i.e. induction ratios 12 to 47) and the liver X receptor (i.e. induction ratios 10 to 45). The ERα CALUX assay indicated that estrogenic activity was lower in effluents compared to influents, with the greatest estrogenic activity observed for grab samples of influent from the lagoon (i.e. 56-215 ng L-1 17β-estradiol equivalents). Finally, the results of the Nrf2 Luciferase Luminescence Assay indicated a lower oxidative stress in the effluent samples. Overall, the present study demonstrates that chemical analyses are limited in their ability to predict or explain reductions in the toxicity of treated wastewater. There are thus advantages to using a combination of chemical analyses and in vitro bioassays to monitor the treatment efficiency of wastewater treatment plants and to predict the potential impacts of wastewater discharges into receiving waters.
Does The Working Length Change When Using The XP-Endo Shaper File at Different Operating Temperatures?

Introduction: This study was directed to evaluate the effect of different operating temperatures on the change in working length when using the XP-endo shaper file. Methods: A total of 20 plastic blocks with16 mm curved canals were used in this study. The working length was adjusted to be 15 mm using a customized Teflon stopper (10mm in length) which was used with all files in the study. The preparation was done using the XP-endo shaper file (FKG, La Chaux-de-Fonds, Switzerland) according to the manufacturer’s instructions. The blocks were divided into 2 groups: Group 1: body temperature, Group 2: room temperature. Pre and post instrumentation imaging of the blocks was done using the stereomicroscopy at 8x. The images were superimposed to create a composite image on which the evaluation of working length change was done. Mann-Whitney U test was used to compare the change in working length in the two groups. Results: There was no statistically significant difference between the two groups (P ≤ 0.05). Conclusions: Within the parameters of this study, although both groups showed an increase in working length when using the XP-endo shaper file, the operating temperature did not have an effect.
Do European firms obey the rules? Environmental innovativeness in light of institutional frameworks

ABSTRACT In light of increasing ecological issues, the deployment of environmentally friendly technologies is of major importance. This paper examines how institutions can influence firm behaviour with respect to introducing environmental innovations. Based on institutional and innovation theory, we explore the relationship of institutional factors with two highly relevant and heterogeneous types of environmental innovation, namely: the reduction of material use (Ecomat) and the reduction of carbon dioxide emissions (Ecoco). We utilise the 2008 and 2014 survey waves of the Community Innovation Survey (CIS). This allows us to explore two separate cross-sectional samples at different points of time. Each sample is drawn from twelve European Union countries, giving us a total of about 70,000 firms. We find that formal institutions more strongly influence Ecoco innovation, especially for the CIS 2014 sample. We find that informal institutions affect both innovation types similarly.
Copper nanoparticles spaced 3D graphene films for binder-free lithium-storing electrodes

Copper nanoparticles (Cu NPs) spaced reduced graphene oxide (rGO) films are fabricated by integrating electrophoresis deposition (EPD) with thermal H2 annealing. The Cu NPs are formed through thermal aggregation and reduction of Cu(II) ions which are counter cations of GO. By tuning the annealing temperature from 400 to 850 °C, the mean diameter of the Cu NPs increases from 35 to 124 nm. Chemical characterizations reveal that the EPD technique may partially remove the O-containing groups of the GO film, while complete removal of the O-containing groups and effective repair of the graphene defects are achieved by thermal H2 treatment. With the implantation of Cu NPs, the resultant rGO/Cu NP films exhibit high porosity and amazing electric conductivities, enabling their direct use as lithium-ion battery (LIB) electrodes (vs. Li/Li+) without a general current collector, binder, and other additives. This novel LIB has a high charge/discharge capacity (>463 mA h g−1), an excellent reversibility, and a high coulombic efficiency (nearly 100%) for 300 cycles at a current density of 0.2 A g−1. It also exhibits good rate capacity: 849 mA h g−1@0.1 A g−1, 618 mA h g−1@0.2 A g−1, 516 mA h g−1@0.3 A g−1, and 470 mA h g−1@0.5 A g−1. Our new technique provides advanced design strategies for high performance LIBs and ultracapacitors, which might be used for mobile phone and electrical vehicles with unprecedented performances.
Analisis Perbandingan Keakuratan CAPM Dan APT Dalam Upaya Pengambilan Keputusan Investasi Saham Sektor Perbankan

The Capital Asset Pricing Model and the Arbitrage Pricing Theory are a balance model that uses risk measurement variables to see risk correlations and returns. This research is descriptive quantitative. The purpose of this research is to find out how much the value of stock returns in the banking sector is calculated by the Capital Asset Pricing Model and Arbitrage Pricing Theory, looking for a more accurate model and how big is the difference in accuracy of the significant accuracy of the Capital Asset Pricing Model and Arbitrage Pricing Theory in making investment decisions in the banking sector. The population in this study is a banking company registered at Indonesia Stock Exchange during 2015-2018. The sample in this study amounted to 36 banking companies listed on the Indonesia Stock Exchange during 2015-2018. The sampling method is a non-probability sampling method that is purposive sampling technique. The results of this study indicate that the Capital Asset Pricing Model is better than the Arbitrage Pricing Theory and there is no difference in accuracy between the Capital Asset Pricing Model and the Arbitrage Pricing Theory in an investment decision making effort at banking sector.