Miracle-dz/UniFAR-FTUs huggingface dataset:
Artifact removal in photoacoustic tomography with an unsupervised method.

Photoacoustic tomography (PAT) is an emerging biomedical imaging technology that can realize high contrast imaging with a penetration depth of the acoustic. Recently, deep learning (DL) methods have also been successfully applied to PAT for improving the image reconstruction quality. However, the current DL-based PAT methods are implemented by the supervised learning strategy, and the imaging performance is dependent on the available ground-truth data. To overcome the limitation, this work introduces a new image domain transformation method based on cyclic generative adversarial network (CycleGAN), termed as PA-GAN, which is used to remove artifacts in PAT images caused by the use of the limited-view measurement data in an unsupervised learning way. A series of data from phantom and in vivo experiments are used to evaluate the performance of the proposed PA-GAN. The experimental results show that PA-GAN provides a good performance in removing artifacts existing in photoacoustic tomographic images. In particular, when dealing with extremely sparse measurement data (e.g., 8 projections in circle phantom experiments), higher imaging performance is achieved by the proposed unsupervised PA-GAN, with an improvement of ∼14% in structural similarity (SSIM) and ∼66% in peak signal to noise ratio (PSNR), compared with the supervised-learning U-Net method. With an increasing number of projections (e.g., 128 projections), U-Net, especially FD U-Net, shows a slight improvement in artifact removal capability, in terms of SSIM and PSNR. Furthermore, the computational time obtained by PA-GAN and U-Net is similar (∼60 ms/frame), once the network is trained. More importantly, PA-GAN is more flexible than U-Net that allows the model to be effectively trained with unpaired data. As a result, PA-GAN makes it possible to implement PAT with higher flexibility without compromising imaging performance.
Deep reinforcement learning in production systems: a systematic literature review

Shortening product development cycles and fully customisable products pose major challenges for production systems. These not only have to cope with an increased product diversity but also enable high throughputs and provide a high adaptability and robustness to process variations and unforeseen incidents. To overcome these challenges, deep Reinforcement Learning (RL) has been increasingly applied for the optimisation of production systems. Unlike other machine learning methods, deep RL operates on recently collected sensor-data in direct interaction with its environment and enables real-time responses to system changes. Although deep RL is already being deployed in production systems, a systematic review of the results has not yet been established. The main contribution of this paper is to provide researchers and practitioners an overview of applications and to motivate further implementations and research of deep RL supported production systems. Findings reveal that deep RL is applied in a variety of production domains, contributing to data-driven and flexible processes. In most applications, conventional methods were outperformed and implementation efforts or dependence on human experience were reduced. Nevertheless, future research must focus more on transferring the findings to real-world systems to analyse safety aspects and demonstrate reliability under prevailing conditions.
Extending OTDR Distance Span by External Front-End Optical Preamplifier

Optical time-domain reflectometer (OTDR) is used to characterize fiber optic links by identifying and localizing various refractive and reflective events such as breaks, splices, and connectors, and measuring insertion/return loss and fiber length. Essentially, OTDR inserts a pulsed signal into the fiber, from which a small portion that is commonly referred to as Rayleigh backscatter, is continuously reflected back with appropriate delays of the reflections expressed as the power loss versus distance, by conveniently scaling the time axis. Specifically, for long-distance events visibility and measurement accuracy, the crucial OTDR attribute is dynamic range, which determines how far downstream the fiber can the strongest transmitted optical pulse reach. As many older-generation but still operable OTDR units have insufficient dynamic range to test the far-end of longer fibers, we propose a simple and cost-effective solution to reactivate such an OTDR by inserting a low-noise high-gain optical preamplifier in front of it to lower the noise figure and thereby the noise floor. Accordingly, we developed an appropriate dynamic range and distance span extension model which provided the exemplar prediction values of 30 dB and 75 km, respectively, for the fiber under test at 1550 nm. These values were found to closely match the dynamic range and distance span extensions obtained for the same values of the relevant parameters of interest by the preliminary practical OTDR measurements conducted with the front-end EDFA optical amplifier, relative to the measurements with the OTDR alone. This preliminary verifies that the proposed concept enables a significantly longer distance span than the OTDR alone. We believe that the preliminary results reported here could serve as a hint and a framework for a more comprehensive test strategy in terms of both test diversification and repeating rate, which can be implemented in a network operator environment or professional lab.
p-Flurophenyldicyanovinyl as electron-withdrawing group for highly soluble and thermally stable donor–acceptor small molecules

Abstract. Solution-processed small molecule-based solar cells have demonstrated high power conversion efficiencies in recent years. However, several challenges have yet to be overcome, including achieving of low cost and excellent long-term stability of donor small molecules. Therefore, development of stable blocks to design organic semiconductors with optimal properties remains an actual problem. We report an alkyl-free star-shaped donor–acceptor (D–A) molecule, N(Ph-2T-DCV-PhF)3, containing p-fluorophenyldicyanovinyl (FPh-DCV) electron-withdrawing groups, triphenylamine as the donor core, and 2,2′-bithiophenes as the π-bridges between them. The study of thermal, optical, and electrochemical properties of the molecule in comparison to the direct analog with phenyldicyanovinyl groups, N(Ph-2T-DCV-Ph)3, made it possible to demonstrate the effect of the fluorine substituent on such key parameters as solubility, bandgap, lowest unoccupied molecular orbital energy level, phase behavior, thermal stability, and wettability. This work suggests that usage of the FPh-DCV block is an effective and simple tool to tune physical and physicochemical properties of stable D–A small molecules.
The effect of solvent on Al-doped ZnO thin films deposited via aerosol assisted CVD

Aluminium-doped zinc oxide (AZO) thin films were deposited via aerosol assisted chemical vapour deposition (AACVD) from zinc acetylacetonate and aluminium chloride at 450 °C. The precursor solutions consisted of methanol in a mixture with one other secondary solvent, including toluene, tetrahydrofuran, n-hexane, cyclohexane, and ethyl acetate. The crystal structures, elemental compositions and surface morphologies of the resulting AZO films were determined, as well as the optoelectronic properties. It was found that the more polar solvents enhanced growth in the (002) plane of the wurtzite crystal structure, and that solutions with low viscosities resulted in superior grain growth. The film deposited from a solution consisting of methanol and ethyl acetate displayed the lowest visible transmittance, due to carbon contamination. However, it also exhibited 60% lower resistivity, in comparison to the film deposited using methanol only. This suggests that optoelectronic properties can be tuned for specific photovoltaic devices.
The performance of ground source heat pipes at low constant source temperatures

ABSTRACT Thermal performance of ground source two-phase closed thermosyphon is investigated theoretically according to different working fluids, different evaporator lengths,, and heat source temperatures. First, a theoretical model of the thermosyphon was created. For the thermosyphon, whose working fluid is ammonia, acetone or methanol, different evaporator lengths, and different heat source temperatures were used for thermal analysis. Analyses are presented in detail with figures. It was observed that the ammonia performed better at the specified working conditions. As the evaporator length increases, the heat transfer capacity of the thermosyphon enhances. However, as the evaporator length increases, the saturation temperature of the fluid also increases due to the effect of hydrostatic pressure, so it was seen that the thermosyphon would not carry heat under these conditions. The maximum heat transfer rate and optimum evaporator lengths for the thermosyphon were determined for the conditions specified and the fluids used in the study.
Perspectives on Chemical Modification of Carbon Nanomaterials Assisted by Microwave Radiation

Carbon nanomaterials (CNMs) as graphene and carbon nanotubes (CNTs) have attracted attention of scientific community due to their high performance and applications. However, their potential applications as nanofillers, depends necessarily of their production which high structural quality, great compatibility with the host system. For instance, in polymeric matrices this issue involves several challenges due to their low dispersibility in water and organic solvents, thus different process of chemical modification of CNMs surfaces have been reported. In cases of functionalization with amino groups, most of them use in one of their chemical steps thionyl chloride (SOCl2) as intermediate reagent. In general, the use of SOCl2 limits the chemical process, due to of its dangerous nature and high level of toxicity. Another drawback found in this kind of methodology is the time spent on reflux lasting days and making it a very onerous process. In this context, the chemical modification of CNMs assisted by microwave radiation has been explored in synthesis, purification and chemical modification processes of these nanostructures resulting in simpler and faster procedures that allow its used on a large scale and with low environmental impact.
Substantial Stem Methane Emissions From Rainforest and Cacao Agroforest Partly Negate Soil Uptake in the Congo Basin

Most stem CH4 emission investigations were conducted in wetland forests, and it remains unknown whether trees in tropical rainforests on heavily weathered soils are substantial contributors to ecosystem CH4 fluxes. Additionally, Africa remains the continent with the lowest numbers of published field studies on soil greenhouse gas fluxes. Over one year, we measured monthly stem and soil CH4 fluxes with forest conversion to traditional cacao agroforestry in the Congo Basin, Cameroon. All the measured trees emitted CH4 throughout the year. The annual total (soil + stem) CH4 fluxes were −2.62 ± 0.37 kg C ha−1 yr−1 from the forest and −3.23 ± 0.45 kg C ha−1 yr−1 for the cacao agroforestry, with stem CH4 emissions equating to 4%–21% of the soil sink in the forest, and 3%–27% of the soil sink in cacao agroforestry. 2% of our measured trees were “hot spots” of CH4 emission, with two orders of magnitude larger emissions than the remaining trees in our sites. Correlations of stem CH4 emissions and soil drivers suggest a potential belowground source of stem CH4 emissions, although this pathway may be working simultaneously with a within‐tree microbial CH4 source. Overall, forest conversion to traditional, mature cacao agroforestry did not affect stem and soil CH4 fluxes. Our results demonstrate that tropical trees on well‐drained, highly weathered soils represent potential CH4 emission pathways that have largely been ignored, and provides evidence that upland ecosystems may be weaker sinks of atmospheric CH4 than previously estimated.
Adsorption of Congo Red from Aqueous Solutions by Porous Soybean Curd Xerogels

Abstract Soybean curd is a very popular food containing high-quality protein, polyunsaturated fats, vitamins, minerals and other nutrients. This study aims to prepare porous soybean curd xerogels via a vacuum freeze drying method and uses them as adsorbents to remove congo red from aqueous solutions. The morphology and functional groups of the soybean curd xerogels were characterized using scanning electron microscopy and Fourier transform infrared spectroscopy, respectively. The adsorption properties of congo red onto the soybean curd xerogels were carried out through investigating the infl uencing experimental parameters such as the drying method, solution pH, adsorbent dose, contact time and temperature. The results showed that the adsorption isotherm data were fitted well to the Freundlich isotherm. Adsorption kinetics of congo red onto the soybean curd followed the pseudo-second-order kinetic model. The thermodynamic parameters, such as ΔG0, ΔH0 and ΔS0, were also determined.
A neglected area: supervision development opportunities for doctoral researchers involved in undergraduate and masters project mentoring

ABSTRACT This paper calls for consideration of appropriate support and development for doctoral research students involved in supervision of undergraduate and Master’s degree projects. This subgroup’s professional development tends to be neglected in academic development and the related literature. The paper describes a development workshop offered regularly to this group over four years. Presenting evaluation and focus group data, the authors argue that although institutional structures can inhibit such development activities, there are benefits to PhD students, project students, and lead supervisors when doctoral research students’ supervision is validated and supported. They call for further research and development provision in this area.
Shooting noise annoyance in communities around German military training areas

Shooting noise is characterized as impulsive, intermittent sound with high energy and low frequencies. Studies have shown that for given average sound levels shooting noise is regarded as more annoying than transportation noise, particularly road traffic noise. In comparison to transportation noise, responses to shooting noise are less frequently studied. The latest published German studies on community responses to shooting noise were conducted in the 1980ies and 1990ies. The study presented in this contribution aims to provide new data on shooting noise responses in communities around military training areas. Annoyance responses were collected using a survey with 1043 residents living around three military training sites in Germany. For the address of each resident, on the basis of shooting training in the year 2019 the average continuous sound levels and the sound exposure levels for day and night-time with the frequency weightings A, C, and Z was estimated for grid cells of 250 x 250 m. Results on the exposure-response relationship between these noise metrics and the percentage of highly annoyed persons (%HA) are presented. Among others, the results indicate, that non-acoustic factors, particularly attitudes related to the source have a strong impact on the annoyance.
The Impact of Psychological Distance on Judging Satisfaction with Nuclear Energy Policy via Knowledge Calibration and an Integrated Causal Path Model

This study investigated how, through knowledge calibration and a causal path model, psychological distance can explain the level of satisfaction with nuclear energy policy. The investigation used multiple regression analysis and path analysis to explore relationships among variables. Data from 1056 adults revealed that more knowledge-calibrated individuals have more positive attitudes toward nuclear energy policy. In addition, the psychological distance influences policy satisfaction by mediation of perceived risk of nuclear energy. This study aimed to increase the understanding of the dynamic of satisfaction with and acceptance of nuclear energy policy among stakeholders. Thus, based on the construal level theory, the study addressed the importance of knowledge and psychological distance in explaining variation in satisfaction and acceptance about nuclear policy.
Three-Level Indirect Matrix Converter With Neutral-Point Potential Balance Scheme for Adjustable Speed Drives

To improve the performance and explore a new solution of adjustable speed drive systems, a T-type three-level indirect matrix converter (T3LIMC) topology and its modulation scheme are presented in this article. The presented topology is composed of an LC input filter, a current-source rectifier, and a T-type three-level inverter, where the split dc source voltage of the inverter is formed by two input line-line voltages and the neutral-point voltage. A multicarrier-based modulation scheme for the inverter and a specific zero-sequence voltage are also developed, and the desired neutral-point current of the inverter is constructed to compensate for the input currents. Consequently, the balanced neutral-point potential and symmetric sinusoidal input currents are achieved without additional control effort. In addition to advantages such as bidirectional power flow, sinusoidal input–output currents, controllable input power factor, no dc-link energy storage elements, and compact structure, the T3LIMC also improves the output waveform quality by generating the three-level output voltages. Meanwhile, the zero current switching (ZCS) operation of the rectifier helps to improve efficiency. Finally, the functionality and effectiveness of the presented topology and modulation scheme are verified by experimental results.
Anthropometric parameters in young cross-country skiers from 13 to 16 years old

Monitoring a series of anthropometric parameters and body composition analysis, respectively the relationship of components of body composition, may be an appropriate indicator of nutritional status, not only the individual, but also indicative of the influence of physical activity on the organism. Cross-country skiing is among the cyclic endurance activity. The aim of our study was to determine the selected anthropometric parameters and determine the somatotype in young cross-country skiers from 13 to 16 years old. The group consisted of 15 boys (average age 14,3 ± 0,9 years, height 169,0 ± 11,3 cm, weight 53,2 ± 10,6 kg, BMI 18,4 ± 1,5 kg/m2). The average somatotype of probands was mezomorfic ectomorph (1,2 3,5 4,5). We used skinfold thickness measurement by Pařízková (1977) for the body composition analysis (average values fat mass 9,2 ± 1,8 %, fat free mass 48,3 ± 9,9 kg).
Analysis on Impact of Acid Hydrolysis on the Hydrogen Bonding Network in Cellulose to Obtain Microcrystalline Cellulose: A Statistical Approach

Hydrolysis of a cellulose biomass results in breaking down the cellulose microfibrils into microcrystalline cellulose (MCC) or nanocrystalline cellulose (NCC) depending on the reaction conditions. Cellulose microfibrils are established robustly due to the synergistic interaction of van der Waals, inter- and intra-molecular hydrogen bonds and glycosidic bond between glucan moieties of cellulose polysaccharide. The hydrogen bonding network plays a crucial role in conforming cellulose chains into crystalline and amorphous region thereby determining its degree of crystallinity. The knowledge of hydrogen bonds in cellulose hence becomes indispensable to understand the crystallinity of cellulose before and after a hydrolysis reaction. However, the nature of hydrogen bonds after hydrolysis and how they contribute to the mechanical properties of resultant MCC/NCC are yet to be realized. This paper is therefore intended to discuss the degree of crystallinity of cellulose particles obtained after hydrolyzing waste cotton fibers (WCF) in two parts: part I, obtaining MCC with maximum total crystallinity index (TCI) by acid hydrolysis of WCF using Box Behnken Design; part II, comparing degree of crystallinity of MCC sample exhibiting highest TCI with that of WCF using analytical tools like X-ray Photoelectron Spectrometer, X-ray Diffractometer and Fourier Transform Infra- Red spectrometer. The physical dimension of MCC particle with maximum TCI has been verified using Field Emission Scanning Electron Microscopic images.
Cost‐effectiveness analysis of energy efficiency measures in the Swiss chemical and pharmaceutical industry

Energy efficiency improvement is an effective way of reducing energy demand and CO2 emissions. Although the overall final energy savings potential in chemical industry has been estimated in a few countries, energy efficiency potentials by concrete measures applicable in the sector have been scarcely explored and their associated costs are hardly analyzed. In Switzerland, the production of chemicals and pharmaceuticals exceeds all other industrial sectors in terms of energy use and CO2 emissions, and it accounted for 22% of the total industry's overall final energy demand and 25% of the CO2 emissions related to non‐renewable energy sources in 2016. In this study, the economic potentials for energy efficiency improvement and CO2 emissions reduction in the Swiss chemical and pharmaceutical industry are investigated in the form of energy efficiency cost curves. The economic potential for final energy savings and CO2 abatement based on energy‐relevant investments is estimated at 15% and 22% of the sector's final energy use and fossil fuel‐related CO2 emissions in 2016, respectively. Measures related to process heat integration are expected to play a key role for final energy savings. The economic electricity savings potential by improving motor systems is estimated at 15% of the electricity demand by these systems in 2016. The size of economic potential of energy efficiency improvement across the sector decreases from 15% to 11% for 0.5 times lower final energy prices while the size increases insignificantly for 1.5 times higher final energy prices. The additional power generation potential based on Combined Heat and Power plants is estimated at 14 MW for 2016. This study is a contribution to the so far limited international literature on economic energy efficiency measures applicable in this heterogeneous sector and can support policy development. The results for specific costs of energy efficiency measures can also be adapted to other parts of the world by making suitable adjustments which in return may provide useful insights for decision makers to invest in economically viable clean energy solutions.
Scalable and facile synthesis of stretchable thermoelectric fabric for wearable self-powered temperature sensors

Wearable sensor systems with ultra-thinness, light weight, high flexibility, and stretchability that are conformally in contact with the skin have advanced tremendously in many respects, but they still face challenges in terms of scalability, processibility, and manufacturability. Here, we report a highly stretchable and wearable textile-based self-powered temperature sensor fabricated using commercial thermoelectric inks. Through various combinations of poly(3,4-ethylene dioxythiophene)-poly(styrene sulfonate) (PEDOT:PSS), silver nanoparticles (AgNPs), and graphene inks, we obtained linear temperature-sensing capability. The optimized sensor generates a thermoelectric voltage output of 1.1 mV for a temperature difference of 100 K through a combination of PEDOT:PSS and AgNPs inks and it shows high durability up to 800 cycles of 20% strain. In addition, the knitted textile substrate exhibits temperature-sensing properties that are dependent upon the stretching directions. We believe that stretchable thermoelectric fabric has broader potential for application in human–machine interfaces, health-monitoring technologies, and humanoid robotics.