275003 research outputs found
Sort by
Microplastic emerging pollutants - impact on microbiological diversity, diarrhea, antibiotic resistance, and bioremediation
No full text14691487Advanced economic development and technologies cause worldwide plastic waste to increase many folds, leaving policymakers with the dilemma of managing it. Synthetic solid particles or polymeric matrices of plastics with diverse shapes and sizes are the primary concern of environmental pollution of the marine ecosystem, freshwater, agriculture fields, atmosphere, food, drinking water, and other remote locations. Researchers demonstrated microplastics (MPs) as multifaceted stressors in the ecosystem, carrying toxic chemicals and vectors of transport, and described the implications of these hazardous chemicals on human health. MPs in the environment can adsorb organic, nitrogenous substances and other minerals. This complex system may promote microbial growth and aggregation. Continuous contact of microbes with MPs changes the internal arrangement of ions and atoms, alternating physio-chemical properties and becoming hydrophobic. These properties allow specific bacterial growth on MPs and promote bacterial resistance and transfer of resistance genes. MPs aged by ultra-violet light, temperature, and chemicals increase bacterial adsorption and antibiotic-resistance gene transfer synergistically. MPs are mitigated in the environment by aggregation of microbes, which leads to aging and loss of the crystalline structure of microplastic due to the release of enzymes that cause oxidation, demethylation and desertification, and hydrolysis of MPs. Aerobic conditions are preferred to degrade MPs in different environmental conditions for large-scale degradation of MPs. However, anaerobic degradation requires controlled conditions and specialized equipment. The use of a consortium of bacteria increases biodegradation efficiency. Among the microorganisms, fungi were the most effective at detoxicating xenobiotics in the environment due to their adaptability and ability to tolerate diverse conditions. This critical review analyses microplastic-induced microbial diversity and microbial adaptations to it. Furthermore, it describes MP's role in the cause of diarrhea, antimicrobial resistance, and spread. The potential use of bioremediation methods and pathways for eliminating MPs like phthalates and bisphenol from ecosystems is discussed in detail. Finally, suggestions are put forward for controlling and removing MPs from the environment.21
Staphylococcus aureus Enterotoxin Sensitization Without Aeroallergen Sensitization: An Important Severe Asthma Phenotype
No full text30623063111
Packaging of Ultra-dynamic Photonic Switches and Transceivers for Integration into 5G Radio Access Network and Datacenter Sub-systems
No full text742747We report the development of a fully non-blocking optical switch fabric, enabling a deterministic and dynamic network infrastructure. Focus is on scalable photonic integration and packaging technologies required to develop a low-cost switch fabric, including micro-transfer-printing of amplifiers, FOWLP for dense photonic-electronic integration, and optical/thermal packaging solutions on IC-substrates
Towards Solving the Blockchain Trilemma: An Exploration of Zero-knowledge Proofs
No full textResearch on blockchain has found that the technology is no silver bullet compared to traditional data structures due to limitations regarding decentralization, security, and scalability. These limitations are summarized in the blockchain trilemma, which today represents the greatest barrier to blockchain adoption and applicability. To address these limitations, recent advancements by blockchain businesses have focused on a new cryptographic technique called "Zero-knowledge proofs". While these primitives have been around for some time and despite their potential significance on blockchains, not much is known in information systems research about them and their potential effects. Therefore, we employ a multivocal literature review to explore this new tool and find that although it has the potential to resolve the trilemma, it currently only solves it in certain dimensions, which necessitates further attention and research
THE THERMOELASTIC STRESSES DURING LASER ANNEALING OF TITANIUM DIOXIDE ON A SAPPHIRE SUBSTRATE ТЕРМОУПРУГИЕ НАПРЯЖЕНИЯ ПРИ ЛАЗЕРНОМ ОТЖИГЕ ДИОКСИДА ТИТАНА НА САПФИРОВОЙ ПОДЛОЖКЕ
No full text100110In order to analyze the technique of laser annealing of titanium dioxide films on sapphire substrates and to optimize the film properties, a thermomechanical model of this technique has been considered. The model allowed us to monitor and vary the values of thermoelastic stresses in the film-substrate structures caused by changes of film annealing technological parameters such as the laser power, the film thickness, the pulse duration, the speed of laser emission, etc. The temperature field under the laser beam was simulated and then the stresses were analyzed using the thermomechanical finite element model. The simulation results showed an important role of the TiO2 film-to-substrate thickness ratio. The optimal combination of technological parameters was selected to prevent formation of cracks and other defects in the films.15
Integrated microelectrode pore cavity device in silicon (111)
No full textWe present a novel approach for the fabrication of single pore microcavities in silicon (111) based on Silicon-on-Insulator substrates and a combination of optical and electron-beam lithography, reactive ion etching and anisotropic wet etching techniques. Using a dedicated sequence of physical vapor deposition, electroplating and surface chemical oxidation, a silver/silver chloride (Ag/AgCl) reference bottom electrode was integrated into the cavity. We have fabricated cavities of volume ∼180 fl terminated at their top with silicon-nitride membranes featuring a single access pore of diameter 150-500 nm, each. Scanning electron microscopy revealed the cavity structure to comprise a hexagonal geometry top silicon nitride membrane and a triangular bottom plane. Atomic force microscopy analysis was performed on the AgCl surface, showing a root-mean-square surface roughness of 43.5 nm, hence resulting in a favorable high surface area of the electrode. We fully characterized our cavities filled with potassium chloride electrolyte solutions in electrical measurements to verify functionality of the integrated reference electrodes. Measured ion currents were stable over 1 d and scaled properly with pore diameter and salt concentration. We suggest our device to serve as platform for the controlled investigation of (bio-) electrochemical processes in smallest confined volumes.36
#135 Back to black? Why big oil's exit from renewables isn't the end of the energy transition
No full textIn dieser Folge spricht Julius mit Michael Liebreich, dem Gründer von Bloomberg New Energy Finance und einer der weltweit führenden Stimmen zur Zukunft der Energie. Gemeinsam erkunden sie, warum die Geschichte der Energiewende noch lange nicht auserzählt ist - und warum es echte Gründe für Optimismus gibt
Impact of the Ferroelectric Stack Lamination in Si Doped Hafnium Oxide (HSO) and Hafnium Zirconium Oxide (HZO) Based FeFETs: Toward High-Density Multi-Level Cell and Synaptic Storage
No full text344369A multi-level cell (MLC) operation as a 1–3 bit/cell of the FeFET emerging memory is reported by utilizing optimized Si doped hafnium oxide (HSO) and hafnium zirconium oxide (HZO) based on ferroelectric laminates. An alumina interlayer was used to achieve the thickness independent of the HSO and HZO-based stack with optimal ferroelectric properties. Various split thicknesses of the HSO and HZO were explored with lamination to increase the FeFET maximum memory window (MW) for a practical MLC operation. A higher MW occurred as the ferroelectric stack thickness increased with lamination. The maximum MW (3.5 V) was obtained for the HZO-based laminate; the FeFETs demonstrated a switching speed (300 ns), 10 years MLC retention, and 104 MLC endurance. The transition from instant switching to increased MLC levels was realized by ferroelectric lamination. This indicated an increased film granularity and a reduced variability through the interruption of ferroelectric columnar grains. The 2–3 bit/cell MLC levels and maximum MW were studied in terms of the size-dependent variability to indicate the impact of the ferroelectric area scaling. The impact of an alumina interlayer on the ferroelectric phase is outlined for HSO in comparison to the HZO material. For the same ferroelectric stack thickness with lamination, a lower maximum MW, and a pronounced wakeup effect was observed in HSO laminate compared to the HZO laminate. Both wakeup effect and charge trapping were studied in the context of an MLC operation. The merits of ferroelectric stack lamination are considered for an optimal FeFET-based synaptic device operation. The impact of the pulsing scheme was studied to modulate the FeFET current to mimic the synaptic weight update in long-term synaptic potentiation/depression.2
SHORT-TERM PREDICTION OF ELECTRIC VEHICLE CHARGING STATION AVAILABILITY USING CASCADED MACHINE LEARNING MODELS
No full text7885Driving long distances with battery electric vehicles is becoming possible thanks to increasing battery capacities and a growing network of fast-charging stations. During peak usage hours, multiple users may require recharging, thereby exceeding available charge points resulting in a queue. An algorithm is necessary to predict when a charging station is likely to be occupied and how long the waiting times at such a station would be to avoid such waiting times. This paper presents a methodology to cascade two machine-learning models to create such an algorithm. The first of these submodels predicts the likelihood that a current occupant is still at the charge point for any time in the future. It is implemented by training an ensemble learner with past charge events, thus learning station-specific and general usage characteristics. The second submodel predicts the probability of new visitors coming to the station and the occupation probability. Both achieve high accuracies in their respective domains. By mathematically combining both models, it is possible to construct an overarching model able to predict future charging station occupation likelihood based on the current occupation level of the station
A pplication of machine learning methods for process optimization in electronic packaging processes
No full text279284E poxy resins are commonly used as encapsulation materials in electronic packaging processes. F luctuations in the materials lead to both changes in processability and to varying quality. Ideally, these variations should be identified, and measures taken as quickly as possible to reduce scrap parts and thus costs. A promising optimization approach for encapsulation processes are machine learning models, which have already shown good results in quality predictions, especially for injection molding. Subsequent quality measurements are avoided with good quality prediction models. W ith this type of models, not only predictions can be made, but also optimal parameter combinations can be found. In this paper, models for predicting quality criteria warpage and residual enthalpy of the epoxy molding compound were set up, trained and validated. T ime series of in-situ sensors were used, from which relevant features were extracted and which, together with machine parameters, provide a dataset for prediction. T he most promising prediction models are random forest regression and gradient boosting regression. T hey predict warpage with an accuracy of 90 % to 91 % and the residual enthalpy with an accuracy of 95 % . Subsequently, optimization models of the machine parameters were set up. All relevant target variables were considered in a cost function, through the minimization of which an optimal parameter set was found. T he gradient boosted tree and Bayesian optimization were determined to be the most promising models, as they lead to the lowest values of the respective cost function