Search Results (73)

Modern agriculture has to alleviate extremes in water demand and/or water waste. In this regard, this work showcases how soil moisture instruments can be combined with low-end microcontrollers, energy-efficient communication protocols, single-board computers, flow and pressure sensors, and purpose-built actuators to form a synergistic platform able to generate and study realistic irrigation scenarios. These scenarios, potentially emulating anomalies such as clogged emitters or pipe leaks with a satisfactory time granularity of a few minutes, provide valuable data that pave the way for the creation of intelligent models intercepting water misuse events and/or irrigation failures. The proposed system utilizes widely available, well-documented, low-cost components to form a functioning whole which is optimized for outdoor, low-power, low-maintenance and long-term operation and is accessible remotely via typical end-user devices. Two drip irrigation points were set up, each having a TEROS 12 and a TEROS 10 instrument placed at different depths, while a prototype water flow/pressure control and report system was developed. All modules sent data in real time, via LoRa, to a central node implemented using a Raspberry Pi for further processing and to make them widely available via common network infrastructures, also provisioning for remote scenario invocation. The system does not claim to achieve specific irrigation water savings, but it contributes to maintaining/increasing the benefits of modern irrigation practices (such as drip irrigation). This goal is served by emulating a wide variety of irrigation events and by gathering and studying the corresponding data. These multimodal data are collected at a frequency of a few minutes, reflecting key irrigation-specific parameters with an accuracy better than or equal to 3%. The exact steps for specific hardware and software component interoperation are clearly explained, allowing other teams of researchers and/or university educators worldwide to be inspired and benefit from platform replication. Full article

Cork oak is a strong emitter of volatiles, namely monoterpenes, which are important precursors of secondary air pollutants. Past studies have revealed distinct chemotypes in emitting as well as non-emitting individuals. Promoting non-emitters in afforestation and urban greening could improve air quality, but their rarity suggests that they are less resilient. To gain insight into this, we screened natural descendants from two non-emitting cork oaks for emissions and ecophysiological traits (CO₂/H₂O-gas exchange variables, budburst date, growth) and tested whether emitting and non-emitting descendants differ in their resistance to temperature and light fluctuations (sun-flecks). Both half-sib populations were composed of the same chemotypes in similar frequencies, comprising 32% of non-emitters and 50 and 18% of two emitting chemotypes with overall moderate emission rates. Based on this distribution, we identified an inheritance mode and compared it with the chemotype frequency of the mother population. In terms of ecophysiological traits, all chemotypes performed similarly, and non-emitters were as resistant to sun-flecks as emitters. We conclude that the chemotypes in emitters reflect a common polymorphism in monoterpene-emitting plants that is not related to adaptive selection. We also conclude that non-emission is heritable and that its phenotype should be evaluated in reforestation studies. Full article

The giant atom paradigm, where a single quantum emitter couples to a continuum at multiple discrete points, has enabled unprecedented control over light-matter interactions, including decoherence-free subspaces and chiral emission. However, realizing these non-local effects beyond the microwave regime remains a significant challenge due to the diffraction limit. Here, we theoretically propose a photonic analog of giant atoms operating at optical frequencies, utilizing a quantum emitter resonantly coupled to a pair of spatially separated single-mode cavities interacting with a common 1D photonic continuum. By rigorously deriving the effective non-Hermitian Hamiltonian and integrating out the bath degrees of freedom, we demonstrate that the interference between cavity-mediated emission pathways leads to the formation of robust Bound States in the Continuum (BICs). These interference-induced dark states allow for the infinite trapping of excitation within the emitter-cavity subsystem, effectively shielding it from radiative decay. Our results extend the giant atom toolbox to the optical domain, offering a scalable architecture for integrated quantum photonics and quantum interconnects. Full article

This paper introduces an enhanced bandgap reference (BGR) design, addressing the shortcomings of traditional circuits, such as significant temperature drift, limited power-supply rejection, and inadequate load-driving capacity. The proposed design incorporates a symmetric folded common-emitter–common-base BJT amplifier with MOS-assisted biasing, employed in the proposed BGR, enforcing branch voltage symmetry to effectively suppress intrinsic offset caused by structural mismatch. By reducing the amplifier input offset, the circuit achieves improved reference voltage stability, a lower temperature coefficient (TC), and an enhanced power-supply rejection ratio (PSRR). Additionally, a negative-feedback adaptive current-adjustment driver is implemented to dynamically adjust the output current in response to real-time load changes. This method bolsters the load-driving capability and maintains a stable reference output across varying load conditions. The circuit was simulated using a 0.18 μm BCD process, revealing that with a 3.3 V supply voltage, the BGR produces a stable output voltage of 2.5 V, with a TC of $2.372\times {10}^{-6}$ °C⁻¹. The simulated PSRR is −114.2 dB at DC and −62.07 dB at 1 kHz. Moreover, under a 3.3 V supply, sweeping the load capacitance from 0.1 μF to 100 μF demonstrates that the reference voltage remains consistently regulated at 2.5 V, confirming its excellent load tolerance and output stability. Full article

The historical peak in CO₂ emissions has intensified global environmental concerns, urging the identification of key determinants. While economic drivers are well-documented, political dimensions—especially democracy and institutional quality—are increasingly emphasized. However, the role of freedom of association and organization (AOF), a core democratic element, remains largely unexamined in this context. This study fills this gap by analyzing the impact of AOF on CO₂ emissions in the top 20 emitter countries from 2006 to 2022. The selection of these countries enables a focused assessment of the world’s primary polluters, ensuring high policy relevance. Using second-generation panel estimators, the Augmented Mean Group and the Common Correlated Effects Mean Group estimators, the analysis accounts for heterogeneity and cross-sectional dependence. Robustness is tested using the CS-ARDL method, confirming the stability of results. Empirical findings show that higher levels of AOF significantly reduce CO₂ emissions. Income and energy consumption increase emissions, while the effect of trade openness is statistically insignificant. These results suggest that strengthening associational freedoms can offer a dual benefit: advancing democratic norms and achieving environmental goals. Full article

Radio Frequency Machine Learning (RFML) has in recent years become a popular method for performing a variety of classification tasks on received signals. Among these tasks is Specific Emitter Identification (SEI), which seeks to associate a received signal with the physical emitter that transmitted it. Many different model architectures, including individual classifiers and ensemble methods, have proven their capabilities for producing high accuracy classification results when performing SEI. Though the works studying different model architectures report on successes, there is a notable absence regarding the examination of systemic failures and negative traits associated with learned behaviors. This work studies those failure patterns for a 64-radio SEI classification problem by isolating common patterns in incorrect classification results across multiple model architectures and two distinct control variables: Signal-to-Noise Ratio (SNR) and the quantity of training data utilized. This work finds that many of the RFML-based models devolve to selecting from amongst a small subset of classes (≈10% of classes) as SNRs decrease and that observed errors are reasonably consistent across different SEI models and architectures. Moreover, our results validate the expectation that ensemble models are generally less brittle, particularly at a low SNR, yet they appear not to be the highest-performing option at a high SNR. Full article

Although the transition to electric vehicles (EVs) is well underway and expected to continue in global car markets, most vehicles on the world’s roads will be powered by internal combustion engine vehicles (ICEVs) and fossil fuels for the foreseeable future, possibly well past 2050. Thus, good environmental performance and effective emission control of ICE vehicles will continue to be of paramount importance if the world is to achieve the stated air and climate pollution reduction goals. In this study, we review 228 publications and identify four main issues confronting these objectives: (1) cheating by vehicle manufacturers, (2) tampering by vehicle owners, (3) malfunctioning emission control systems, and (4) inadequate in-service emission programs. With progressively more stringent vehicle emission and fuel quality standards being implemented in all major markets, engine designs and emission control systems have become increasingly complex and sophisticated, creating opportunities for cheating and tampering. This is not a new phenomenon, with the first cases reported in the 1970s and continuing to happen today. Cheating appears not to be restricted to specific manufacturers or vehicle types. Suspicious real-world emissions behavior suggests that the use of defeat devices may be widespread. Defeat devices are primarily a concern with diesel vehicles, where emission control deactivation in real-world driving can lower manufacturing costs, improve fuel economy, reduce engine noise, improve vehicle performance, and extend refill intervals for diesel exhaust fluid, if present. Despite the financial penalties, undesired global attention, damage to brand reputation, a temporary drop in sales and stock value, and forced recalls, cheating may continue. Private vehicle owners resort to tampering to (1) improve performance and fuel efficiency; (2) avoid operating costs, including repairs; (3) increase the resale value of the vehicle (i.e., odometer tampering); or (4) simply to rebel against established norms. Tampering and cheating in the commercial freight sector also mean undercutting law-abiding operators, gaining unfair economic advantage, and posing excess harm to the environment and public health. At the individual vehicle level, the impacts of cheating, tampering, or malfunctioning emission control systems can be substantial. The removal or deactivation of emission control systems increases emissions—for instance, typically 70% (NO_x and EGR), a factor of 3 or more (NO_x and SCR), and a factor of 25–100 (PM and DPF). Our analysis shows significant uncertainty and (geographic) variability regarding the occurrence of cheating and tampering by vehicle owners. The available evidence suggests that fleet-wide impacts of cheating and tampering on emissions are undeniable, substantial, and cannot be ignored. The presence of a relatively small fraction of high-emitters, due to either cheating, tampering, or malfunctioning, causes excess pollution that must be tackled by environmental authorities around the world, in particular in emerging economies, where millions of used ICE vehicles from the US and EU end up. Modernized in-service emission programs designed to efficiently identify and fix large faults are needed to ensure that the benefits of modern vehicle technologies are not lost. Effective programs should address malfunctions, engine problems, incorrect repairs, a lack of servicing and maintenance, poorly retrofitted fuel and emission control systems, the use of improper or low-quality fuels and tampering. Periodic Test and Repair (PTR) is a common in-service program. We estimate that PTR generally reduces emissions by 11% (8–14%), 11% (7–15%), and 4% (−1–10%) for carbon monoxide (CO), hydrocarbons (HC), and oxides of nitrogen (NO_x), respectively. This is based on the grand mean effect and the associated 95% confidence interval. PTR effectiveness could be significantly higher, but we find that it critically depends on various design factors, including (1) comprehensive fleet coverage, (2) a suitable test procedure, (3) compliance and enforcement, (4) proper technician training, (5) quality control and quality assurance, (6) periodic program evaluation, and (7) minimization of waivers and exemptions. Now that both particulate matter (PM, i.e., DPF) and NO_x (i.e., SCR) emission controls are common in all modern new diesel vehicles, and commonly the focus of cheating and tampering, robust measurement approaches for assessing in-use emissions performance are urgently needed to modernize PTR programs. To increase (cost) effectiveness, a modern approach could include screening methods, such as remote sensing and plume chasing. We conclude this study with recommendations and suggestions for future improvements and research, listing a range of potential solutions for the issues identified in new and in-service vehicles. Full article

Applying poor-quality water in drip irrigation has become increasingly common to address agricultural water scarcity. However, emitter clogging remains a critical challenge that limits the widespread adoption of this technology. Currently, the mechanism of emitter clogging under poor-quality water conditions remains insufficiently explored. This study investigates the distribution and accumulation of clogging substances within drip irrigation emitters under three water conditions: saline water, Yellow River water, and a 1:1 mixture of both, at clogging degrees of 5%, 20%, and 50% (i.e., the flow rate reaches 95%, 80%, 50% of the rated flow). The results showed that when clogging reached 20%, Yellow River water led to the highest clogging volume (i.e., the total volume of clogging substance in the flow channel, 1.77 mm³), while at 50%, saline water resulted in the highest clogging volume (5.11 mm³), while the use of blended water improved the clogging situation. Under different water conditions, clogging substances mainly formed on the upstream and downstream faces of the flow channel, accounting for 23.9–31.8% and 9.3–32.4% of the total volume, respectively. With higher clogging levels, the proportion of clogging substances on the downstream face increased significantly, while other areas showed minimal change. The volume of clogging substances was more pronounced at the front of the flow channel than at the back across the entire length, except at the 20% clogging degree for Yellow River water. At 5% clogging, the largest difference in clogging volume was observed with Yellow River water, while at 50%, the largest difference occurred with blended water. This research provides critical insights into the impact of poor-quality water on emitter clogging and suggests that the use of blending water, gradually varying channel structure, and increasing the arc of clogging faces can effectively alleviate clogging and enhance drip irrigation efficiency. Full article

This study addresses the critical challenge of performing a detailed calculation of energy savings in buildings by implementing suitable actions aiming at reducing greenhouse gas emissions. Given the high energy consumption of buildings’ space heating systems, optimizing their performance is crucial for reducing their overall primary energy demand. Unfortunately, the calculations of such savings are often based on extremely simplified methods, neglecting the dynamics of the emitters installed inside the buildings. These approximations may lead to relevant errors in the estimation of the possible energy savings. In this framework, the present study presents a novel 0-dimensional capacitive model of a radiator, the most common emitter used in residential buildings. The final scope of this paper is to integrate such a novel model within the TRNSYS 18simulation environment, performing a 1-year simulation of the overall building-space heating system. The radiator model is developed in MATLAB 2024b and it carefully considers the impact of surface area, inlet temperature, and flow rate on the radiator performance. Moreover, the dynamic heat transfer rate of the capacitive radiator is compared with the one returned by the built-in non-capacitive model available in TRNSYS, showing that neglecting the capacitive effect of radiators leads to an incorrect estimation of the heating consumption. During the winter season, with a heating system turned on from 8 a.m. to 4 p.m. and from 6 p.m. to 8 p.m., the thermal energy is underestimated by roughly 20% with the commonly used non-capacitive model. Full article

Frequency-response analysis is critical in circuit design. Frequency response encodes crucial information, like gain, accuracy, bandwidth, response time, phase shift, stability, and more. Unfortunately, existing methods are either algebraic and obscure or approximations with inaccuracies. So applying them to more complex circuits is often arduous or unreliable. This paper proposes recursive shunt-circuit transformations: a simple, rigorous, and insightful analytical method for conceptualizing and designing electronic circuits. The method asserts that (a) each equivalent capacitance shunts away its parallel resistance past its RC frequency. This (b) decreases the gain (induces a pole) and (c) changes the circuit. (d) The next dominant capacitance shunts its parallel resistance past the next pole and so on until all remaining capacitances shunt their parallel resistances past the poles they establish. The method also asserts that (e) bypass capacitances increase gain (induce zeros) and (f) cross-amp capacitances couple stages and poles. By applying this method and concepts, designers can (i) simplify an arbitrarily complex circuit into simpler coupled/decoupled stages and (ii) determine and manage poles and zeros with insight. This method was applied to design and analyze single- and multi- stage amplifier circuits and results were benchmarked against traditional methods and NGSPICE simulations, demonstrating its accuracy and broad applicability. Full article

In this paper, a silicon carbide (SiC) phototransistor based on an open-base structure was fabricated and used as a radiation detector. In contrast to the exposed and thin sensitive region of traditional photo detectors, the sensitive region of the radiation detector was much thicker (30 μm), ensuring the high energy deposition of radiation particles. The response properties of the fabricated SiC npn radiation detector were characterized by high-energy X-ray illumination with a maximum X-ray photon energy of 30 keV. The SiC npn detector featured stable and clear response to the X-ray within 0.0766 Gy∙s⁻¹ to 0.766 Gy∙s⁻¹ below 300 V. Due to to the low leakage current of less than 1 nA and the fully depleted sensitive region, the bipolar-transistor-modeled SiC npn detector exhibited a clear common-emitter current gain of 5.85 at 200 V (under 0.383 Gy∙s⁻¹), where the gain increased with bias voltage due to the Early effect and reached 7.55 at 300 V. In addition, the transient response of the SiC npn detector revealed a longer delay time than the SiC diode of the same size, which was associated with the larger effective capacitance of the npn structure. The npn detector with internal gain showed great potential in radiation detection. Full article

Nano-scale vacuum transistors (NVCTs) based on field emission have the potential to operate at high frequencies and withstand harsh environments, such as radiation, high temperatures, and high power. However, they have demonstrated instability and failures over time. To achieve high currents from NVCTs, these devices are typically fabricated in large-scale arrays known as field emitter arrays (FEAs), which share a common gate, cathode, and anode. Consequently, the measured currents come from the entire array, providing limited information about the emission characteristics of individual tips. Arrays can exhibit nonuniform emission behavior across the emitting area. A phosphor screen can be used to monitor the emission pattern of the array. Additionally, visible damage can occur on the surface of the FEAs, potentially leading to the destruction of the gate and emitters, causing catastrophic failure of the FEAs. To monitor damage while operating the device, an ITO-coated glass anode, which is electrically conductive and visible-light-transparent, can be used. In this work, a method was developed to automatically monitor the emission pattern of the emitters and the changes in surface morphology while operating the devices and collecting electrical data, providing real-time information on the failure sequence of the FEAs. Full article

The research on boron/nitrogen (B/N)-based multiresonance thermally activated delayed fluorescence (MR-TADF) emitters has been a prominent topic due to their narrowband emission and high luminous efficiency. However, devices derived from the common types of narrowband TADF materials often experience an efficiency roll-off, which could be ascribed to their relatively slow triplet–singlet exciton interconversion. Since inserting the heavy Se atom into the B/N scheme has been a proven strategy to address the abovementioned issues, herein, extensive density functional theory (DFT) and time-dependent DFT (TD-DFT) simulations have been employed to explore the effects of the structural modification on a series of structurally modified selenium-doped derivatives. Furthermore, the two-layered ONIOM (QM/MM) model has been employed to study the pressure effects on the crystal structure and photophysical properties of the pristine CzBSe. The theoretical results found that the introduced tert-butyl units in Cz-BSeN could result in a shorter charge transfer distance and smaller reorganization energy than the parent CzBSe. In contrast to directly incorporating the o-carborane (Cb) unit to CzBSe, incorporating the bridged phenyl units is important in order to achieve narrowband emissions and high luminous efficiency. The lowest three triplet excited states of CzBSe, Cz-BSeN and PhCb-BSeN all contribute to their triplet–singlet exciton conversions, resulting in a high utilization of triplet excitons. The pressure has an evident influence on the photophysical properties of the aggregated CzBSe and is favored for obtaining narrowband emissions. Our work is promised to provide a feasible strategy for designing selenium-doped derivatives with narrowband emissions and rapid triplet–singlet exciton interconversions. Full article

GDP is a common and essential indicator for evaluating a country’s overall economy. However, environmental issues may be overlooked in the pursuit of GDP growth for some countries. It may be beneficial to adopt more sustainable criteria for assessing economic health. In this study, green GDP (GGDP) is discussed using mathematical approaches. Multiple dataset indicators were selected for the evaluation of GGDP and its impact on climate mitigation. The k-means clustering algorithm was utilized to classify 16 countries into three distinct categories for specific analysis. The potential impact of transitioning to GGDP was investigated through changes in a quantitative parameter, the climate impact factor. Ridge regression was applied to predict the impact of switching to GGDP for the three country categories. The consequences of transitioning to GGDP on the quantified improvement of climate indicators were graphically demonstrated over time on a global scale. The entropy weight method (EWM) and TOPSIS were used to obtain the value. Countries in category 2, as divided by k-means clustering, were predicted to show a greater improvement in scores as one of the world’s largest carbon emitters, China, which belongs to category 2 countries, plays a significant role in global climate governance. A specific analysis of China was performed after obtaining the EWM-TOPSIS results. Gray relational analysis and Pearson correlation were carried out to analyze the relationships between specific indicators, followed by a prediction of CO₂ emissions based on the analyzed critical indicators. Full article

Organic upconversion devices (OUDs) are a class of technology that convert low-energy infrared (IR) photons into high-energy visible photons, offering extensive application prospects in fields such as bioimaging, photovoltaics, and display technologies. In recent years, organic materials-based upconversion technology has attracted considerable attention and research interest due to its unique advantages in molecular design, material diversity, and flexible device fabrication. An up-conversion imager consists of the organic photosensitive layer as the sensitizer which is used for absorbing infrared light and the active layers of the organic light-emitting diodes (OLEDs) as emitters which are used for displaying visible light. Under the effect of their common, the incident IR light is converted to visible light. Here, we review the recent progress in the field of organic upconversion materials, explain their performance and characterization, and discuss the challenges and prospects. Full article