Search Results (19)

From 31 August 2022 to early 2024, the City of Chicago welcomed nearly 40,000 migrants. Chicago had designated itself as a sanctuary city nearly 40 years ago and has since been a popular destination for migrants, accepting large numbers in other periods throughout its history. However, the influx during the period 2022–2024 was unique because of the large amounts of resources local and federal governments dedicated to settling these individuals. Immigrant benefits varied over this period but peaked at $15,000 per family, which did not include services offered by local churches and private organizations. In this study, log-linear multiple regression was employed to determine the impact subsidies can have on the local rental real estate market. According to the study findings, rental real estate rates increased by up to 5.6% in response to subsidization of migrant housing. Additionally, neighborhoods that were adjacent to migrant shelters experienced the greatest additional increase of 29.96%. In addition to the rapidity with which rental real estate pricing can respond to subsidies and policy shifts, the study findings demonstrate the financial benefits that can accrue to real estate owners and managers who participate in the rental marketplace with subsidization. Full article

Aquamarine, a popular variety of blue beryl, faces challenges in market valuation due to its reliance on subjective color assessment. This study investigates the coloration mechanism and establish a quantitative framework for assessing its color based on spectral and chromaticity analysis. We utilized electron probe microanalysis, ultraviolet-visible-near-infrared spectroscopy, laser Raman spectroscopy, and fiber optic spectroscopy to examine Brazilian aquamarine samples with varying blue intensities. The results indicate that the samples have high alkali metal (Na, K) content and low V/Cr content, consistent with the characteristics of high-alkali beryl. Ultraviolet spectroscopy reveals that the Fe³⁺-Fe²⁺ interaction (absorption at 620 nm) is the primary cause of blue coloration, while in deep blue samples, absorption at 956 nm decreases. Raman shifts (317 cm⁻¹, 392 cm⁻¹ Al-O bonds) correlate with TFeO content and chromaticity b value higher TFeO content corresponds to smaller Al–O peak shifts, and larger shifts are associated with higher b values (yellow hue). Specifically, increasing TFeO content leads to a shift of the Al-O Raman peak towards higher wavenumbers, and the magnitude of this shift is negatively correlated with the TFeO level. Based on hue angle (H) and saturation (S), we propose a classification method: “Light Blue” (H: 140–170, S ≤ 15), “Sky Blue” (H: 170–200, 15 < S ≤ 25), “Ocean Blue” (H: 200–230, 25 < S ≤ 35), and “Deep Blue” (H > 230, S > 35). This system provides a scientific basis for the quality assessment and market valuation of aquamarine. Full article

We discuss the spread of epidemics caused by two viruses which cannot infect the same individual at the same time. The mathematical modeling of this epidemic leads to a kind of SIIRR model with two groups of infected individuals and two groups of recovered individuals. An additional assumption is that after recovering from one of the viruses, the individual cannot be infected by the other virus. The mathematical model consists of five equations which can be reduced to a system of three differential equations for the susceptible and for the recovered individuals. This system has analytical solutions for the case when one of the viruses infects many more individuals than the other virus. Cases which are more complicated than this one can be studied numerically. The theory is applied to the study of waves of popularity of an individual/groups of individuals or of an idea/group of ideas in the case of the presence of two opposite opinions about the popularity of the corresponding individual/group of individuals or idea/group of ideas. We consider two cases for the initial values of the infected individuals: (a) the initial value of the individuals infected with one of the viruses is much larger than the initial values of the individuals infected by the second virus, and (b) the two initial values of the infected individuals are the same. The following effects connected to the evolution of the numbers of infected individuals are observed: 1. arising of bell-shaped profiles of the numbers of infected individuals; 2. suppression of popularity; 3. faster increase–faster decrease effect for the peaks of the bell-shaped profiles; 4. peak shift in the time; 5. effect of forgetting; 6. window of dominance; 7. short-term win–long-term loss effect; 8. effect of the single peak. The proposed SIIRR model is used to build a mathematical theory of popularity waves where a person or idea can have positive and negative popularity at the same time and these popularities evolve with time. Full article

Background: Running is a popular physical activity known for its health benefits but also for a high incidence of lower-limb injuries. This study examined the effects of three biomechanical interventions—cadence adjustments, footwear modifications, and foot orthoses—on plantar pressure distribution and spatiotemporal running parameters. Methods: A quasi-experimental, repeated-measures design was conducted with 23 healthy recreational runners (mean age 25, mean BMI 22.5) who ran at least twice per week. Five conditions were tested: baseline (C0), increased cadence (C1), orthoses (C2), low-drop footwear (C3), and a combination of these (C4). Data were collected on a Zebris treadmill, focusing on rearfoot contact time, peak forces, and stride length. Results: Increasing cadence (C1) reduced rearfoot impact forces (−81.36 N) and led to a shorter stride (−17 cm). Low-drop footwear (C3) decreased rearfoot contact time (−1.89 ms) and peak force (−72.13 N), while shifting pressure toward the midfoot. Orthoses (C2) effectively redistributed plantar pressures reducing rearfoot peak force (−41.31 N) without changing stride length. The combined intervention (C4) yielded the most pronounced reductions in peak forces across the rearfoot (−183.18 N) and forefoot (−139.09 N) and increased midfoot contact time (+5.07 ms). Conclusions: Increasing cadence and low-drop footwear significantly reduced impact forces, improving running efficiency. Orthoses effectively redistributed plantar pressures, supporting individualized injury prevention strategies. These findings suggest that combining cadence adjustments, footwear modifications, and orthoses could enhance injury prevention and running efficiency for recreational runners. Full article

Electric vehicles (EVs) are rapidly replacing fossil-fuel-powered vehicles, creating a need for a fast-charging infrastructure that is crucial for their widespread adoption. This research addresses this challenge by improving the control of dual active bridge converters, a popular choice for high-power EV charging stations. A critical issue in EV battery charging is the smooth transition between charging stages (constant current and constant voltage) which can disrupt converter performance. This work proposes a novel feedforward control method using a combination of droop-based techniques combined with a sophisticated linear active disturbance rejection control system applied to a single-phase shift-modulated dual active bridge. This combination ensures a seamless transition between charging stages and enhances the robustness of the system against fluctuations in both input voltage and load. Numerical simulations using MATLAB/Simulink R2024a demonstrated that this approach not only enables smooth charging but also reduces the peak input converter current, allowing for the use of lower-rated components in the converter design. This translates to potentially lower costs for building these essential charging stations and faster adoption of EVs. Full article

This paper proposes a microwave rectifier designed for the popular 5G band, featuring impedance dispersion compensation and a cross-type impedance matching network. The rectifier has an ultra-high power conversion efficiency. The compensation network employs two parallel transmission lines to counteract the nonlinear shift of the diode input impedance caused by frequency variation. Additionally, the cross-over impedance matching network enhances matching and minimizes losses. After rigorous theoretical analysis and simulation, the rectifier is fabricated. Experimental results show significant conversion efficiency in the 5G band (across 4–6.5 GHz). At an input power of 12 dBm, the rectifier achieves more than 60% efficiency between 4.8 and 6.4 GHz and more than 70% between 5.2 and 6.2 GHz, with a peak efficiency of 78.1%. Moreover, the rectifier maintains more than 50% efficiency over a wide input power range of 5 to 14 dBm. Full article

Deep learning (DL) networks are a popular choice for short-term load forecasting (STLF) in the residential sector. Hybrid DL methodologies based on convolutional neural networks (CNNs) and long short-term memory networks (LSTMs) have a higher forecasting accuracy than conventional statistical STLF techniques for different types of single-household load series. However, existing load forecasting methodologies are often inefficient when a high load demand persists for a few hours in a day. Peak load consumption is explicitly depicted as a tail in the probability distribution function (PDF) of the load series. Due to the diverse and uncertain nature of peak load demands, DL methodologies have difficulty maintaining consistent forecasting results, particularly when the PDF of the load series has a longer tail. This paper proposes a multihousehold load forecasting strategy based on the collective moment measure (CMM) (which is obtained from the PDF of the load series), data augmentation, and a CNN. Each load series was compared and ordered through CMM indexing, which helped maintain a minimum or constant shifting variance in the dataset inputted to the CNN. Data augmentation was used to enlarge the input dataset and solve the existing data requirement issues of the CNN. With the ordered load series and data augmentation strategy, the simulation results demonstrated a significant improvement in the performance of both single-household and multihousehold load forecasting. The proposed method predicts day-ahead multihousehold loads simultaneously and compares the results based on a single household. The forecasting performance of the proposed method for six different household groups with 10, 20, 30, 50, 80, and 100 household load series was evaluated and compared with those of existing methodologies. The mean absolute percentage error of the prediction results for each multihousehold load series could be improved by more than 3%. This study can help advance the application of DL methods for household load prediction under high-load-demand conditions. Full article

Cobalt(II) thiocyanate-based tests are routinely used to screen cocaine products, with the formation of a blue species interpreted as a positive response. Two popular candidates for the origin of the blue color are an ionic coordination compound, frequently referred to as an ion pair, of the general form (HL)₂[Co(SCN)₄] or the coordination compound [CoL₂(SCN)₂], where L represents select nitrogenous bases. Given the high number of nitrogenous bases documented to yield false positives for cobalt(II) thiocyanate-based tests, a reasonable hypothesis is that both candidates are possible but their preferential formation depends on the specific nitrogenous bases screened. This hypothesis was tested through the crystallographic and spectroscopic analysis of reaction products of cocaine hydrochloride, lidocaine monohydrate hydrochloride, and benzimidazole exposed to a classic cobalt(II) thiocyanate reagent. Single-crystal X-ray diffraction revealed that the blue product isolated from benzimidazole test vessels is a coordination compound, with comparative ultraviolet–visible and Raman spectroscopy validating that blue precipitates collected from cocaine hydrochloride and lidocaine monohydrate hydrochloride reaction containers are ionic coordination compounds. Peaks corresponding to π-π* transitions in UV-vis at around 320 nm (cocaine hydrochloride: 320 nm, lidocaine hydrochloride: 323 nm) shift to a higher wavelength of 332 nm for the coordinated benzimidazole, and the broader d-d transitions at 550–630 nm show both a shift and change in envelope for benzimidazole coordinated with cobalt(II). The compound is a new polymorph of bis(benzimidazole)bis(thiocyanato-N)Cobalt(II), γ-[Co(Hbzim)₂(SCN)₂] (Hbzim = benzimidazole), and the differences in the intermolecular interactions to the two previous polymorphs were clarified by graph set analysis and Hirshfeld surface analysis. Furthermore, the coordination of aromatic nitrogen bases (such as benzimidazole) with Co(II) and aliphatic bases was compared by analyzing the Cambridge Structural Database, and the aromatic bases were found to have a shorter Co-N bond length compared to the aliphatic bases by around 0.02 Å. Full article

Piezoelectric materials are defined by their ability to display a charge across their surface in response to mechanical strain, making them great for use in sensing applications. Such applications include pressure sensors, medical devices, energy harvesting and structural health monitoring (SHM). SHM describes the process of using a systematic approach to identify damage in engineering infrastructure. A method of SHM that uses piezoelectric wafers connected directly to the structure has become increasingly popular. An investigation of a novel pitch-catch method of determining instrumentation quality of piezoelectric wafer active sensors (PWASs) used in SHM was conducted as well as an investigation into the effects of defects in piezoelectric sensors and sensor bonding on the sensor response. This pitch-catch method was able to verify defect-less instrumentation quality of pristinely bonded PWASs. Additionally, the pitch-catch method was compared with the electromechanical impedance method in determining defects in piezoelectric sensor instrumentation. Using the pitch-catch method, it was found that defective instrumentation resulted in decreasing amplitude of received and transmitted signals as well as changes in the frequency spectrums of the signals, such as the elimination of high frequency peaks in those with defects in the bonding layer and an increased amplitude of around 600 kHz for a broken PWAS. The electromechanical impedance method concluded that bonding layer defects increase the primary frequency peak’s amplitude and cause a downward frequency shift in both the primary and secondary frequency peaks in the impedance spectrum, while a broken sensor has the primary peak amplitude reduced while shifting upward and nearly eliminating the secondary peak. Full article

Reversible data hiding (RDH) techniques recover the original cover image after data extraction. Thus, they have gained popularity in e-healthcare, law forensics, and military applications. However, histogram shifting using a reversible data embedding technique suffers from low embedding capacity and high variability. This work proposes a technique in which the distribution obtained from the cover image determines the pixels that attain a peak or zero distribution. Afterward, adjacent histogram bins of the peak point are shifted, and data embedding is performed using the least significant bit (LSB) technique in the peak pixels. Furthermore, the robustness and embedding capacity are improved using the proposed dynamic block-wise reversible embedding strategy. Besides, the secret data are encrypted before embedding to further strengthen security. The experimental evaluation suggests that the proposed work attains superior stego images with a peak signal-to-noise ratio (PSNR) of more than 58 dB for 0.9 bits per pixel (BPP). Additionally, the results of the two-sample t-test and the Kolmogorov–Smirnov test reveal that the proposed work is resistant to attacks. Full article

Due to failures or even the absence of an electricity grid, microgrid systems are becoming popular solutions for electrifying African rural communities. However, they are heavily stressed and complex to control due to their intermittency and demand growth. Demand side management (DSM) serves as an option to increase the level of flexibility on the demand side by scheduling users’ consumption patterns profiles in response to supply. This paper proposes a demand-side management strategy based on load shifting and peak clipping. The proposed approach was modelled in a MATLAB/Simulink R2021a environment and was optimized using the artificial neural network (ANN) algorithm. Simulations were carried out to test the model’s efficacy in a stand-alone PV-battery microgrid in East Africa. The proposed algorithm reduces the peak demand, smoothing the load profile to the desired level, and improves the system’s peak to average ratio (PAR). The presence of deferrable loads has been considered to bring more flexible demand-side management. Results promise decreases in peak demand and peak to average ratio of about 31.2% and 7.5% through peak clipping. In addition, load shifting promises more flexibility to customers. Full article

The ever increasing popularity of Cloud and similar services pushes the demand for data centres, which have a high power consumption. In an attempt to increase the sustainability of the power generation, data centres have been fed by microgrids which include renewable generation—so-called ‘green data centres’. However, the peak load of data centres often does not coincide with solar generation, because demand mostly peaks in the evening. Shifting power to data centres incurs transmission losses; shifting the data transmission has no such drawback. We demonstrate the effectivity of computational load shifting between data centres located in different time zones using a case study that balances demands between three data centres on three continents. This study contributes a method that exploits the opportunities provided by the varied timing of peak solar generation across the globe, transferring computation load to data centres that have sufficient renewable energy whenever possible. Our study shows that balancing computation loads between three green data centres on three continents can improve the use of renewables by up to 22%. Assuming the grid energy does not include renewables, this amounts to a 13% reduction in CO₂ emissions. Full article

Balancing energy demand and supply will become an even greater challenge considering the ongoing transition from traditional fuel to electric vehicles (EV). The management of this task will heavily depend on the pace of the adoption of light-duty EVs. Electric vehicles have seen their market share increase worldwide; the same is happening in Portugal, partly because the government has kept incentives for consumers to purchase EVs, despite the COVID-19 pandemic. The consequent shift to EVs entails various challenges for the distribution network, including coping with the expected growing demand for power. This article addresses this concern by presenting a case study of an area comprising 20 municipalities in Northern Portugal, for which battery electric vehicles (BEV) sales and their impact on distribution networks are estimated within the 2030 horizon. The power required from the grid is estimated under three BEV sales growth deterministic scenarios based on a daily consumption rate resulting from the combination of long- and short-distance routes. A Monte Carlo computational simulation is run to account for uncertainty under severe EV sales growth. The analysis is carried out considering three popular BEV models in Portugal, namely the Nissan Leaf, Tesla Model 3, and Renault Zoe. Their impacts on the available power of the distribution network are calculated for peak and off-peak hours. The results suggest that the current power grid capacity will not cope with demand increases as early as 2026. The modeling approach could be replicated in other regions with adjusted parameters. Full article

Cryptocurrencies are a type of digital money meant to provide security and anonymity while using cryptography techniques. Although cryptocurrencies represent a breakthrough and provide some important benefits, their usage poses some risks that are a result of the lack of supervising institutions and transparency. Because disinformation and volatility is discouraging for personal investors, cryptocurrencies emerged hand-in-hand with the proliferation of online users’ communities and forums as places to share information that can alleviate users’ mistrust. This research focuses on the study of the interplay between these cryptocurrency forums and fluctuations in cryptocurrency values. In particular, the most popular cryptocurrency Bitcoin (BTC) and a related active discussion community, Bitcointalk, are analyzed. This study shows that the activity of Bitcointalk forum keeps a direct relationship with the trend in the values of BTC, therefore analysis of this interaction would be a perfect base to support personal investments in a non-regulated market and, to confirm whether cryptocurrency forums show evidences to detect abnormal behaviors in BTC values as well as to predict or estimate these values. The experiment highlights that forum data can explain specific events in the financial field. It also underlines the relevance of quotes (regular mechanism to response a post) at periods: (1) when there is a high concentration of posts around certain topics; (2) when peaks in the BTC price are observed; and, (3) when the BTC price gradually shifts downwards and users intend to sell. Full article

With the increase in local energy generation from Renewable Energy Sources (RESs), the concept of decentralized peer-to-peer Local Energy Market (LEM) is becoming popular. In this paper, a blockchain-based LEM is investigated, where consumers and prosumers in a small community trade energy without the need for a third party. In the proposed model, a Home Energy Management (HEM) system and demurrage mechanism are introduced, which allow both the prosumers and consumers to optimize their energy consumption and to minimize electricity costs. This method also allows end-users to shift their load to off-peak hours and to use cheap energy from the LEM. The proposed solution shows how energy consumption and electricity cost are optimized using HEM and demurrage mechanism. It also provides economic benefits at both the community and end-user levels and provides sufficient energy to the LEM. The simulation results show that electricity cost is reduced up to 44.73% and 28.55% when the scheduling algorithm is applied using the Critical Peak Price (CPP) and Real-Time Price (RTP) schemes, respectively. Similarly, 65.15% and 35.09% of costs are reduced when CPP and RTP are applied with demurrage mechanism. Moreover, 51.80% and 44.37% electricity costs reduction is observed when CPP and RTP are used with both demurrage and scheduling algorithm. We also carried out security vulnerability analysis to ensure that our energy trading smart contract is secure and bug-free against the common vulnerabilities and attacks. Full article