Search Results (59)

Background/Objectives: Food technology neophobia (FTN), defined as the reluctance to accept or consume foods produced with novel or emerging food technologies, represents a psychological barrier to the adoption of sustainable and innovative dietary practices. This cross-sectional study investigated the prevalence of food technology neophobia and its associated factors among Italian university students. Methods: A total of 1788 undergraduates from 13 universities completed a validated online questionnaire between February and October 2024. The instrument included the Food Technology Neophobia Scale (FTNS), environmental attitude items, and demographic and dietary questions. Results: The mean FTNS score was 51.2 ± 14.0, suggesting moderate levels of neophobia. Multivariate logistic regression identified several factors inversely associated with neophobia: male gender (OR = 0.73, p = 0.003), paternal university education (OR = 0.73, p = 0.024), studying in Northern Italy (OR = 0.64, p < 0.001), dietary supplement use (OR = 0.74, p = 0.003), and pro-environmental attitudes (OR = 0.97, p < 0.001). Conversely, being a commuter student was associated with increased neophobia (OR = 1.29, p = 0.031). Conclusions: These findings highlight the influence of socio-demographic, behavioral, and attitudinal factors on the acceptance of new food technologies. Tailored strategies are recommended to address FTN in specific subgroups, particularly among female, commuter, and Southern Italian students, to enhance receptivity to food innovation and support sustainable dietary transitions. Full article

Next-generation communication systems demand extreme spectral efficiency to handle ever-increasing data traffic. The combination of faster-than-Nyquist (FTN) signaling and reconfigurable intelligent surfaces (RISs) presents a promising solution to meet this demand. However, the aggressive time compression inherent to FTN signaling introduces severe and highly non-linear inter-symbol interference (ISI). This complex distortion is challenging for conventional linear equalizers and even for recurrent neural network (RNN)-based detectors, which can struggle to model long-range dependencies within the signal sequence. To overcome this limitation, this paper proposes a novel signal detection framework based on the transformer model. By leveraging its core multi-head self-attention mechanism, the transformer globally analyzes the entire received signal sequence at once. This enables it to effectively model and reverse complex ISI patterns by identifying the most significant interfering symbols, regardless of their position, leading to superior signal recovery. The simulation results validate the outstanding performance of the proposed approach. To achieve a target bit error rate (BER) of ${10}^{-4}$, the transformer-based detector shows a significant signal-to-noise ratio (SNR) gain of approximately 1.5 dB over a Bi-LSTM detector over 4 dB compared to the conventional FTN-RIS system, while maintaining a high spectral efficiency of nearly 2 bps/s/Hz. Full article

Faster-than-Nyquist (FTN) tight filtering introduces serious inter-symbol interference (ISI) impairment, leading to an insufficient compensation range for conventional IQ imbalance compensation algorithms. Furthermore, receiver (Rx) IQ imbalance and ISI impairments significantly increase the convergence cost required by the squared Gardner phase detector (SGPD) timing recovery algorithm to establish a timing synchronization loop. This paper proposes a joint Rx IQ compensation and timing recovery scheme. By embedding a two-stage IQ imbalance compensation algorithm into the timing recovery feedback loop, the proposed scheme could effectively estimate and compensate for Rx IQ imbalance. Meanwhile, thanks to the innovative scheme, which equalizes Rx IQ imbalance and ISI during the timing feedback loop, the convergence cost of timing recovery could be reduced compared with the conventional blind frequency domain (BFD) scheme. The simulation results of 128 GBaud polarization multiplexing (PM) 16-quadrature amplitude modulation (QAM) FTN wavelength division multiplexing (WDM) transmission systems demonstrate that the proposed scheme could bring about 14%, 12.5%, and 16.6% improvements in the compensation range for Rx IQ amplitude imbalance, phase imbalance, and skew, respectively, compared with the conventional one. Meanwhile, the convergence cost is reduced by at least 31% with a 0.9 acceleration factor. In addition, 40 GBaud PM-16QAM FTN experiment results show that the proposed scheme could bring about a 0.8 dB improvement in the optical signal noise ratio (OSNR) compared with the conventional BFD scheme. Full article

The land-use conversion of Masson pine forests to tea fields is extensively practiced across subtropical China, primarily driven by its economic benefit. However, the effects of this conversion on soil fungal communities and functional guilds are poorly understood. Herein, a field experiment was conducted in a Masson pine forest (F), a 5-year-old tea plantation without (FT-CK) fertilization or with (FT-N), and a 30-year-old tea plantation (FT-O) to assess the impact of Masson pine forest-to-tea conversion on soil fungal abundance, community structure, and functional guilds by using qPCR and high-throughput sequencing. Compared to F, fungal abundance significantly decreased by 95%, 68%, and 79% in FT-CK, FT-N, and FT-O, respectively, probably caused by the decreased total nitrogen content and habitat disruption. Fungal alpha diversity significantly increased in FT-N and FT-O compared to FT-CK. FT-O presented the highest percentages of Mortierella among treatments, which favours soil organic carbon accumulation. FUNGuild-based predictions showed that FT-CK and FT-N had higher relative abundances of plant pathogens than F and FT-O. FT-O presented the highest percentages of litter and soil saprotrophs but exhibited the lowest percentages of ectomycorrhizal fungi among treatments, likely driven by increased soil organic carbon, total nitrogen, and total phosphorus content. Our findings demonstrate that Masson pine forest-to-tea conversion significantly degrades soil fungal community and function, highlighting the urgent need for soil management strategies (e.g., organic amendments) to enhance soil health in tea agroecosystems. Full article

To enable highly reliable and spectrum-efficient vehicle-to-everything (V2X) communications under conditions with severe Doppler effects and rapidly time-varying channels, we propose a novel faster-than-Nyquist orthogonal time frequency space (FTN-OTFS) modulation scheme. In this scheme, FTN signaling is integrated with spectrally efficient frequency division multiplexing (SEFDM) within the OTFS framework, enabling a higher symbol-transmission density within a fixed time–frequency resource block and thus enhancing spectral efficiency without increasing the occupied bandwidth. An analytical input–output model is derived in both the delay–Doppler and time–frequency domains. To further enhance numerical stability, an improved detection algorithm called adaptive damping log-domain message-passing (ADL-MP) is developed for the proposed scheme. Simulation results demonstrate that the proposed scheme achieves robust and reliable performance in high-mobility scenarios and that the proposed algorithm consistently outperforms conventional methods in terms of bit error rate (BER) under both the extended vehicular A (EVA) model and the high-speed train (HST) scenario, confirming its effectiveness and superiority for V2X communications. Full article

Impaired renal function can influence biomarker levels through mechanisms involving blood–brain barrier integrity and clearance pathways; however, the impact of variations within normal renal function remains unclear. The main aim of this study was to determine whether adjustment for the specific level of renal function is necessary when renal function remains within physiological levels. We studied n = 183 patients (NID n = 122; other neurological diseases n = 39; somatoform controls n = 22) who underwent lumbar puncture at University Hospital Frankfurt. Serum and cerebrospinal fluid (CSF) levels of neurofilament light chain (NfL), glial fibrillary acidic protein (GFAP), total tau protein (tTAU), and ubiquitin C-terminal hydrolase-L1 (UCHL1) were measured using the single molecule array (SIMOA) technique. Estimated glomerular filtration rate (eGFR) correlated negatively with CSF GFAP (r = −0.217, p = 0.004) and serum NfL (r = −0.164, p = 0.032). Patients with impaired renal function exhibited higher CSF NfL (p = 0.036) and CSF GFAP (p = 0.026) levels. However, these findings did not remain significant after adjusting for BMI and age. Importantly, in patients with normal renal function, no significant correlations with eGFR and biomarker levels were observed after adjustment. Our findings indicate that serum and CSF concentrations of NfL, GFAP, tTAU, and UCHL1 are not significantly affected by fluctuations in physiological kidney function but emphasize the importance of considering comorbidities in impaired renal function when interpreting biomarker levels. Full article

FTN signalling is an effective communication method that achieves a high spectral efficiency. However, employing a symbol rate faster than the Nyquist rate disrupts the orthogonality between symbols, leading to unavoidable inter-symbol interference (ISI). To mitigate the effects of ISI, interference cancellation and signal detection processes are essential for FTN receivers. Conventional ISI reduction techniques often utilize trellis-based algorithms. However, as the number of states increases due to additional interference symbols, the complexity of these algorithms grows exponentially. To address this challenge, this paper explores a matrix computation-based interference cancellation technique tailored for FTN communication systems, aiming to significantly reduce the complexity of the ISI mitigation process. To execute ISI cancellation and signal detection more precisely, the proposed technique includes iterative interference cancellation and a signal detection process. When six interference symbols are considered, the complexity of the proposed technique is reduced by 97% compared with that of the conventional Viterbi algorithm. Furthermore, in the case of τ = 0.85, the performance of the proposed technique is about 1 dB better than that of the Viterbi algorithm at BER = ${10}^{-4}$. Full article

In recent years, ensuring communication security at the physical layer has become increasingly important due to the transmission of sensitive information over various networks. Traditional approaches to physical layer security often rely on artificial noise generation, which may not offer robust solutions against advanced interception techniques. This study addresses these limitations by proposing a novel security technique based on non-orthogonal signaling using Faster-than-Nyquist (FTN) signaling. Unlike conventional FTN methods that utilize fixed symbol intervals, the proposed technique employs variable symbol intervals encoded as secure information, shared only with legitimate receivers. This encoding enables effective interference cancellation and symbol detection at the receiver, while preventing eavesdroppers from deciphering transmitted signals. The performance of the proposed technique was evaluated using the DVB-S2X system, a practical digital video broadcasting standard. Simulation results demonstrated that the proposed method maintains smooth communication with minimal performance degradation compared to traditional methods. Furthermore, eavesdroppers were unable to decode the transmitted signals, confirming the enhanced security. This research presents a new approach to physical layer security that does not depend on generating artificial noise, offering a path to more secure and efficient communication systems. Full article

Compared with high spectrum efficiency faster-than-Nyquist (FTN) backbone network, an enhanced carrier phase recovery based on dual pilot tones is more sensitive to capital cost in FTN metropolitan areas as well as inter-datacenter optical networks. The use of distributed feedback (DFB) lasers is a way to effectively reduce the cost. However, under high symbol rate FTN systems, equalization-enhanced phase noise (EEPN) induced by a DFB laser with large linewidth will significantly deteriorate the system performance. What is worse, in FTN systems, tight filtering introduces inter-symbol interference so severe that the carrier phase estimation (CPE) algorithm of the FTN systems is more sensitive to EEPN, thus it will lead to a more serious cycle slip problem. In this paper, an enhanced carrier phase recovery based on dual pilot tones is proposed to mitigate EEPN and suppress cycle slip, in which the chromatic dispersion (CD)-aware Tx and LO laser phase noise is estimated, respectively. Offline experiments results under 40 Gbaud polarization multiplexing (PM) 16-quadrature amplitude modulation (QAM) FTN wavelength division multiplexing (FTN-WDM) systems at 0.9 acceleration factor, 5 MHz laser linewidth, and 500 km transmission demonstrate that the proposed algorithm could bring about 0.65 dB improvement of the required SNR for the normalized generalized mutual information of 0.9 compared with the training sequence-based cycle slip suppression carrier phase estimation (TS-CSS) algorithm. Full article

To mitigate inter-symbol interference (ISI) caused by Faster-than-Nyquist (FTN) technology in a multiple input multiple output (MIMO) optical wireless communication (OWC) system, we propose an ISI cancellation algorithm that combines multi-head self-attention (MHSA), a one-dimensional convolutional neural network (1D CNN), and bi-directional long short-term memory (Bi-LSTM). This hybrid network extracts data features using 1D CNN and captures sequential information with Bi-LSTM, while incorporating MHSA to comprehensively reduce ISI. We analyze the impact of antenna numbers, acceleration factors, wavelength, and turbulence intensity on the system’s bit error rate (BER) performance. Additionally, we compare the waveform graphs and amplitude–frequency characteristics of FTN signals before and after processing, specifically comparing sampled values of four-pulse-amplitude modulation (4PAM) signals with those obtained after ISI cancellation. The simulation results demonstrate that within the Mazo limit for selecting acceleration factors, our proposal achieves a 7 dB improvement in BER compared to the conventional systems without deep learning (DL)-based ISI cancellation algorithms. Furthermore, compared to systems employing a point-by-point elimination adaptive pre-equalization algorithm, our proposal exhibits comparable BER performance to orthogonal transmission systems while reducing computational complexity by 31.15%. Full article

Lung injury caused by respiratory infection is a major cause of hospitalization and mortality and a leading origin of sepsis. Sepsis-associated encephalopathy and delirium are frequent complications in patients with severe lung injury, yet the pathogenetic mechanisms remain unclear. Here, 70 female C57BL/6 mice were subjected to a single full-body-exposure with nebulized lipopolysaccharide (LPS). Neuromotor impairment was assessed repeatedly and brain, blood, and lung samples were analyzed at survival points of 24 h, 48 h, 72 h, and 96 h after exposure. qRT-PCR revealed increased mRNA-expression of TNFα and IL-1β 24 h and 48 h after LPS-exposure in the lung, concomitantly with increased amounts of proteins in bronchoalveolar lavage and interstitial lung edema. In the cerebral cortex, at 72 h and/or 96 h after LPS exposure, the inflammation- and activity-associated markers TLR4, GFAP, Gadd45b, c-Fos, and Arc were increased. Therefore, single exposure to nebulized LPS not only triggers an early inflammatory reaction in the lung but also induces a delayed neuroinflammatory response. The identified mechanisms provide new insights into the pathogenesis of sepsis-associated encephalopathy and might serve as targets for future therapeutic approaches. Full article

One of the ways to increase the volume of transmitted information is to increase the bit rate above the Nyquist barrier. However, an increase in bit rate in the case of FTN (Faster-Than-Nyquist) signals leads to an increase in energy costs for receiving information on channels with limited bandwidth, for example, in Digital Video Broadcasting satellite systems like DVB-S2/S2X. It is possible to minimize energy losses by using the processing algorithm “maximum likelihood sequence estimation”. However, the computational complexity of this algorithm is extremely high, which limits its use, especially in terrestrial mobile satellite terminals. We propose a new bit-by-bit decision feedback algorithm with maximum likelihood ratio estimation of subsequent symbols in the observation interval. This algorithm provides minimal energy costs comparable to the method “maximum likelihood sequence estimation” at speeds 2–3 times higher than the Nyquist barrier. At the same time, the complexity is two orders of magnitude less. It is shown by simulation for a channel with additive noise that energy losses in relation to the potential bit error rate (BER) are less than 4.5 dB. In the presence of Rayleigh fading, the application of the proposed algorithm makes it possible to provide the processing of FTN signals for double bit rates in urban areas with energy costs equal to 12 dB when using an equalizer. We give numerical estimations of the increase in computational complexity for the proposed processing algorithm. It is shown that an increase in the bit rate by 1.5 times leads to an increase in the computational complexity by more than an order of magnitude. The same conclusion can be reformulated in another form: for the proposed algorithm, each decibel of energy gain is achieved by increasing the number of computational operations by $1.5\times {10}^5$. It is experimentally shown that additional energy losses due to non-ideal phase and timing synchronization are no more than 1 dB when the proposed algorithm is applied in a fading channel. The energy costs in fading channels relative to a stationary channel for twice the Nyquist rate are equal to 13.8 dB when using an equalizer. Full article

Post-acute COVID-19 vaccination syndrome (PACVS) is a chronic disease triggered by SARS-CoV-2 vaccination (estimated prevalence 0.02%). PACVS is discriminated from the normal post-vaccination state by altered receptor antibodies, most notably angiotensin II type 1 and alpha-2B adrenergic receptor antibodies. Here, we investigate the clinical phenotype using a study registry encompassing 191 PACVS-affected persons (159 females/32 males; median ages: 39/42 years). Unbiased clustering (modified Jaccard index) of reported symptoms revealed a prevalent cross-cohort symptomatology of malaise and chronic fatigue (>80% of cases). Overlapping clusters of (i) peripheral nerve dysfunction, dysesthesia, motor weakness, pain, and vasomotor dysfunction; (ii) cardiovascular impairment; and (iii) cognitive impairment, headache, and visual and acoustic dysfunctions were also frequently represented. Notable abnormalities of standard serum markers encompassing increased interleukins 6 and 8 (>80%), low free tri-iodine thyroxine (>80%), IgG subclass imbalances (>50%), impaired iron storage (>50%), and increased soluble neurofilament light chains (>30%) were not associated with specific symptoms. Based on these data, 131/191 participants fit myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and simultaneously also several other established dysautonomia syndromes. Furthermore, 31/191 participants fit none of these syndromes. In conclusion, PACVS could either be an outlier of ME/CFS or a dysautonomia syndrome sui generis. Full article

Invasive dental procedures, such as wisdom teeth removal, have been identified as potential triggers for vascular events due to the entry of oral bacteria into the bloodstream, leading to acute vascular inflammation and endothelial dysfunction. This study presents the case of a 27-year-old healthy male who developed ischemic stroke resulting from bacteremia after undergoing wisdom teeth extraction. Initially, the patient experienced fever and malaise, which were followed by right-sided hemiplegia. Diagnostic imaging, including a CT scan, identified a subacute infarction in the posterior crus of the left internal capsule, and MRI findings indicated inflammatory changes in the masticatory muscles. Further investigations involving biopsies of the masticatory muscles, along with blood and cerebrospinal fluid samples, confirmed bacterial meningitis with associated vasculitis. Notably, oral bacteria linked to periodontitis, including Porphyromonas gingivalis, Fusobacterium nucleatum, Tannerella forsythia, and Parvimonas micra, were found in the biopsies and microbiological analyses. To the best of our knowledge, this is the first reported case showing that bacteremia following dental procedures can lead to such severe neurological outcomes. This case underscores the importance of recognizing bacteremia-induced vasculitis in patients presenting with neurological symptoms post-dental procedures, emphasizing the broader implications of oral infections in such pathologies. Full article

Fentanyl (FTN) and synthetic analogs of FTN continue to ravage populations across the globe, including in the United States where opioids are increasingly being used and abused and are causing a staggering and growing number of overdose deaths each year. This growing pandemic is worsened by the ease with which FTN can be derivatized into numerous derivatives. Understanding the chemical properties/behaviors of the FTN class of compounds is critical for developing effective chemical detection schemes using nanoparticles (NPs) to optimize important chemical interactions. Halogen bonding (XB) is an intermolecular interaction between a polarized halogen atom on a molecule and e⁻-rich sites on another molecule, the latter of which is present at two or more sites on most fentanyl-type structures. Density functional theory (DFT) is used to identify these XB acceptor sites on different FTN derivatives. The high toxicity of these compounds necessitated a “fragmentation” strategy where smaller, non-toxic molecules resembling parts of the opioids acted as mimics of XB acceptor sites present on intact FTN and its derivatives. DFT of the fragments’ interactions informed solution measurements of XB using ¹⁹F NMR titrations as well as electrochemical measurements of XB at self-assembled monolayer (SAM)-modified electrodes featuring XB donor ligands. Gold NPs, known as monolayer-protected clusters (MPCs), were also functionalized with strong XB donor ligands and assembled into films, and their interactions with FTN “fragments” were studied using voltammetry. Ultimately, spectroscopy and TEM analysis were combined to study whole-molecule FTN interactions with the functionalized MPCs in solution. The results suggested that the strongest XB interaction site on FTN, while common to most of the drug’s derivatives, is not strong enough to induce NP-aggregation detection but may be better exploited in sensing schemes involving films. Full article