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The insurance of green economy assets against natural hazards is a growing market. This study explores whether currently available published knowledge is adequate for the vulnerability assessment of these assets to natural hazards. A matrix is constructed to demonstrate the vulnerability to functional loss of 37 asset classes in the renewable energy, green construction, resource management, carbon capture and storage, energy storage, and sustainable transportation sectors. The 28 hazards adopted range from environmental and geophysical events to oceanic, coastal, and space weather events. A fundamental challenge in constructing the matrix was the lack of an asset–hazard taxonomy for the green economy. Each matrix cell represents the vulnerability of an asset to a specific hazard, based on a comprehensive systematic literature review. A confidence level is assigned to each vulnerability assessment based on a literature density heat map. The latter highlights specific knowledge gaps, in particular a lack of quantitative vulnerability studies that appropriately represent all functional loss mechanisms in green economy assets. Apart from charting research gaps, a main output of this study is the proposal of a representative asset–hazard taxonomy to guide future quantitative research that can be applied by the insurance industry.

Indonesia has experienced several tsunamis triggered by seismic and non-seismic (i.e., landslides) sources. These events damaged or destroyed coastal buildings and infrastructure and caused considerable loss of life. Based on the Global Earthquake Model (GEM) guidelines, this study assesses the empirical tsunami fragility to the buildings inventory of the 2018 Sunda Strait, 2018 Sulawesi–Palu, and 2004 Indian Ocean (Khao Lak–Phuket, Thailand) tsunamis. Fragility curves represent the impact of tsunami characteristics on structural components and express the likelihood of a structure reaching or exceeding a damage state in response to a tsunami intensity measure. The Sunda Strait and Sulawesi–Palu tsunamis are uncommon events still poorly understood compared to the Indian Ocean tsunami (IOT), and their post-tsunami databases include only flow depth values. Using the TUNAMI two-layer model, we thus reproduce the flow depth, the flow velocity, and the hydrodynamic force of these two tsunamis for the first time. The flow depth is found to be the best descriptor of tsunami damage for both events. Accordingly, the building fragility curves for complete damage reveal that (i) in Khao Lak–Phuket, the buildings affected by the IOT sustained more damage than the Sunda Strait tsunami, characterized by shorter wave periods, and (ii) the buildings performed better in Khao Lak–Phuket than in Banda Aceh (Indonesia). Although the IOT affected both locations, ground motions were recorded in the city of Banda Aceh, and buildings could have been seismically damaged prior to the tsunami's arrival, and (iii) the buildings of Palu City exposed to the Sulawesi–Palu tsunami were more susceptible to complete damage than the ones affected by the IOT, in Banda Aceh, between 0 and 2 m flow depth. Similar to the Banda Aceh case, the Sulawesi–Palu tsunami load may not be the only cause of structural destruction. The buildings' susceptibility to tsunami damage in the waterfront of Palu City could have been enhanced by liquefaction events triggered by the 2018 Sulawesi earthquake.

In recent years, bottom-up nanofabrication techniques and especially solution-based ones have gained significant popularity due to their relatively facile implementation, low-cost and design flexibility that allows the development of a plethora of three-dimensional nanostructures and nanoarchitectures. Nonetheless, despite the apparent simplicity of the methods, the resulting nanostructures are often morphologically and hierarchically complex with no apparent way of appropriately describing their features in a quantifiable and methodological way. In this work, we propose a symmetry-based approach for the quantitative characterization of the morphology of nanostructured surfaces. The key idea is to characterize the morphology of nanostructures by means of the fundamental spatial symmetry metrics and the deviations from the fully symmetrical counterparts. The focus of the proposed methodology is on the translational and scaling symmetry, which are investigated through the mathematical tools of Fourier and (multi)fractal analysis, respectively. The calculated metrics characterizing these symmetries are the period and the fractal dimension of surfaces while the deviations are quantified by the disorder parameter ωd related to the FWHM of Fourier peak and by the asymmetry of the multifractal spectrum for the translational and scaling symmetry respectively. As an initial study case and in order to demonstrate its suitability, the developed symmetry-based methodology was applied to nickel oxide (NiO) and copper oxide (CuO) nanostructures hydrothermally-grown on silicon substrates. The results show that even in the cases where the surfaces display similar symmetry metrics (period, fractal dimension) the symmetry-based approach reveals subtle, but quantifiable differences in the deviations from full symmetries which are not easily identified by other approaches.

Abstract Background This study aimed to explore the impact of occupational activities involving extensive finger movement on the muscular characteristics of the forearms. In particular, the flexor digitorum (FD) muscular thickness and strength asymmetry between right and left hand were compared between musicians and non-musicians. Methods Ultrasonography was employed to measure the thickness of the FD in each hand, while a validated custom-made device was used to assess the strength of the flexor and extensor digitorum (ED). Initially, muscle differences were estimated by computing the asymmetry index between dominant and non-dominant hands. To assess potential occupational disparities, comparisons of the asymmetry index were conducted between 25 right-handed instrumental musicians and 25 right-handed non-musicians. Results Musicians exhibited lower asymmetry between dominant and non-dominant hands in both FD thickness and ED strength when compared to non-musicians. This effect was particularly pronounced in musicians playing instruments that extensively use the left-hand fingers (e.g., violinists). Conclusions Occupational activities, such as playing a musical instrument, can alter forearm muscle mass and strength distribution between dominant and non-dominant hands. This underscores the importance of considering occupational parameters in clinical or experimental interventions and musculoskeletal assessments.

BackgroundGenetic testing in psychiatry has gained attention, raising questions about its application and impact. Understanding stakeholders’ perspectives, including healthcare providers and patients, is vital for informed policy development. The aim of this systematic review was to focus on the perceptions and concerns of patients and healthcare workers in psychiatry regarding the use of genetic testing.MethodsWe conducted a systematic review following PRISMA guidelines, for the period 1/2/2014, to 1/1/2024, via PubMed and Embase databases identifying 50 articles in total. After excluding duplicates (n = 12), 38 articles went through screening. After careful full-text article assessment for eligibility and applying the inclusion and exclusion criteria, only fifteen (n = 15) of the articles were included.ResultsAmong 15 selected studies involving 3,156 participants (2,347 healthcare professionals; 809 patients), thematic analysis identified four primary themes: Organizational-implementation concerns, Ethical Considerations, Concerns on changes in clinical praxis, and Legal implications. Despite these concerns, seven out of eleven studies indicated that healthcare workers viewed genetic testing in psychiatry positively. Patients’ perspectives varied, with two of the four studies reflecting positive attitudes. No pervasive negative sentiment was observed.ConclusionOur review highlights the multidimensional perspectives of healthcare professionals and patients surrounding the application of genetic testing in psychiatry. These considerations need to be addressed to facilitate the implementation of genetic testing in clinical praxis in psychiatry. Further research is needed for validation of the results and to guide policies and clinicians in the integration of genetic testing into mental healthcare practice.

Due to their minimal environmental impact, green energy sources like wind turbines and solar panels are increasingly utilized in power systems. However, the power they generate is highly variable, leading to unpredictable fluctuations in power supply. Additionally, advanced smart functions in consumer devices and their unpredictable usage patterns contribute to similar fluctuations in power consumption. These fluctuations present a significant challenge to the stability and quality of the power grid, creating a complex issue of power imbalance that becomes harder to manage. Innovative management and control approaches are necessary to address these challenges and thus support the shift to sustainable energy sources. Artificial intelligence (AI) techniques are increasingly proposed as promising solutions, albeit mostly implemented as isolated solutions within centralized power control systems. To effectively manage the complex and often large scale power systems, this paper advocates the use of a Distributed AI (DAI) framework as imperative in enhancing their agility and stability. An illustrative Nano-Grid example (including the potential use of battery sources in extreme scenarios) is adopted to demonstrate the framework’s utility, and a number of power control strategies to safeguard the power system against the variability of both power generators and loads are theoretically formulated and then realized within the proposed framework. Linear Programming, Ant Colony Optimization, Genetic Algorithms, and Particle Swarm Optimization techniques are experimented with, and through simulations, the utility of the DAI framework is demonstrated. The findings underscore the effectiveness and potential benefits of the proposed framework in ensuring the safe and effective operation of power systems with the use of particle swarm optimization amid fluctuating energy scenarios with a small to large number of devices in the nano-grid.

In the rapidly developing field of wireless communication, the control of beams in Reconfigurable Intelligent Surfaces (RISs) has emerged as a promising element beyond 5G wireless communication systems. Due to their distinctive reflecting elements, Reconfigurable Intelligent Surface (RIS) is essential in several operations, including beamforming and beam steering. However, the optimization of these functions necessitates complex solutions. In this study, the authors introduce the Feedback DNN strategy, which combines the Feedback Neural Network and Deep Neural Network techniques specifically designed for channel estimation. This methodology utilizes deep neural networks to provide the RIS and user equipment communication path, enabling improved beamforming and steering capabilities. This study highlights the incorporation of machine learning (ML) within the field of communication engineering, intending to enhance the reliability and effectiveness of wireless communication systems. The contributions encompass a novel methodology for managing RIS beams, sophisticated approaches for channel estimates, optimization of beam operations, and the potential to enhance the performance of wireless systems by utilizing RISs via a Feedback DNN (called DeepRISBeam). The proposed approach is compared against other state-of-the-art ML approaches regarding their training accuracy. At the same time, it evaluated Bit Error Rate performance in high- and low-mobility vehicular communication scenarios.

Despite good agreement of national guidelines for the assessment and treatment of tinnitus, there is still substantial variation regarding tinnitus-related healthcare across Europe. In contrast to previous work, which has mainly focussed on the perspective of healthcare professionals, we here report the results of separate web-based surveys conducted with clinicians and researchers as well as tinnitus patients. These surveys were devised to obtain information about their respective attitudes and needs with respect to tinnitus healthcare, and to reveal possible interdisciplinary inconsistencies among clinicians and researchers. We mainly targeted participants from Germany, Cyprus, and Greece, the countries in which the institutions of the researchers involved in this project are based. Results showed, firstly, that the treatment satisfaction of the patients was overall more negative than that of the clinicians and researchers, and that the patients' treatment satisfaction did not depend on the number of different treatments they had received. Secondly, patients as well as clinicians and researchers indicated that they were interested in learning more about a variety of tinnitus-related topics, especially treatment strategies, with no marked differences between clinicians from different professional disciplines. This suggests similar tinnitus-specific educational needs in patients and healthcare professionals.

Intrusion Detection Systems (IDSs) have played a crucial role in identifying cyber threats for a very long time. Still, their significance has increased significantly with the advent of 5G/6G technologies, particularly Device-to-Device (D2D) communication. Multiple cyberattacks, such as Man in the Middle (MITM) attacks, Structured Query Language (SQL) injection attacks, Dictionary attacks, Distributed Denial of Service (DDoS) attacks, and others by using specific attack tools such as HULK, RUDY, and GoldenEye, that can cause rapid battery drain, rendering D2D network devices more prone to hardware failure or even to the dissolution of the D2D communication network affecting the operation and the performance of the mobile network. Using a Deep Hierarchical Machine Learning Model/Deep Hierarchical Neural Network (DHMLM/DHNN) technique, we develop an Intrusion Detection System (IDS) for D2D communication that, due to its hierarchical structure, is distinct from other comparable approaches. (i.e., Recurrent Neural Networks (RNN), Deep Neural Networks (DNN), Long short-term memory (LSTM)), has several advantages, including i) reduced training time (training time can be reduced by 56%.); ii) the ability to identify multiple types of attacks; iii) the ability to identify Zero-day/Unknown attacks (i.e., attacks that it has not seen before); iv) a more straightforward model design due to the low number of connections and neurons compared to other approaches (excluding RNN and LSTM), and; v) overall outstanding performance in terms of accuracy (i.e., 99.07%). The custom/unified data set used to train and evaluate the model was partially manually emulated and partially sampled from a large set (>95%) from the commonly used CIC-DDoS-2019 data set. The after-comparison final proposed model’s 99.07% accuracy on this unified data set demonstrates the efficacy of our method. The model was also tested and demonstrated an astounding 99.63% accuracy for zero-day/unknown attacks.

Efficient hyperpolarization of nuclear spins via optically active defect centers, such as the nitrogen vacancy (NV) center in diamond, has great potential for enhancing NMR-based quantum information processing and nanoscale magnetic resonance imaging. Recently, pulse-based protocols have been shown to efficiently transfer optically induced polarization of the electron defect spin to surrounding nuclear spins—at particular resonant pulse intervals. In this work, we investigate the performance of these protocols, both analytically and experimentally, with the electronic spin of a single NV defect. We find that whenever polarization resonances of nuclear spins are near degenerate with a “blocking” spin, which is single spin with stronger off-diagonal coupling to the electronic central spin, they are displaced out of the central resonant region—without, in general, significant weakening in the rate of polarization. We analyze the underlying physical mechanism and obtain a closed-form expression for the displacement. We propose that spin blocking represents a common but overlooked effect in hyperpolarization of nuclear spins and suggest solutions for improved protocol performance in the presence of (naturally occurring) blocking nuclear spins.

The present study assessed muscular atrophy and weakness of the flexor digitorum superficialis (FDS) and profundus (FDP) muscle as possible long-term side effects of botulinum toxin (BoNT) injections in hand dystonia patients after the termination of their treatment. For the assessment of both parameters, a group of 12 musicians diagnosed with focal hand dystonia was compared with a group of 12 healthy matched musicians. The minimum and maximum times since the last injection across patients were 0.5 to 3.5 years, respectively. The thickness and strength of the FDS and FDP were assessed via ultrasonography and a strength measurement device. Group differences were estimated through the calculation of the symmetry index between the dominant and non-dominant hand. The results revealed that compared to the control group, thickness and flexion strength of the injected FDS and FDP were decreased by 10.6% ± 5.3% (95% CI) and 12.5% ± 6.4% (95% CI), respectively, in the patient group. The amount of weakness and atrophy was predicted significantly by the total amount of BoNT injected throughout the entire treatment period. In contrast, the time after the last injection did not predict the amount of strength and muscle mass recovery after the cessation of the treatment. The current study revealed that even up to 3.5 years after the termination of BoNT injections, long-term side effects such as weakness and atrophy can still be observed. We suggest that the total BoNT dose should remain as small as possible to reduce long-lasting side effects to the minimum. Although side effects differ significantly among patients, a potential full recovery of atrophy and weakness after the cessation of BoNT treatment might be observed after periods longer than 3.5 years.

The synthesis of 3,4-dihydroquinoxalin-2-ones via the selective reduction of aromatic, multifunctional nitro precursors catalyzed by supported gold nanoparticles is reported. The reaction proceeds through the in situ formation of the corresponding amines under heterogeneous transfer hydrogenation of the initial nitro compounds catalyzed by the commercially available Au/TiO2-Et3SiH catalytic system, followed by an intramolecular C-N transamidation upon treatment with silica acting as a mild acid. Under the present conditions, the Au/TiO2-TMDS system was also found to catalyze efficiently the present selective reduction process. Both transfer hydrogenation processes showed very good functional-group tolerance and were successfully applied to access more structurally demanding products bearing other reducible moieties such as chloro, aldehyde or methyl ketone. An easily scalable (up to 1 mmol), low catalyst loading (0.6 mol%) synthetic protocol was realized, providing access to this important scaffold. Under these mild catalytic conditions, the desired products were isolated in good to high yields and with a TON of 130. A library analysis was also performed to demonstrate the usefulness of our synthetic strategy and the physicochemical profile of the derivatives.

With the advent of strain-hardening cementitious composites (SHCC), an opportunity for alternative jacketing solutions is presented, where the internal confinement exerted by the fibers in the material may effectively encase the structural component, thereby enhancing the strength and deformation capacity in the critical regions. This concept is explored in the present paper through testing of four pre-damaged prismatic flexural reinforced concrete members with various reinforcing deficiencies. Thin SHCC jackets constituted of a fiber-reinforced Engineered Cementitious Composite (ECC) are used to replace the damaged cover without any additional confining reinforcement. An advantage of cover replacement is that strengthening is achieved without altering the dimensions of the members. The experimental results documented the SHCC jackets’ effectiveness as a rehabilitation strategy, enhancing both the strength and ductility of the retrofitted elements and mitigating the deficiency in transverse reinforcement detailing. The strength recovery showed that the cover-thin SHCC jacket sufficed to enhance flexural and shear resistance through confinement and mobilization of stress transfer at the interface with the encased core.

The assessment methods for estimating the behavior of the complex mechanics of reinforced concrete (RC) structural elements were primarily based on experimental investigation, followed by the collective evaluation of experimental databases from the available literature. There is still a lot of uncertainty in relation to the strength and deformability criteria that have been derived from tests due to the differences in the experimental test setups of the individual research studies that are being fed into the databases used to derive predictive models. This research work focuses on structural elements that exhibit pronounced strength degradation with plastic deformation and brittle failure characteristics. The study’s focus is on evaluating existing models that predict the shear strength of RC columns, which take into account important factors including the structural element’s ductility and axial load, as well as the contributions of specific resistance mechanisms like that of concrete, transverse, and longitudinal reinforcement. Significantly improved predictive models are proposed herein through the implementation of machine learning (ML) algorithms on refined datasets. Three ML models, LREGR, POLYREG-HYT, and XGBoost-HYT-CV, were used to develop different predictive models that were able to compute the shear strength of RC columns. According to the numerical findings, POLYREG-HYT- and XGBoost-HYT-CV-derived models outperformed other ML models in predicting the shear strength of rectangular RC columns with the correlation coefficient having a value R greater than 99% and minimal errors. It was also found that the newly proposed predictive model derived a 2-fold improvement in terms of the correlation coefficient compared to the best available equation in international literature.

Next-generation mobile networks, such as Fifth-Generation (5G), and Sixth-Generation (6G) are envisioned to undergo an unprecedented transformation from connected things to connected intelligence with more stringent characteristics, i.e., low end-to-end latency, high bandwidth, reliable connectivity, etc. Such networks will significantly increase network traffic in the distribution networks, causing the need for real-time automated decision-making, such as automated network resource allocation. The network resources be allocated dynamically based on the Quality of Service (QoS) requirements. However, the primary concern is that the distribution networks may get congested soon after allocating network resources. Thus, a QoS-aware prediction framework can be used proactively to predict the future trend of network traffic in each QoS class. In this paper, we propose a framework for predicting the heterogeneous multivariate QoS-aware network traffic to make the best use of network resources dynamically. Specifically, we use a Recurrent Neural Network (RNN) to integrate a Bidirectional Long Short-Term Memory (BLSTM) neural network. The results show that the fusion of RNN-BLSTM can predict the QoS-aware network traffic for over 13 hours with an average accuracy of 97.68%. Moreover, the proposed model is trained and tested over limited data, collected and identified through Deep Packet Inspection (DPI) over an operational network. In addition, we compared the RNN-BLSTM with other prediction algorithms (i.e., LSTM, ARIMA, SVM) in terms of precision, execution time, and energy consumption. Lastly, the proposed framework is used to assign the network resources to each QoS class based on the QoS requirements of that class and its pre-defined priority.

The presentation of two sinusoidal tones, one to each ear, with a slight frequency mismatch yields an auditory illusion of a beating frequency equal to the frequency difference between the two tones; this is known as binaural beat (BB). The effect of brief BB stimulation on scalp EEG is not conclusively demonstrated. Further, no studies have examined the impact of musical training associated with BB stimulation, yet musicians' brains are often associated with enhanced auditory processing. In this study, we analysed EEG brain responses from two groups, musicians and non-musicians, when stimulated by short presentation (1 min) of binaural beats with beat frequency varying from 1 Hz to 48 Hz. We focused our analysis on alpha and gamma band EEG signals, and they were analysed in terms of spectral power, and functional connectivity as measured by two phase synchrony based measures, phase locking value and phase lag index. Finally, these measures were used to characterize the degree of centrality, segregation and integration of the functional brain network. We found that beat frequencies belonging to alpha band produced the most significant steady-state responses across groups. Further, processing of low frequency (delta, theta, alpha) binaural beats had significant impact on cortical network patterns in the alpha band oscillations. Altogether these results provide a neurophysiological account of cortical responses to BB stimulation at varying frequencies, and demonstrate a modulation of cortico-cortical connectivity in musicians' brains, and further suggest a kind of neuronal entrainment of a linear and nonlinear relationship to the beating frequencies.

This paper explores the perspectives of different urban actors regarding public participation in the context of the increasing incorporation of digital technologies and urban platforms. The study is based on three workshops with local governance actors, six semi-structured interviews with academics in the fields of public participation and digital technologies and a citizen survey with 260 respondents. The results provide multi-perspective insights into the challenges of participatory processes and are synthesized into three contributions: (i) guidelines for effective public participation, including factors that encourage or discourage citizen engagement; (ii) guidelines for designing participatory platforms, highlighting specific features that promote digital engagement (i.e. social media, gamification and user-friendly interfaces), and (iii) a typology of digital participation platforms to connect the diverse needs of actor groups with the various possibilities provided by new technologies. The guidelines provide concrete recommendations to support both urban practitioners and interface designers in designing participatory strategies and platforms, respectively. Recognizing that there is no-one-size-fits-all platform, the typology provides a framework for the assessment and further development of digital platforms for public participation.This article is part of the theme issue 'Co-creating the future: participatory cities and digital governance'.

Methylmalonic aciduria and homocystinuria, CblC type, is an inborn error of intracellular vitamin B12 (cobalamin) metabolism caused, in the majority of cases, by mutations in the MMACHC gene. Five Cypriot patients (four males and one female) were diagnosed with a CblC defect. Age at diagnosis ranged from 10 days to 9 months. We present here the clinical, biochemical and molecular findings of these patients. Our retrospective study indicates that all patients were carriers of the known p.Arg91LysfsTer14 variant in either a homozygous or compound heterozygous state with other known MMACHC pathogenic variants. Out of three patients sharing the same genotype the one diagnosed and initiated treatment in the neonatal period displayed an improved clinical outcome., Competing Interests: The authors declare that they have no competing interests., (© 2024 The Authors.)

Selective screening for inherited metabolic disorders (IMD) began in Cyprus in 1990. Over the last thirty-three years 7388 patients were investigated for IMD and 200 diagnoses were made (diagnostic yield 2.7%). The existence of a single laboratory of Biochemical Genetics for the whole island facilitated the creation of a national registry for IMD. The minimal prevalence of IMD in Cyprus is 53.3 cases per 100,000 live births. The most common group are disorders of amino acid metabolism (41.0%), followed by disorders of carbohydrate metabolism (16.5%), disorders of complex molecule degradation (16.5%), mitochondrial disorders (10.5%) and disorders of vitamin and co-factor metabolism (5.5%). Hyperphenylalaninaemia is the most common IMD (14.0%) followed by galactosaemia (7.0%), glutaric aciduria type I (5.5%) and MSUD (4.0%). Some disorders were found to have a relatively high incidence in specific communities, for example Sandhoff disease among the Cypriot Maronites and GM1 gangliosidosis in one particular area of the island. Other disorders were found to have a relatively higher overall incidence, compared to other Caucasian populations, for example galactosaemia, glutaric aciduria type I and MSUD, while fatty acid oxidation defects, Gaucher disease and classic PKU were found to have a relatively lower incidence. Molecular characterization of selected disorders revealed many novel genetic variants, specific to the Cypriot population., Competing Interests: None., (© 2024 The Authors. Published by Elsevier Inc.)

P-type Bi 0.3 Sb 1.7 Te 3 polycrystalline pellets were fabricated using different methods: melting and mechanical alloying, followed by hot-press sintering. The effect of starting powder particle size on the thermoelectric properties was investigated in samples prepared using powders of different particle sizes (with micro- and/or nano-scale dimensions). A peak ZT (350 K) of ~1.13 was recorded for hot-pressed samples prepared from mechanical alloyed powder. Moreover, hot-pressed samples prepared from ≤45 μm powder exhibited similar ZT (~1.1). These high ZT values are attributed both to the presence of high-density grain boundaries, which reduced the lattice thermal conductivity, as well as the formation of antisite defects during milling and grinding, which resulted in lower carrier concentrations and higher Seebeck coefficient values. In addition, Bi 0.3 Sb 1.7 Te 3 bulk nanocomposites were fabricated in an attempt to further reduce the lattice thermal conductivity. Surprisingly, however, the lattice thermal conductivity showed an unexpected increasing trend in nanocomposite samples. This surprising observation can be attributed to a possible overestimation of the lattice thermal conductivity component by using the conventional Wiedemann-Franz law to estimate the electronic thermal conductivity component, which is known to occur in nanocomposite materials with significant grain boundary electrical resistance.

The transition to university is a process that presents young adults with several challenges in adaptation, especially students with disabilities. The current study investigated the differences in adaptation and academic performance between students with and without disabilities and further examined these differences among students with disabilities. Additionally, we explored the role of academic support for students with disabilities' adaptation and academic performance, as well as their perceptions of a proposed specialised package of counselling psychology interventions. The sample consisted of 127 students with disabilities and 127 without disabilities, aged 18-24 years. Results revealed that students with disabilities reported a lower GPA and adaptation than students without disabilities. Additionally, differences among students with disabilities were observed only in terms of GPA, according to their disability type, existence of comorbidity and type of exam accommodations. Interestingly, no differences were found in GPA or adaptation between students with disabilities who utilised psychological therapy and those who did not. Finally, adaptation scores, but not GPA, were higher for students with disabilities who were positive in receiving a specialised package of counselling psychology interventions. The findings are discussed in relation to the existing literature and future considerations of counselling psychology's role in support of students with disabilities.

This study aimed to investigate the effect of an innovative ecofriendly process-instant controlled pressure drop technology, also known as "détente instantanée contrôlée" or DIC-coupled with Tripolium extraction (DIC-Tripolium), on the hesperidin recovery, and antioxidant and antidiabetic activities of orange byproduct extracts. A DIC pretreatment was applied to partially dried orange byproducts (~16% wet basis). A central composite rotatable design (CCRD), composed of 13 experimental trials (four factorial points, four-star points, and five repetitions for the central point), was followed by a Tripolium process consisting of successive intermittent extraction periods using ethanol/water solvent at 20 ± 1 °C, 5 kPa for 5 min and m / v ratio = 5 g/50 mL. The DIC pretreatment, coupled with the Tripolium process, increased the extractability of hesperidin (from 1.55- to 4.67-fold compared to untreated DIC orange byproducts). The radical scavenging activities of the extracts were also enhanced or preserved in different DIC-Tripolium extracts. The α-Amylase inhibition percentage varied between 55.6 ± 0.02 and 88.30 ± 0.01% according to DIC-Tripolium conditions. The multi-criteria optimized condition of DIC-Tripolium extraction, allowing for the maximization of the hesperidin content, radical scavenging activities, iron chelating activity, and α-amylase inhibition of extracts, corresponds to a DIC saturated steam pressure of 599.4 kPa and a DIC pretreatment time of 38 s.

There are several studies on the deregulated gene expression profiles in kidney cancer, with varying results depending on the tumor histology and other parameters. None of these, however, have identified the networks that the co-deregulated genes (co-DEGs), across different studies, create. Here, we reanalyzed 10 Gene Expression Omnibus (GEO) studies to detect and annotate co-deregulated signatures across different subtypes of kidney cancer or in single-gene perturbation experiments in kidney cancer cells and/or tissue. Using a systems biology approach, we aimed to decipher the networks they form along with their upstream regulators. Differential expression and upstream regulators, including transcription factors [MYC proto-oncogene (MYC), CCAAT enhancer binding protein delta (CEBPD), RELA proto-oncogene, NF-kB subunit (RELA), zinc finger MIZ-type containing 1 (ZMIZ1), negative elongation factor complex member E (NELFE) and Kruppel-like factor 4 (KLF4)] and protein kinases [Casein kinase 2 alpha 1 (CSNK2A1), mitogen-activated protein kinases 1 (MAPK1) and 14 (MAPK14), Sirtuin 1 (SIRT1), Cyclin dependent kinases 1 (CDK1) and 4 (CDK4), Homeodomain interacting protein kinase 2 (HIPK2) and Extracellular signal-regulated kinases 1 and 2 (ERK1/2)], were computed using the Characteristic Direction, as well as GEO2Enrichr and X2K, respectively, and further subjected to GO and KEGG pathways enrichment analyses. Furthermore, using CMap, DrugMatrix and the LINCS L1000 chemical perturbation databases, we highlight putative repurposing drugs, including Etoposide, Haloperidol, BW-B70C, Triamterene, Chlorphenesin, BRD-K79459005 and β-Estradiol 3-benzoate, among others, that may reverse the expression of the identified co-DEGs in kidney cancers. Of these, the cytotoxic effects of Etoposide, Catecholamine, Cyclosporin A, BW-B70C and Lasalocid sodium were validated in vitro. Overall, we identified critical co-DEGs across different subtypes in kidney cancer, and our results provide an innovative framework for their potential use in the future.

The orange byproduct is a widely accessible and valuable source of functional phenolic compounds, particularly hesperidin. Hesperidin extraction remains a challenging phase in its valorization chain due to its low solubility and limited extractability in solvents. This work aims to examine the effect of conventional solvent extraction (CSE) compared to emerging and innovative extraction methods: accelerated solvent extraction (ASE) and ultrasound-assisted extraction (UAE) when applied with or without a pretreatment process of instant controlled pressure drop (DIC) to intensify extraction, antioxidant, and antidiabetic activities. The total phenols, flavonoids, hesperidin contents, radical scavenging activities, iron chelating activity, and in vitro α-amylase inhibition of the extracts were determined for CSE (80%, 70 °C), UAE (ethanol 80%, 70 °C, 200 W), and ASE (ethanol 60%, 100 °C, 100 bars) with or without DIC pretreatment (pressure = 0.4 MPa, total thermal time = 30 s). The hesperidin amounts obtained were 0.771 ± 0.008 g/100 g DM, 0.823 ± 0.054 g/100 g DM, and 1.368 ± 0.058 g/100 g DM, for CSE, UAE, and ASE, respectively. DIC pretreatment of orange byproducts increased hesperidin recovery by 67%, 25.6%, and 141% for DIC-CSE, DIC-UAE, and DIC-ASE, respectively. The DPPH and ABTS radical scavenging and iron chelating activities of extracts were also significantly enhanced, and the in vitro antidiabetic activity of extracts was preserved.

The consequences of global warming call for a shift to circular manufacturing practices. In this context, carbon capture and utilization (CCU) has become a promising alternative toward a low-emitting chemical sector. This study addresses for the first time the design of an integrated CO 2 refinery and compares it against the business-as-usual (BAU) counterpart. The refinery, which utilizes atmospheric CO 2 , comprises three synthesis steps and coproduces liquefied petroleum gas, olefins, aromatics, and methanol using technologies that were so far studied decoupled from each other, hence omitting their potential synergies. Our integrated assessment also considers two residual gas utilization (RGU) designs to enhance the refinery's efficiency. Our analysis shows that a centralized cluster with an Allam cycle for RGU can drastically reduce the global warming impact relative to the BAU (by ≈135%) while simultaneously improving impacts on human health, ecosystems, and resources, thereby avoiding burden-shifting toward human health previously observed in some CCU routes. These benefits emerge from (i) recycling CO 2 from the cycle, amounting to 11.2% of the total feedstock, thus requiring less capture capacity, and (ii) reducing the electricity use while increasing heating as a trade-off. The performance of the integrated refinery depends on the national grid, while its high cost relative to the BAU is due to the use of expensive electrolytic H 2 and atmospheric CO 2 feedstock. Overall, our work highlights the importance of integrating CCU technologies within chemical clusters to improve their economic and environmental performance further., Competing Interests: The authors declare no competing financial interest., (© 2023 The Authors. Published by American Chemical Society.)

Sinapine is a phenolic compound found in mustard ( Brassica juncea ) seed meal. It has numerous beneficial properties such as antitumor, neuroprotective, antioxidant, and hepatoprotective effects, making its extraction relevant. In this study, the extraction of sinapine was investigated using three methods: (i) from a mustard seed meal defatted by a supercritical CO 2 (SC-CO 2 ) pretreatment, (ii) by the implementation of high-voltage electrical discharges (HVEDs), (iii) and by the use of ultrasound. The use of SC-CO 2 pretreatment resulted in a dual effect on the valorization of mustard seed meal, acting as a green solvent for oil recovery and increasing the yield of extracted sinapine by 24.4% compared to the control. The combination of ultrasound and SC-CO 2 pretreatment further increased the yield of sinapine by 32%. The optimal conditions for ultrasound-assisted extraction, determined through a response surface methodology, are a temperature of 75 °C, 70% ethanol, and 100% ultrasound amplitude, resulting in a sinapine yield of 6.90 ± 0.03 mg/g dry matter. In contrast, the application of HVEDs in the extraction process was not optimized, as it led to the degradation of sinapine even at low-energy inputs.

Purpose: ECMO is an escalation treatment for hypoxic respiratory failure in patients with CDH. Open repair has been advocated after ECMO indicating that physiological changes associated to thoracoscopic repair were not well tolerated., Methods: We have performed a retrospective review of all patients who underwent ECMO prior CDH repair over a 7 year period (2015-2021). Outcome measures were intra-operative Ph, PCO 2 , PO 2 and FiO 2 at 30 min, 1 h 30 min, and 2 h 30 min of surgery, operative time and recurrence rate. Data are shown in median (range)., Results: Eleven patients required ECMO prior CDH repair. Six of eleven (55%) were done thoracoscopically (Group A) and five of eleven (45%) via laparotomy (Group B). Two of six (33%) patients (Group A) were converted to a laparotomy, one of six (16%) patient developed a recurrence, and there was no recurrence in Group B. Two of five (40%) patients died within the first 60 days of life, whilst there was no death in Group A. Intra-operative values are shown below., Conclusion: Whilst this is a preliminary report of a limited number of patients, there is no obvious difference of intra-operative blood gas parameters during surgical repair in patients after ECMO. Thoracoscopic CDH repair may be considered in patients after ECMO., (© 2023. The Author(s).)

Forced chicory roots (FCR) are the main but also the least valued by-products of Belgian endive culture. However, they contain molecules of interest for industry such as caffeoylquinic acids (CQAs). This study aims to investigate accelerated solvent extraction (ASE) as a green technique to recover chlorogenic acid (5-CQA) and 3,5-dicaffeoylquinic acid (3,5-diCQA), the main CQAs. A D-optimal design was used to determine the influence of temperature and ethanol percentage on their extraction. Optimal extraction conditions were determined using response surface methodology (RSM) and allow the recovery of 4.95 ± 0.48 mg/g DM of 5-CQA at 107 °C, 46% of ethanol and 5.41 ± 0.79 mg/g DM of 3,5-diCQA at 95 °C, 57% of ethanol. The antioxidant activity of the extracts was also optimized by RSM. The highest antioxidant activity was achieved at 115 °C with 40% ethanol (more than 22mgTrolox/g DM ). Finally, correlation between the antioxidant activity and the amount of CQAs was determined. FCR can be a great source of bioactive compounds with potential use as biobased antioxidant.

Carbon capture and utilisation (CCU) provides an appealing framework to turn carbon emissions into valuable fuels and chemicals. However, given the vast energy required to activate the CO 2 molecule, CCU may have implications on sustainable development that are still poorly understood due to the narrow scope of current carbon footprint-oriented assessments lacking absolute sustainability thresholds. To bridge this gap, we developed a power-chemicals nexus model to look into the future and understand how we could produce 22 net-zero bulk chemicals of crucial importance in a sustainable manner by integrating fossil, CCU routes and power technologies, often assessed separately. We evaluated the environmental performance of these technologies in terms of their contribution to 5 Sustainable Development Goals (SDGs), using 16 life cycle assessment metrics and 9 planetary boundaries (PB) to quantify and interpret the impact values. We found that fossil chemicals could hamper the attainment of SDG 3 on good health and well-being and SDG 13 on climate change. CCU could help meet SDG 13 but would damage other SDGs due to burden-shifting to human health, water scarcity, and minerals and metals depletion impacts. The collateral damage could be mitigated by judiciously combining fossil and CCU routes with carbon-negative power sources guided by optimisation models incorporating SDGs-based performance criteria explicitly. Our work highlights the importance of embracing the SDGs in technology development to sensibly support the low-carbon energy and chemicals transition., Competing Interests: There are no conflicts to declare., (This journal is © The Royal Society of Chemistry.)

The behaviour of pre-code reinforced concrete (RC) columns in sequence of fire and earthquake is not well understood and can be critical in case of buildings which experienced fire and are either unrepaired or poorly repaired when exposed to an earthquake. This study proposes a framework on how to construct a simplified model to assess the post-fire cyclic behaviour of such columns. Emphasis is given to the development of simplified material models which can be used to describe the performance of the confined concrete, as its post-fire behaviour is not well studied. The model's performance is validated against the experimental results of a square, non-seismically designed RC column. Three scenarios are considered. The reference scenario, where the column is exposed only to cyclic loading. In the other two, the column is firstly exposed to an ISO-834 time-temperature curves in a furnace of 30 min and 90 min duration and after it cooled down, it is exposed to cyclic loading. The results showed that simplified material models can be used to capture the post-fire cyclic behaviour of an RC column, built without seismic design. It was also found that the confined model adopted played an important role after the peak strength is reached., (© 2022. The Author(s).)