bluuebunny/crossref_metadata_2025 huggingface dataset:
Carbamoylase-based impedimetric electronic tongue for rapid detection of paralytic shellfish toxins
Authors: Raposo Mariana , Soreto Silvia , Moreirinha Catarina , Gomes Maria Teresa S. R. , Costa Sara T. , Botelho Maria João , Melo Bruno M. G. , Costa Luís Cadillon , Rudnitskaya Alisa
Published: February 2024

Phytotoxins produced by marine microalgae, such as paralytic shellfish toxins (PSTs), can accumulate in bivalve molluscs, representing a human health concern due to the life-threatening symptoms they cause. To avoid the commercialization of contaminated bivalves, monitoring programs were established in the EU. The purpose of this work is the implementation of a PST transforming enzyme—carbamoylase—in an impedimetric test for rapid simultaneous detection of several carbamate and N-sulfocarbamoyl PSTs. Carbamoylase hydrolyses carbamate and sulfocarbamoyl toxins, which may account for up to 90% of bivalve toxicity related to PSTs. Conformational changes of carbamoylase accompanying enzymatic reactions were probed by Fourier transform mid-infrared spectroscopy (FT-MIR) and electrochemical impedance spectroscopy (EIS). Furthermore, a combination of EIS with a metal electrode and a carbamoylase-based assay was employed to harness changes in the enzyme conformation and adsorption on the electrode surface during the enzymatic reaction as an analytical signal. After optimization of the working conditions, the developed impedimetric e-tongue could quantify N-sulfocarbamoyl toxins with a detection limit of 0.1 µM. The developed e-tongue allows the detection of these toxins at concentration levels observed in bivalves with PST toxicity close to the regulatory limit. The quantification of a sum of N-sulfocarbamoyl PSTs in naturally contaminated mussel extracts using the developed impedimetric e-tongue has been demonstrated.
Nitric oxide synthase expression in Pseudomonas koreensis MME3 improves plant growth promotion traits
Authors: Labarthe María M. , Maroniche Guillermo A. , Lamattina Lorenzo , Creus Cecilia M.
Published: February 2024

The development of novel biotechnologies that promote a better use of N to optimize crop yield is a central goal for sustainable agriculture. Phytostimulation, biofertilization, and bioprotection through the use of bio-inputs are promising technologies for this purpose. In this study, the plant growth–promoting rhizobacteria Pseudomonas koreensis MME3 was genetically modified to express a nitric oxide synthase of Synechococcus SyNOS, an atypical enzyme with a globin domain that converts nitric oxide to nitrate. A cassette for constitutive expression of synos was introduced as a single insertion into the genome of P. koreensis MME3 using a miniTn7 system. The resulting recombinant strain MME3:SyNOS showed improved growth, motility, and biofilm formation. The impact of MME3:SyNOS inoculation on Brachypodium distachyon growth and N uptake and use efficiencies under different N availability situations was analyzed, in comparison to the control strain MME3:c. After 35 days of inoculation, plants treated with MME3:SyNOS had a higher root dry weight, both under semi-hydroponic and greenhouse conditions. At harvest, both MME3:SyNOS and MME3:c increased N uptake and use efficiency of plants grown under low N soil. Our results indicate that synos expression is a valid strategy to boost the phytostimulatory capacity of plant-associated bacteria and improve the adaptability of plants to N deficiency.

Key points

• synos expression improves P. koreensis MME3 traits important for rhizospheric colonization

• B. distachyon inoculated with MME3:SyNOS shows improved root growth

• MME3 inoculation improves plant N uptake and use efficiencies in N-deficient soil
Can Exclusion of Feral Ecosystem Engineers Improve Coastal Floodplain Resilience to Climate Change? Insight from a Case Study in North East Arnhem Land, Australia
Authors: Sloane Daniel R. , Ens Emilie , Wunungmurra Yumutjin , Mununggurr Lanydjana , Falk Andrew , Wunungmurra Richard , Gumana Goninyal , Towler Gillian , Preece Dave ,   The Yirralka Rangers
Published: February 2024

Global climate change can interact with local drivers, such as ecosystem engineers, to exacerbate changes in ecosystem structure and function, with socio-ecological consequences. For regions of Indigenous interest, there may also be cultural consequences if species and areas affected are culturally significant. Here we describe a participatory approach between the Indigenous (Yolngu) Yirralka Rangers and non-Indigenous researchers that explored the interaction between sea level rise and feral ungulate ecosystem engineers on culturally significant floodplains in the Laynhapuy Indigenous Protected Area (IPA), northern Australia. A feral ungulate exclusion fence array (12 fenced and 12 unfenced plots) was stratified by elevation/salinity to disentangle the effects of salinity and ungulates on floodplain soil and vegetation. We found that exclusion of feral ungulates improved ground cover vegetation, which, according to our literature-derived ecosystem process model, may enhance soil trapping and reduce evapotranspiration to provide the antecedent conditions needed to improve floodplain resilience to sea level rise. The mid-zone of the supratidal floodplain study site was suggested as the region where the benefits of fencing were most pronounced after two years and ground cover species diversity was highest. Ongoing monitoring is required to investigate whether removal of feral ungulates can increase resilience against sea level rise and recruitment of eco-culturally significant Melaleuca species. An interview with a key Yolngu Traditional Owner of the study site demonstrated the importance and effectiveness of the partnership. Yolngu land owners and rangers were active co-researchers and will decide if, when and how to integrate results into feral ungulate management and climate adaptation responses, highlighting the importance of industry-university partnerships in maximising biocultural conservation outcomes.
Calibration of agent based models for monophasic and biphasic tumour growth using approximate Bayesian computation
Authors: Wang Xiaoyu , Jenner Adrianne L. , Salomone Robert , Warne David J. , Drovandi Christopher
Published: February 2024

Agent-based models (ABMs) are readily used to capture the stochasticity in tumour evolution; however, these models are often challenging to validate with experimental measurements due to model complexity. The Voronoi cell-based model (VCBM) is an off-lattice agent-based model that captures individual cell shapes using a Voronoi tessellation and mimics the evolution of cancer cell proliferation and movement. Evidence suggests tumours can exhibit biphasic growth in vivo. To account for this phenomena, we extend the VCBM to capture the existence of two distinct growth phases. Prior work primarily focused on point estimation for the parameters without consideration of estimating uncertainty. In this paper, approximate Bayesian computation is employed to calibrate the model to in vivo measurements of breast, ovarian and pancreatic cancer. Our approach involves estimating the distribution of parameters that govern cancer cell proliferation and recovering outputs that match the experimental data. Our results show that the VCBM, and its biphasic extension, provides insight into tumour growth and quantifies uncertainty in the switching time between the two phases of the biphasic growth model. We find this approach enables precise estimates for the time taken for a daughter cell to become a mature cell. This allows us to propose future refinements to the model to improve accuracy, whilst also making conclusions about the differences in cancer cell characteristics.
A zinc porphyrin-amidine as a green carbon-based electron transport material for organic-light emitting diodes
Authors: Soultati Anastasia , Verykios Apostolis , Tsekouras Marios , Georgiopoulou Zoi , Vidali Veroniki , Pistolis Georgios , Davazoglou Dimitris , Coutsolelos Athanassios G. , Ogawa Marina , Skandamis Panagiotis N. , Argitis Panagiotis , Otsuki Joe , Vasilopoulou Maria
Published: February 2024

Charge injection and transport interlayers based on artificial green carbon materials are imperative for a sustainable future of many classes of optoelectronic devices, including organic light-emitting diodes (OLEDs). Especially, porphyrin derivatives can act as efficient energy and charge funnels mimicking their successful photosynthetic function. Here, we report on the application of a novel green carbon material, in particular, a zinc porphyrin derivative bearing an amidine functional group (referred to as ZnP-amidine), as an electron transport material in fluorescent OLEDs based on a green-yellow co-polymer emitter. ZnP-amidine is processed from environmental friendly solvents without any annealing requirements thus being suitable for low-cost sustainable optoelectronics. It is applies as an ultra-thin interlayer between the aluminum cathode and the emissive layer to enable efficient electron transport and stable performance. This work paves the path towards low-cost green carbon materials inspired by natural processes for organic optoelectronics.
Formal Methods for Industrial Critical Systems
Authors: Groote Jan Friso , Huisman Marieke
Published: February 2024

To stimulate the development and application of formal methods in industry, we need to promote research and development for the improvement of formal methods and tools for industrial applications, and we need to exchange experiences of the industrial usage of these methods and tools. This special issue of Software Tools for Technology Transfer presents various tools and experience reports that are targeting the use of formal methods in industry. The papers in this special issue are extended versions of selected conference papers from the proceedings of the 27th International Conference on Formal Methods for Industrial Critical Systems (FMICS 2022).
Affordances and constraints of integrating esports into higher education from the perspectives of students and teachers: An ecological systems approach
Authors: Zhong Yuchun , Guo Kai , Chu Samuel Kai Wah
Published: February 2024

This study aimed to investigate the perceived affordances of incorporating esports into higher education using an ecological systems approach that examined the multiple factors shaping behaviours at the individual, interpersonal, and organisational levels. A total of 40 participants, comprising 32 students and 8 teachers, were invited to take part in semi-structured interviews. The data gathered from the interviews underwent qualitative analysis through the employment of thematic analysis methods. The results suggested that esports were perceived as having the potential to promote students’ skills development and foster an interactive learning culture. The study also identified constraints on esports integration at various levels, including student differences (i.e. in gaming interest, skills, attention, and physical capacity) and teachers’ insufficient knowledge (i.e. of esports and related pedagogy and content) at the individual level; concerns about the negative impacts of esports at the interpersonal level; and a lack of effective execution of university leadership at the organisational level. The results of this study offer valuable insights for education leaders into how to effectively exercise leadership in the context of esports. Specifically, the findings underscore the importance of developing professional development programmes for teachers to enhance their knowledge of the use of esports and related pedagogy and teaching content to improve the implementation of esports-based instruction.
Tokenized but remaining: how do international academics make sense of their decision to remain in Japanese universities?
Authors: Chen Lilan
Published: February 2024

Despite challenging and uncertain circumstances and the perception of being tokenized symbols in Japanese universities, the majority of international academics are more inclined to remain in their affiliations. The study intends to elucidate how international academics make sense of their decision to remain in Japanese universities. The data are from a qualitative dataset examining the integration experiences of international academics in Japan. Following the philosophical foundations of purposive sampling in interpretative phenomenological analysis (IPA), which was applied as a methodological framework, the study recruited a total of 30 participants. The study reveals varied sensemaking strategies among the interviewees, characterized as survivors, pragmatists, and ambitionists. Survivors refer to those who were compelled to remain in their current affiliations often due to constraints related to their academic roles or age restrictions. Pragmatists prioritize the practical benefits of their positions or affiliations, deriving from professional aspects, sociocultural dimensions, and personal considerations. Ambitionist academics generally view experiences in their current affiliations as a stepping stone toward future professional opportunities elsewhere. The study suggests that insufficient dedication to recruiting and retaining international academics may pose potential long-term risks for Japanese higher education institutions (HEIs) in the global academic sphere, affecting their internationally competitive standing and resilience in an evolving academic landscape. The study provides theoretical and practical implications to researchers, university administrators, and policymakers.
Investigating the impact of vitrification on bovine ovarian tissue morphology, follicle survival, and transcriptomic signature
Authors: Deligiannis Spyridon P. , Kask Keiu , Modhukur Vijayachitra , Boskovic Nina , Ivask Marilin , Jaakma Ülle , Damdimopoulou Pauliina , Tuuri Timo , Velthut-Meikas Agne , Salumets Andres
Published: February 2024

Purpose

Ovarian tissue cryopreservation is vital for fertility preservation, yet its effect on ovarian tissue follicle survival and transcriptomic signature requires further investigation. This study delves into the effects of vitrification on tissue morphology, function, and transcriptomic changes, helping to find possibilities for vitrification protocol improvements.

Methods

Ovarian cortex from 19 bovine animals were used to conduct pre- and post-vitrification culture followed by histological assessment, immunohistochemistry, and TUNEL assay. Follicles’ functionality was assessed for viability and growth within the tissue and in isolated cultures. RNA-sequencing of ovarian tissue was used to explore the transcriptomic alterations caused by vitrification.

Results

Follicle density, cell proliferation, and DNA damage in ovarian stroma were unaffected by vitrification. However, vitrified cultured tissue exhibited reduced follicle density of primordial/primary and antral follicles, while freshly cultured tissue manifested reduction of antral follicles. Increased stromal cell proliferation and DNA damage occurred in both groups post-culture. Isolated follicles from vitrified tissue exhibited similar viability to fresh follicles until day 4, after which the survival dropped. RNA-sequencing revealed minor effects of vitrification on transcriptomic signatures, while culture induced significant gene expression changes in both groups. The altered expression of WNT and hormonal regulation pathway genes post-vitrification suggests the molecular targets for vitrification protocol refinement.

Conclusion

Vitrification minimally affects tissue morphology, follicle density, and transcriptomic signature post-thawing. However, culture revealed notable changes in vitrified tissue samples, including reduced follicle density, decreased isolated follicle survival, and alteration in WNT signalling and ovarian hormonal regulation pathways, highlighted them as possible limitations of the current vitrification protocol.
Control of the PVTOL with Strong Input Coupling
Authors: Lozano Rogelio , Eulopa-Hernandez Jhonatan F , Salazar-Cruz Sergio
Published: February 2024

This paper studies the modeling and control of a Planar Vertical Take-Off and Landing (PVTOL) with steerable thruster. A longitudinal model is obtained using Newton’s second law for the PVTOL which evolves in 3 degrees of freedom and has two control inputs. The aerial vehicle is driven by steerable propulsion controlling its evolution in the vertical plane through the thrust and torque control inputs, which drive the vehicle body and generate a rotation. The obtained model is nonlinear and is significantly different with respect to the well-known PVTOL. For this reason, different control algorithms are presented, and the closed-loop behavior is studied for each of them. The proposed control strategies perform a stationary flight at a desired altitude and control the position of the aerial vehicle. The performance of the proposed control algorithms is tested in numerical simulations.
Exploring User Perceptions of a Mobile App for Religious Practices
Authors: Laird Breanne , Van Tongeren Daryl R. , Hook Joshua N. , Do Bridgette , Hall Todd , Huberty Jennifer
Published: February 2024

The purpose of this study was to explore the usage patterns of USA subscribers of an online religious/spiritual application (i.e., app; Pray.com) and the associations of app usage with physical health, mental health, spiritual health, and well-being outcomes. A total of 1031 subscribers participated in the survey about their engagement with the Pray.com app. Most of the respondents had been using the app between one and two years, and more than half were high-frequency users. Although many individuals engaged with the app experienced spiritual growth, many also reported retrospective improvement in mental and physical health. This research serves as an initial examination of how religious-based apps may be associated with self-reported improvements in physical, mental, and spiritual health outcomes.
Study of phosphate sorption on rendzina soil by heterogeneous isotopic exchange: a biexponential kinetic model
Authors: Vörös János Z. , Kónya József , Nagy Noémi M.
Published: February 2024

Phosphate sorption on rendzina soil was studied by P-32 heterogeneous isotopic exchange under a steady-state. There are two types of sorbed phosphate, namely strongly and weakly bonded phosphate, the latter being able to exchange with phosphate (H232PO4−) ions in the soil solution. The experimental kinetic data was not fitted by the one exponential kinetic model. Starting from this observation, a new kinetic model is established by assuming two types of weakly bonded phosphate, which take part in the two parallel exchange processes. A biexponential kinetic equation is obtained, which fits the experimental data much better than the one exponential equation.

Graphical abstract
GREEN PATH: an expert system for space planning and design by the generation of human trajectories
Authors: Paolanti Marina , Manco Davide , Pietrini Rocco , Frontoni Emanuele
Published: February 2024

Public space is usually conceived as where people live, perceive, and interact with other people. The environment affects people in several different ways as well. The impact of environmental problems on humans is significant, affecting all human activities, including health and socio-economic development. Thus, there is a need to rethink how space is used. Dealing with the important needs raised by climate emergency, pandemic and digitization, the contributions of this paper consist in the creation of opportunities for developing generative approaches to space design and utilization. It is proposed GREEN PATH, an intelligent expert system for space planning. GREEN PATH uses human trajectories and deep learning methods to analyse and understand human behaviour for offering insights to layout designers. In particular, a Generative Adversarial Imitation Learning (GAIL) framework hybridised with classical reinforcement learning methods is proposed. An example of the classical reinforcement learning method used is continuous penalties, which allow us to model the shape of the trajectories and insert a bias, which is necessary for the generation, into the training. The structure of the framework and the formalisation of the problem to be solved allow for the evaluation of the results in terms of generation and prediction. The use case is a chosen retail domain that will serve as a demonstrator for optimising the layout environment and improving the shopping experience. Experiments were assessed on shoppers’ trajectories obtained from four different stores, considering two years.
Spectro Temporal Fusion with CLSTM-Autoencoder based approach for Anomalous Sound Detection
Authors: Chandrakala S. , Pidikiti Akhilandeswari , Sai Mahathi P. V. N.
Published: February 2024

Deep learning models are proved efficient for complex learning tasks. Anomalous sound detection is one such complex task for which self-supervised deep architectures are emerging in recent days. Self-supervised deep models efficiently capture the underlying structure of data. Self-supervised anomalous sound detection attempts to distinguish between normal sounds and unidentified anomalous sounds. With the use of appropriate autoencoders, reconstruction error based decision making is effective for anomaly detection in domains such as computer vision. Auditory image (Spectrogram) based representation of sound signals are commonly used in sound event detection. We propose convolutional long short-term memory (CLSTM) Auto Encoder based approach for anomalous sound detection. In this approach, we explore fusion of spectral and temporal features to model characteristics of normal sounds with noises. The proposed approach is evaluated using MIMII dataset and the DCASE Challenge (2020) Task 2—Anomalous sound detection dataset. Experiments on proposed approach reveal significant improvement over the state-of-the-art approaches.
Exponential Stability of Stochastic Time-Delay Neural Networks with Random Delayed Impulses
Authors: Huang Yueli , Wu Ailong , Zhang Jin-E
Published: February 2024

The mean square exponential stability of stochastic time-delay neural networks (STDNNs) with random delayed impulses (RDIs) is addressed in this paper. Focusing on the variable delays in impulses, the notion of average random delay is adopted to consider these delays as a whole, and the stability criterion of STDNNs with RDIs is developed by using stochastic analysis idea and the Lyapunov method. Taking into account the impulsive effect, interference function and stabilization function of delayed impulses are explored independently. The results demonstrate that delayed impulses with random properties take a crucial role in dynamics of STDNNs, not only making stable STDNNs unstable, but also stabilizing unstable STDNNs. Our conclusions, specifically, allow for delays in both impulsive dynamics and continuous subsystems that surpass length of impulsive interval, which alleviates certain severe limitations, such as presence of upper bound for impulsive delays or requirement that impulsive delays can only exist between two impulsive events. Finally, feasibility of the theoretical results is verified through three simulation examples.
Synthetic Hard Negative Samples for Contrastive Learning
Authors: Dong Hengkui , Long Xianzhong , Li Yun
Published: February 2024

Contrastive learning has emerged as an essential approach in self-supervised visual representation learning. Its main goal is to maximize the similarities between augmented versions of the same image (positive pairs), while minimizing the similarities between different images (negative pairs). Recent studies have demonstrated that harder negative samples, i.e., those that are more challenging to differentiate from the anchor sample perform a more crucial function in contrastive learning. However, many existing contrastive learning methods ignore the role of hard negative samples. In order to provide harder negative samples for the network model more efficiently. This paper proposes a novel feature-level sample sampling method, namely sampling synthetic hard negative samples for contrastive learning (SSCL). Specifically, we generate more and harder negative samples by mixing them through linear combination and ensure their reliability by debiasing. Finally, we execute weighted sampling of these negative samples. Compared to state-of-the-art methods, our method can provide more high-quality negative samples. Experiments show that SSCL improves the classification performance on different image datasets and can be readily integrated into existing methods.
The Multifaceted Impact of Erasmus Programme on the School-to-Work Transition: A Matching Sensitivity Analysis
Authors: Croce Giuseppe , Ghignoni Emanuela
Published: February 2024

This study investigates the effects of studying abroad through the Erasmus Programme (EP), a European Union programme launched primarily to foster international mobility and cultural exchange of University students, on the school-to-work transition of university graduates. Since a satisfactory transition does not only mean finding a job, but also concerns the wage level and the quality of work, such as stability, working hours and risk of overeducation, we consider all these aspects in order to draw a comprehensive picture of the effect of the EP. We exploit a composite dataset, built on administrative and survey data, covering all graduates from the largest Italian university from 2011 to 2015, and replicate the analysis on a national sample of graduates to verify whether the results can be extended nationwide. Estimates are provided, based on a PSM procedure, of the effects of the EP on the probability of employment, including abroad, on the quality of jobs and on wage levels at different points in time after graduation. We also investigate whether less advantaged students benefit from the Erasmus experience, and provide insights about the role of the foreign languages skills. The results show that the participation in the EP improves employment prospects at least in the short term, as well as the quality of job, and has a positive long term effect on the participants' ability to find a job abroad. The wages of participants are persistently higher than those of non-participants. Less advantaged groups also benefit from the Erasmus experience.
Can ChatGPT be used to predict citation counts, readership, and social media interaction? An exploration among 2222 scientific abstracts
Authors: de Winter Joost
Published: February 2024

This study explores the potential of ChatGPT, a large language model, in scientometrics by assessing its ability to predict citation counts, Mendeley readers, and social media engagement. In this study, 2222 abstracts from PLOS ONE articles published during the initial months of 2022 were analyzed using ChatGPT-4, which used a set of 60 criteria to assess each abstract. Using a principal component analysis, three components were identified: Quality and Reliability, Accessibility and Understandability, and Novelty and Engagement. The Accessibility and Understandability of the abstracts correlated with higher Mendeley readership, while Novelty and Engagement and Accessibility and Understandability were linked to citation counts (Dimensions, Scopus, Google Scholar) and social media attention. Quality and Reliability showed minimal correlation with citation and altmetrics outcomes. Finally, it was found that the predictive correlations of ChatGPT-based assessments surpassed traditional readability metrics. The findings highlight the potential of large language models in scientometrics and possibly pave the way for AI-assisted peer review.
On the scalability of the speedup considering the overhead of consolidating virtual machines in servers for data centers
Authors: Juiz Carlos , Bermejo Belen
Published: February 2024

Virtualization technologies are extensively utilized in data centers, particularly cloud computing. This facilitates data center management and diminishes the number of physical machines (servers) and, subsequently, their cooling requirements, leading to cost, space, and power consumption reductions. When applications in data centers are executing independent parallel transactions, but with similar performance requirements, the appropriate level of virtual machine consolidation on a server poses a fundamental challenge for capacity planning. This article introduces a method to evaluate the performance speedup achieved through virtualization on any server and the effects of virtualization and consolidation overheads on physical or virtual machine scalability. This research formalizes the speedup and overheads, using classical computer architecture statements. but at the same time proposes a new method to analyze these overhead amounts and types, showing the scalability and efficiency of different consolidations in the same server and its comparison against no consolidation. This work also proposes a new way to determine the optimal number of physical servers and the optimal number of consolidated virtual machines for a given transaction workload. The real experimentation was performed with different workload sizes, types of virtualizations and different servers. The method presented also facilitates the representation of linear scalability against the real degree of parallelism of either physical machines or consolidated virtual machines for a given transaction workload, as well as striking the right balance between speedup and energy in virtual server consolidation.
Effect of three different insect larvae on growth performance and antioxidant activity of thigh, breast, and liver tissues of chickens reared under mild heat stress
Authors: Stelios Vasilopoulos , Ilias Giannenas , Ioannis Panitsidis , Christos Athanassiou , Elias Papadopoulos , Paschalis Fortomaris
Published: February 2024

This study investigated the potential of insect-based diets to mitigate heat stress impact on broiler chickens, focusing on growth performance and antioxidant stability. Four dietary groups were examined, including a control and three treated groups with Tenebrio molitor (TM), Hermetia illucens (HI), and Zophobas morio (ZM) larvae, respectively, at a 5% replacement ratio. Temperature and relative humidity of the poultry house were monitored. Under heat stress conditions, the HI-fed group consistently exhibited the highest body weight, demonstrating their remarkable growth-promoting potential. TM-fed broilers also displayed commendable growth compared to the control. Insect larvae inclusion in the diet improved feed intake during early growth stages, indicating their positive influence on nutrient utilization. Regarding antioxidant stability, malondialdehyde (MDA) levels in the liver, an oxidative stress and lipid peroxidation marker, were significantly lower in the TM-fed group, suggesting reduced oxidative stress. While the specific insect-based diet did not significantly affect MDA levels in thigh and breast tissues, variations in the total phenolic content (TPC) were observed across tissues, with HI larvae significantly increasing it in the breast. However, the total antioxidant capacity (TAC) and 2,2-diphenyl-1-picrylhydrazyl (DPPH) levels did not differ significantly among dietary groups in the examined tissues. Results suggest that insect-based diets enhance broiler growth and potentially reduce oxidative stress, particularly in the liver. Dietary presence of bioactive compounds may contribute to these benefits. Further research is required to fully elucidate the mechanisms underlying these findings. Insect-based diets seem to offer promise as feed additives in addressing the multifaceted challenges of oxidative stress and enhancing broiler health and resilience under heat stress conditions.
A Spectral Method for Identifiable Grade of Membership Analysis with Binary Responses
Authors: Chen Ling , Gu Yuqi
Published: February 2024

Grade of membership (GoM) models are popular individual-level mixture models for multivariate categorical data. GoM allows each subject to have mixed memberships in multiple extreme latent profiles. Therefore, GoM models have a richer modeling capacity than latent class models that restrict each subject to belong to a single profile. The flexibility of GoM comes at the cost of more challenging identifiability and estimation problems. In this work, we propose a singular value decomposition (SVD)-based spectral approach to GoM analysis with multivariate binary responses. Our approach hinges on the observation that the expectation of the data matrix has a low-rank decomposition under a GoM model. For identifiability, we develop sufficient and almost necessary conditions for a notion of expectation identifiability. For estimation, we extract only a few leading singular vectors of the observed data matrix and exploit the simplex geometry of these vectors to estimate the mixed membership scores and other parameters. We also establish the consistency of our estimator in the double-asymptotic regime where both the number of subjects and the number of items grow to infinity. Our spectral method has a huge computational advantage over Bayesian or likelihood-based methods and is scalable to large-scale and high-dimensional data. Extensive simulation studies demonstrate the superior efficiency and accuracy of our method. We also illustrate our method by applying it to a personality test dataset.
Evaluating lake water quality with a GIS-based MCDA integrated approach: a case in Konya/Karapınar
Authors: Akar Ali Utku , Sisman Suleyman , Ulku Harika , Yel Esra , Yalpir Sukran
Published: February 2024

Considering water quality is an essential requirement in terms of environmental planning and management. To protect and manage water resources effectively, it is necessary to develop an analytical decision-support system. In this study, a systematic approach was suggested to evaluate the lake water quality. The methodology includes the prediction of the values in different locations of the lakes from experimental data through inverse distance weighting (IDW) method, creation of maps by using Geographic Information System (GIS) integrated with analytic hierarchy process (AHP) from multi-criteria decision analysis (MCDA), reclassification into five class, combining the time-related spatial data into a single map to predict the whole lake water quality from the data of sampling points, and finally overlapping the final maps with topography/geology and land use. The proposed approach was verified and presented as case study for Meke and Acigol Lakes in Konya/Turkey which were affected by human and natural factors although they have ecological, hydromorphological, and socio-economic importance. In the proposed approach, categorizing water quality parameters as “hardness and minerals,” “substrates and nutrients,” “solids content,” “metals,” and “oil-grease” groups was helpful for AHP with the determined group weights of 0.484, 0.310, 0.029, and 0.046, respectively. Assigning weights within each group and then assigning weights between groups resulted in creating accurate final map. The proposed approach is flexible and applicable to any lake water quality data; even with a limited number of data, the whole lake water quality maps could be created for assessment.
Stationarity and cycles in the energy consumption in the United States
Authors: Presno María José , Landajo Manuel
Published: February 2024

The purpose of this paper is twofold: analyzing stationarity of energy consumption by source in the United States and studying their cycles and pairwise synchronization. We study a panel of nine time series of monthly energy consumption for the period 1973–2022. Four of the series (namely coal, natural gas, petroleum, and nuclear electric power consumption) are non-renewables, whereas the remaining ones (hydroelectric power, geothermal, biomass, solar, and wind energy consumption) are renewable energy sources. We employ a nonparametric, panel stationarity testing approach. The results indicate that most of the series may be trend-stationarity, with nuclear and geothermal energy consumption being the only exceptions. Additionally, a study on potential cycles in the series of energy consumption by source is carried out, and subsequently we analyze pairwise concordance between states of different energy sources and between states of energy sources and the business cycle. Significant correlations are detected in the latter analysis, which are positive in the case of fossil fuel sources and negative for two renewable sources, namely geothermal and biomass energy consumption.
Enhancing groundwater vulnerability assessment for improved environmental management: addressing a critical environmental concern
Authors: Abduljaleel Yasir , Amiri Mustapha , Amen Ehab Mohammad , Salem Ali , Ali Zana Fattah , Awd Ahmed , Lóczy Dénes , Ghzal Mohamed
Published: February 2024

Groundwater serves as a primary water source for various purposes. Therefore, aquifer pollution poses a critical threat to human health and the environment. Identifying the aquifer’s highly vulnerable areas to pollution is necessary to implement appropriate remedial measures, thus ensuring groundwater sustainability. This paper aims to enhance groundwater vulnerability assessment (GWVA) to manage aquifer quality effectively. The study focuses on the El Orjane Aquifer in the Moulouya basin, Morocco, which is facing significant degradation due to olive mill wastewater. Groundwater vulnerability maps (GVMs) were generated using the DRASTIC, Pesticide DRASTIC, SINTACS, and SI methods. To assess the effectiveness of the proposed improvements, 24 piezometers were installed to measure nitrate concentrations, a common indicator of groundwater contamination. This study aimed to enhance GWVA by incorporating new layers, such as land use, and adjusting parameter rates based on a comprehensive sensitivity analysis. The results demonstrate a significant increase in Pearson correlation values (PCV) between the produced GVMs and measured nitrate concentrations. For instance, the PCV for the DRASTIC method improved from 0.42 to 0.75 after adding the land use layer and adjusting parameter rates using the Wilcoxon method. These findings offer valuable insights for accurately assessing groundwater vulnerability in areas with similar hazards and hydrological conditions, particularly in semi-arid and arid regions. They contribute to improving groundwater and environmental management practices, ensuring the long-term sustainability of aquifers.
The Credit Suisse bailout in hindsight: not a bitter pill to swallow, but a case to follow
Authors: Böni Pascal , Zimmermann Heinz
Published: February 2024

In March 2023, Credit Suisse (CS) was bailed out based on the implementation of emergency law to the exclusion of all shareholder rights of the involved banks, likely violating basic principles of monetary order. However, this paved the way for a support plan amounting to 209 billion Swiss francs and the implementation of a state-orchestrated emergency merger with UBS. By the end of August 2023, UBS had fully paid back the support plan and reported the biggest-ever quarterly profit for a bank, amounting to 29 billion US dollars. UBS also started to absorb CS’s domestic business, thereby abandoning the branding of an institution with a history of 167 years. Popular accounts claim the plan could be considered a success and that there was no cost because the money was repaid. We critically evaluate the CS bailout, shedding light on key issues such as bailout-induced wealth transfers, the “too-big-to-fail” challenge, the likelihood of bank bailouts, the optimal level of bank equity, the doctrinal separation of solvency and liquidity, and the benefits of ex-ante market-based bank fragility indicators rather than ex-post accounting indicators. We infer a financial economist’s perspective, in which supervision is expanded by ex-ante market-based risk indicators, unweighted capital ratios are increased to adequately reflect large bank risks, and ex-ante paid liquidity options are introduced. Finally, we call for a public debate on the willingness of taxpayers to implicitly finance the too-big-to-fail risk of large banks.
Social acceptance of district heating: evidence from the Netherlands
Authors: Onencan A. M. , Ou J. , de Koning J. I. J. C.
Published: February 2024

The Netherlands Climate Change Agreement aims to reduce CO2 emissions and seismic events by halting natural gas usage by 2050. This will require widespread societal acceptance by 90% of households. The study investigates the social acceptance of a district heating network (DHN) among social housing tenants in Haarlem, Netherlands. The findings of a survey administered to ninety-five tenants revealed a substantial level of support for the DHN project. A significant portion of respondents, 75%, expressed their approval for the DHN, surpassing the legally required threshold of 70% for implementing building retrofits. Findings imply that although the participants possess an adequate comprehension of the rationale for energy transition, their familiarity with the precise particulars and practical information pertaining to the proposed transition to DHN is inadequate. The level of trust in housing corporations, energy providers, and the municipality is uniformly low, indicating a lack of institutional trust. Generally, the interpersonal trust among tenants tends to be lower than their trust in the broader public, which in turn restricts their capacity for self-organization and exercising influence over energy institutions. Although DHNs are typically regarded as environmentally friendly and secure, there are several challenges that need to be addressed, including the uncertainty about who will cover the costs of transitioning and the doubts surrounding DHN feasibility (warmth and reliability). We suggest implementing interventions to improve tenants' comprehension of the DHN project's particulars (capability), provide practical information regarding costs and feasibility (motivation), and foster trust at both interpersonal and institutional levels (opportunity).
Enthalpy of Formation of Calcium and Magnesium Oxide Obtained by Knudsen Effusion Mass Spectrometry
Authors: Halwax Alexander , Sergeev Dmitry , Müller Michael , Schenk Johannes
Published: February 2024

Calcium and magnesium oxide are important components of metallurgical slag systems. However, the literature values for the standard enthalpy of formation $${{\Delta }_{f}H}_{298}^{^\circ }$$

Δ
f

H

298

∘

of both oxides exhibit large variations in some cases. Since $${{\Delta }_{f}H}_{298}^{^\circ }$$

Δ
f

H

298

∘

is crucial for the modeling and prediction of equilibrium states and, thus, also for process optimization; it was determined by Knudsen effusion mass spectrometry (KEMS). Pure CaO as well as MgO were investigated in an iridium Knudsen cell. For this purpose, the intensities of the main species present in the gas phase were recorded in a temperature range between 1825 K to 2125 K and 1675 K to 2075 K, respectively, and their partial pressures were obtained. It was observed that CaO and MgO evaporated congruently with the main species in the gas phase, Ca, Mg, O, and O2. The experimental vapor pressures of the gas species in the study of MgO are in good agreement with the calculated values using FactSageTM 7.3 and the FactPS database, while those for the evaporation of CaO show significant differences. These calculations are based on available thermodynamic information, including the Gibbs energy functions of CaO(s), Ca(g), MgO(s), Mg(g), O(g), and O2(g). After calculating the partial pressures and equilibrium constants of reactions, an average formation enthalpy of $${{\Delta }_{f}H}_{298}^{^\circ }$$

Δ
f

H

298

∘

= − 624.5 ± 3.5 kJ/mol for CaO(s) and $${{\Delta }_{f}H}_{298}^{^\circ }$$

Δ
f

H

298

∘

= − 598 ± 10 kJ/mol for MgO(s) based on the third law method of thermodynamics were obtained. The deviation of $${{\Delta }_{f}H}_{298}^{^\circ }$$

Δ
f

H

298

∘

for MgO from the previous literature values can be attributed to the use of different ionization cross sections, temperature calibration, and variation of tabulated Gibbs energy functions.
Anticarcinogenic Effects of Gold Nanoparticles and Metformin Against MCF-7 and A549 Cells
Authors: Yeşildağ Ali , Kızıloğlu Halime Topal , Dirican Ebubekir , Erbaş Elif , Gelen Volkan , Kara Adem
Published: February 2024

Metformin is commonly prescribed to people with diabetes. Metformin has been shown in previous studies to be able to prevent the growth of cancer cells. This study aims to investigate the effects of metformin and gold nanoparticles in MCF7 breast cancer and A549 lung cell lines. The effects of metformin and gold nanoparticles on MCF7 breast cancer and A549 lung cells were determined on cells grown in 24 h cell culture. MCF-7 and A549 cells were incubated for 24 h with the treatment of escalating molar concentrations of ifosfamide. The MTT assay was used to determine the cytotoxicity of metformin toward MCF7 and A549 cell lines. The expression of Bax, BCL2, PI3K, Akt3, mTOR, Hsp60, Hsp70, and TNF-α was measured by RT-PCR. Metformin and gold nanoparticles inhibited the proliferation of MCF-7 and A549 cells in a dose and time-dependent manner with an IC50 value of 5 µM and 10 µg/mL. RT-PCR assays showed ifosfamide + metformin + gold nanoparticles significantly reduced the expression of BCL2, PI3K, Akt3, mTOR, Hsp60 and Hsp70 and increased the expression of TNF-α and Bax. The findings obtained in this study suggest that further studies should be conducted, and metformin and gold nanoparticles can be used in breast cancer and lung cancer treatments.
Melatonin Modulates Cell Cycle Dynamics and Promotes Hippocampal Cell Proliferation After Ischemic Injury in Neonatal Rats
Authors: Canonico Barbara , Carloni Silvia , Montanari Mariele , Ambrogini Patrizia , Papa Stefano , Alonso-Alconada Daniel , Balduini Walter
Published: February 2024

Promoting neural cell proliferation may represent an important strategy for enhancing brain repair after developmental brain injury. The present study aimed to assess the effects of melatonin on cell proliferation after an ischemic injury in the developing hippocampus, focusing on cell cycle dynamics. After in vivo neonatal hypoxia–ischemia (HI), hippocampal cell cycle dynamics were assessed by flow cytometry, together with histological evaluation of dentate gyrus cellularity and proliferation. Melatonin significantly increased the number of proliferating cells in the G2/M phase as well as the proliferating cell nuclear antigen (PCNA) and doublecortin (DCX) labeling reduced by HI. In vivo BrdU labeling revealed a higher BrdU-positivity in the dentate gyrus of ischemic rats treated with melatonin, an effect followed by increased cellularity and preserved hippocampal tissue integrity. These results indicate that the protective effect of melatonin after ischemic injury in neonatal rats may rely on the modulation of cell cycle dynamics of newborn hippocampal cells and increased cell proliferation.
Giving Consent to the Ineffable
Authors: Villiger Daniel
Published: February 2024

A psychedelic renaissance is currently taking place in mental healthcare. The number of psychedelic-assisted therapy trials is growing steadily, and some countries already grant psychiatrists special permission to use psychedelics in non-research contexts under certain conditions. These clinical advances must be accompanied by ethical inquiry. One pressing ethical question involves whether patients can even give informed consent to psychedelic-assisted therapy: the treatment’s transformative nature seems to block its assessment, suggesting that patients are unable to understand what undergoing psychedelic-assisted therapy actually means for them and whether it aligns with their values. The present paper argues that patients often have sufficient knowledge to give informed consent because they know that they want to change their negative status quo and that psychedelic-assisted therapy offers an effective way to do so. Accordingly, patients can understand what the transformative nature of psychedelic-assisted therapy means for them and a make a value-aligned choice even if they are unable to anticipate the manifestation of a psychedelic experience.