Latest Articles

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  Section: Animal Science ; Topics: Agricultural sciences, Environmental sciences, Sustainability science

  Yellow mealworm (Tenebrio molitor) 2020–2025 evidence for circular bioeconomy and key sustainability constraints

  Debache, Karim  

  10.24072/pcjournal.722 - Peer Community Journal, Volume 6 (2026), article no. e42

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  The yellow mealworm, Tenebrio molitor (T. molitor), is increasingly considered a promising protein and lipid source for circular bioeconomy strategies in food and feed. Interest is driven by the need to diversify protein supplies and reduce environmental footprints, but feasibility depends on safety, regulation, and scalable operating conditions. Alongside industrial systems, low-input models adapted to arid conditions have been proposed, yet evidence remains heterogeneous and context-dependent. This review covers developments between 2020 and 2025, a period that coincides with accelerated EU novel food assessments and a rapid expansion of applied research on processing, safety, and valorization, with a focus on scientific progress and regulatory approvals such as those issued by EFSA in Europe. Several new applications have emerged, including enzymatic hydrolysates, lipid recovery, and the extraction of chitosan from exuviae. Uses now span animal nutrition, biodegradable materials, and bioactive food ingredients. Life-cycle assessments often report lower greenhouse gas emissions and land use than conventional livestock, but outcomes are sensitive to energy inputs, feed substrates, and system boundaries. Key constraints include variable frass composition, allergenicity and cross-reactivity risks, regulatory and compliance constraints, and mixed consumer acceptance. For research, priority needs include longer-term safety datasets and field-relevant validation of bioactive claims beyond in vitro assays. For policy and industry, priorities include harmonised criteria for substrate safety and traceability, and transparent supply-chain controls that enable reproducible quality at scale.

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  Section: Ecology ; Topics: Ecology

  Population size estimation when multiple samples carrying the risk of misidentification are taken within the same capture occasion from the same individual

  Fraysse, Remi;   Choquet, Remi;   Pradel, Roger  

  10.24072/pcjournal.711 - Peer Community Journal, Volume 6 (2026), article no. e41

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  Although non-invasive sampling is increasingly used in capture-recapture (CR) monitoring, it carries a risk of misidentification that, if ignored, causes an overestimation of population size. Models that deal with misidentification have been proposed. However, these models assume that only one sample can be collected per individual at one occasion. This is not true for several monitoring programs based on DNA, for example for those that extract the DNA from faecal samples. The models do not take repeated observations into account, leading to biased estimates. In this paper, we develop an approach that extends the latent multinomial model (LMM) of Link et al. (2010) using a Poisson distribution to model the number of samplings of the same individual on a given occasion. We then conduct simulations to test how our new model performs. As an illustration, we applied the new Poisson model to a collection of Eurasian otter faeces (Lampa et al., 2015). Our model yields unbiased estimates of population size when the expected number of samples per individual ($\lambda$) is sufficiently high: simulations with $\lambda \geq 0.36$ and five capture occasions or with $\lambda \geq 0.23$ and seven or more occasions. In contrast, when $\lambda = 0.11$ (corresponding to about 42%, 53% and 62% of the individuals being detected with respectively 5, 7 and 9 occasions), the population size is consistently underestimated. Applying the model to the otter dataset confirms the presence of misidentifications, consistent with the authors’ expectations. Our findings indicate that repeated observations can be modelled without bias. The application on otters shows that our model is necessary to accurately estimate population size in presence of misidentification and repeated observations. 

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  Section: Archaeology ; Topics: Archaeology, Engineering, Computer sciences ; Conference: CAA2025

  Crossing software boundaries: From iDig and ODK to QField for archaeological field documentation

  Sgouropoulos, Kyriakos;   Chrysafakoglou, Periklis;   Ladenis, Ilias

  10.24072/pcjournal.712 - Peer Community Journal, Volume 6 (2026), article no. e40

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  The rapid development of technology and its integration into archaeological practices have greatly benefited archaeologists. Despite the many advantages of using technological tools, archaeologists face a major risk related to their limitations and technological dependence on specific software platforms. This article presents two case studies in which archaeological teams transitioned to open-source software that natively supports GIS technologies, replacing previously closed or limited digital frameworks. The first case concerns the transition from the iDig recording system to the QField ecosystem for excavation documentation. The second case presents a similar technological transition where QField replaced an ODK-based data collection framework in the context of surface survey. Each case includes a comparison of the software solutions used, focusing on their features and performance in archaeological workflows. The purpose of the article is to highlight that the long-term improvement of performance in archaeological field documentation is not tied to any single software, but depends mainly on the team’s ability to transition and adapt to new digital environments. Archaeological teams can benefit far more from embracing openness, interoperability, and long-term sustainability through the use of open-source software.

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  Section: Neuroscience ; Topics: Neuroscience, Psychological and cognitive sciences, Physiology

  MLIB: an easy-to-use Matlab toolbox for the analysis of extracellular spike data

  Stüttgen, Maik C.  

  10.24072/pcjournal.713 - Peer Community Journal, Volume 6 (2026), article no. e39

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  The analysis of neurophysiological data obtained from extracellular recordings is usually performed using a number of standard techniques. These include a) the extraction of action potentials from voltage traces and their subsequent classification, i.e., spike sorting, b) the visualization of activity, e.g., by constructing raster plots, peri-stimulus time histograms (PSTHs), and spike density functions, and c) the quantification of neuronal responses according to experimental variables such as stimulation or movement. Here I present a Matlab toolbox containing functions for the visualization and analysis of neuronal spike data. The toolbox consists entirely of one-liners that operate on vector or matrix inputs, i.e., spike and event timestamps or waveform samples. The toolbox functions provide both basic (constructing PSTHs, computing waveform characteristics etc.) and more advanced functionality, such as dimensionality reduction of multi-neuron recordings. While offering a high degree of versatility, the toolbox should also be accessible to newcomers to neurophysiology, such as (under)graduate students or PhD students. The functions are streamlined, easy to use, and each function is extensively introduced with several examples using real or simulated data. In addition, many functions provide fully formatted plots on request, even with minimal Matlab knowledge.