Current Data Research Articles

Cooling rate and turbulence in the intracluster medium of the cool-core cluster Abell 2667

We present a detailed analysis of the thermal X-ray emission from the intracluster medium in the cool-core galaxy cluster Abell 2667 at z=0.23. Our main goal is to detect low-temperature ($<2$ keV) X-ray emitting gas associated with a potential cooling flow connecting the hot intracluster medium reservoir to the cold gas phase responsible for star formation and supermassive black hole feeding. We combined new deep XMM-Newton EPIC and RGS data, along with archival Chandra data, and performed a spectral analysis of the emission from the core region. We find 1σ upper limits on the fraction of gas cooling equal to ∼ 40 rm M_ ⊙ yr^ and ∼ 50-60 rm M_ ⊙ yr^ in the temperature ranges of 0.5-1 keV and 1-2 keV, respectively. We do not identify OVII, FeXXI-FeXXII, and FeXVII recombination and resonant emission lines in our RGS spectra, implying that the fraction of gas cooling below 1 keV is limited to a few tens of solar masses per year at maximum. We do detect several lines (particularly SiXIV, MgXII, FeXXIII/FeXXIV, NeX, OVIIIα) from which we are able to estimate the turbulent broadening. We obtain a 1σ upper limit of ∼ 320 km/s, which is much higher than the one found in other cool-core clusters such as Abell 1835, suggesting the presence of some mechanisms that boost significant turbulence in the atmosphere of Abell 2667. Imaging analysis of Chandra data suggests the presence of a cold front possibly associated with sloshing or with intracluster medium cavities. However, current data do not allow us to clearly identify the dominant physical mechanism responsible for turbulence. These findings show that Abell 2667 is not different from other, low-redshift, cool-core clusters, with only upper limits on the mass deposition rate associated with possible isobaric cooling flows. Despite the lack of clear signatures of recent feedback events, the large upper limit on the turbulent velocity leaves room for significant heating of the intracluster medium, which may quench cooling in the cool core for an extended period, albeit also driving local intracluster medium fluctuations that will contribute to the next cycle of condensation rain.

Transfer Learning-Based Health Monitoring of Robotic Rotate Vector Reducer Under Variable Working Conditions

Due to their precision, compact size, and high torque transfer, Rotate vector (RV) reducers are becoming more popular in industrial robots. However, repetitive operations and varying speed conditions mean that these components are prone to mechanical failure. Therefore, it is important to develop effective health monitoring (HM) strategies. Traditional approaches for HM, including those using vibration and acoustic emission sensors, encounter such challenges as noise interference, data inconsistency, and high computational costs. Deep learning-based techniques, which use current electrical data embedded within industrial robots, address these issues, offering a more efficient solution. This research provides transfer learning (TL) models for the HM of RV reducers, which eliminate the need to train models from scratch. Fine-tuning pre-trained architectures on operational data for the three different reducers of health conditions, which are healthy, faulty, and faulty aged, improves fault classification across different motion profiles and variable speed conditions. Four TL models, EfficientNet, MobileNet, GoogleNet, and ResNET50v2, are considered. The classification accuracy and generalization capabilities of the suggested models were assessed across diverse circumstances, including low speed, high speed, and speed fluctuations. Compared to the other models, the proposed EfficientNet model showed the most promising results, achieving a testing accuracy and an F1-score of 98.33% each, which makes it best suited for the HM of robotic reducers.

Возрастные особенности динамики альфа-ритма: краткий обзор

<p>In this mini-review, the age-related features of alpha rhythm dynamics, its generation sources, and its connection to cognitive functions are discussed. The review focuses on a brief systematization of data regarding the alpha rhythm of human brain bioelectrical activity and its informativeness in determining the biological age of the human brain. The alpha rhythm is characterized by high individual stability and exhibits pronounced age-related dynamics in its U-shape. The peak frequency of the alpha rhythm increases from infancy to young adulthood and then decreases during brain aging. Discussions about the sources of alpha rhythm generation are still ongoing. Current data show a lack of a clear connection between the peak frequency of alpha rhythm and human cognitive abilities and intelligence. Parameters of the alpha rhythm, such as individual stability, genetic predisposition, and age-related characteristics, make it a promising marker for both normative development and brain aging in determining cognitive and biological age.</p>

Virginia Memory Project: Using the Healthy Brain Initiative Roadmap to design a statewide dementia registry

AbstractINTRODUCTIONThe Virginia Memory Project (VMP) is a statewide epidemiological registry for Alzheimer's disease and related disorders (ADRD) and other neurodegenerative conditions. It aims to support dementia research, policy, and care by leveraging the Centers for Disease Control (CDC) Healthy Brain Initiative (HBI) Roadmap.METHODSTo capture comprehensive data, the VMP integrates self‐enrollment and automatic enrollment using Virginia's All‐Payer Claims Database (APCD). It also adapts Behavioral Risk Factors Surveillance Survey (BRFSS) modules for self‐reported cognitive and caregiving data, offering connections to research, clinical services, and education.RESULTSVirginia successfully codified the VMP in the 2024 general assembly session.DISCUSSIONThe VMP demonstrates a novel approach to Alzheimer's Disease and Related Disorders (ADRD) surveillance by combining traditional registry functions with community engagement and workforce development. Future efforts will focus on increasing enrollment, especially among underrepresented groups, to enhance data‐driven dementia policy and care in Virginia.Highlights Integrated the Healthy Brain Initiative (HBI) domains into the newest statewide epidemiological dementia registry in the Commonwealth of Virginia. Collected data and identified gaps in the current research related to dementia and Alzheimer's related diseases. Aimed to mitigate barriers to dementia registry enrollment by identifying significant underdiagnosis and underrepresentation of racial and ethnic minority groups. Developed solutions to alleviate the current data and enrollment disparities and to connect individuals to research, physicians, and community groups.

Sustainable Development and Security: Key Challenges to Achieving SDG 16

Introduction. SDG 16, one of the 17 Sustainable Development Goals adopted by the UN General Assembly in 2015, aims to build peaceful inclusive societies for sustainable development, ensure equitable access to justice everywhere, and build effective, accountable and inclusive institutions at all levels. The subject of the study is characteristic features of the current progress in the realization of SDG 16 targets, as well as identifying further prospects for its achievement at the global level. The relevance of the study stems from the fact that SDG 16, like all other SDGs, is critical to ensuring a prosperous future for all humankind, yet SDG 16 is one of the goals where progress has been very slow and some indicators have regressed. The aim of the study is to analyze the available statistical data on the results of the implementation of SDG 16, to identify current obstacles to its achievement, and to characterize future prospects taking into account the current realities.Materials and Methods. The study is based on the analysis of statistical data on the performance of the world community in the process of achieving the SDGs, such as the Global Sustainable Development Report, the Global SDG 16 Progress Reports for 2023 and 2024.Research results. Based on the analysis, the article offers conclusions about the main reasons that hinder progress towards SDG 16, including the persistently high level of violence, the problem of data quality and accessibility, lack of funding.Discussion and Conclusion. The results suggest that achieving the stated goals of SDG 16 by 2030 is highly unlikely, so the global community needs to address the current funding and data quality issues as soon as possible, and to ensure greater consistency between approaches in measuring progress towards SDG 16.

Unlocking ultra-deep wide-field imaging with sidereal visibility averaging

abstract Producing ultra-deep high-angular-resolution images with current and next-generation radio interferometers introduces significant computational challenges. In particular, the imaging is so demanding that processing large datasets, accumulated over hundreds of hours on the same pointing, is likely infeasible in the current data reduction schemes. In this paper, we revisit a solution to this problem that was considered in the past but is not being used in modern software: sidereal visibility averaging (SVA). This technique combines individual observations taken at different sidereal days into one much smaller dataset by averaging visibilities at similar baseline coordinates. We present our method and validated it using four separate 8-hour observations of the ELAIS-N1 deep field, taken with the International LOw Frequency ARray (LOFAR) Telescope (ILT) at 140 MHz. Additionally, we assessed the accuracy constraints imposed by Earth's orbital motion relative to the observed pointing when combining multiple datasets. We find, with four observations, data volume reductions of a factor of 1.8 and computational time improvements of a factor of 1.6 compared to standard imaging. These factors will increase when more observations are combined with SVA. For instance, with 3000 hours of LOFAR data aimed at achieving sensitivities of the order of μJy beam^-1 at sub-arcsecond resolutions, we estimate data volume reductions of up to a factor of 169 and a 14-fold decrease in computing time using our current algorithm. This advancement for imaging large deep interferometric datasets will benefit current generation instruments, such as LOFAR, and upcoming instruments such as the Square Kilometre Array (SKA), provided the calibrated visibility data of the individual observations are retained. abstract

Recommendations of Multiple Sclerosis and Neuroimmunology Section of Polish Neurological Society and Immuno-oncology Section of Polish Society of Oncology on oncological risk in patients with multiple sclerosis undergoing immunomodulatory therapy.

Multiple sclerosis (MS) is an autoimmune demyelinating disease of the central nervous system (CNS) that is usually diagnosed between the ages of 20 and 40. Changes in the immune system also observed in cancer may suggest a higher prevalence of cancer in the MS patient population. In recent years, many highly effective immunosuppressive drugs have been introduced into disease-modifying therapy (DMT) which may be associated with a higher risk of cancer development in patients with MS. This paper presents current data on the oncological risk of individual drugs. In addition, it provides recommendations on the management for qualifying for DMT and monitoring the safety of the therapy from anoncological perspective.

A Study on an Artificial Intelligence Prediction Method for Current Fluctuations Based on Multivariate Analysis

With the increasing complexity of power systems and higher demands for stability, accurately predicting current fluctuations is crucial. This study proposes an artificial intelligence prediction method combined with multivariate analysis, utilizing multidimensional information such as historical current data, new energy generation output, and meteorological conditions, and modeling through Long Short-Term Memory (LSTM) networks. This method optimizes the data processing process and improves the model's ability to adapt to dynamic changes in data. The results show that the proposed method effectively enhances the prediction accuracy of current fluctuations, providing practical value for grid operation and maintenance as well as fault warnings

Compact complementary slot resonator antenna with L-Probe feed excitation for wireless communication

ABSTRACT This study presents a concise design of a complementary slot resonator antenna employing the L-probe feed excitation. The antenna features a compact size of 0.086λ0 × 0.086λ0 × 0.006λ0, unlike the wire-loaded miniaturised slot antenna, which has a greater height. The extensive electrical path length of the complementary slot resonator results in the proposed antenna resonating at 434 MHz, a frequency substantially lower than the wavelength (λ0). The work explores essential parameters, such as return loss, radiation patterns and efficiency, highlighting a consistent correlation between simulation and measurement results through a parametric study. In simulation, the antenna exhibits an efficiency of 92.19%, while in practical measurements, it maintains a high efficiency of 89.73%. In addition, the study incorporates simulated input impedance and surface current distribution data to enhance the comprehensive analysis of the antenna design. The antenna is fabricated using copper metal due to its excellent electrical conductivity properties and the achieved resonant frequency has applications in various wireless communication scenarios.

The basis of bacteriological safety in the neonatal intensive care unit (literature review)

Background. According to world statistics, 7% of patients out of 100 in high-income countries and 15% of patients out of 100 in low- and middle-income countries develop infections related to medical care. As follows from the report of the World Health Organization, one in four cases of hospital sepsis that occurred in the intensive care unit is caused by hospital strains. On average, one in ten of these patients has a hospital-acquired infection that is fatal. The high-risk group includes patients in intensive care units, including newborns. In 2023, 28973 cases of neonatal infections (including intrauterine infection) were registered in medical organizations of the Russian Federation. The highest rates of neonatal morbidity were recorded in the Sverdlovsk Region (42.2%), the Trans-Baikal Territory (33.0%), the Novosibirsk Region (26.0%), the Chelyabinsk Region (22.4%), the Krasnoyarsk Territory (21.8%) and the Irkutsk Region (21.3%). Thus, infection prevention and control strategies aimed at both patients and their environment are of paramount importance in neonatal intensive care units.Objective. To summarize current relevant data on the prevention of hospital infections in neonatal intensive care units.Materials and methods. A literature review was conducted using the MEDLINE database (PubMed) as of December 2024 using keywords and a filter: randomized controlled trial, meta-analysis, systematic review.Results. This review summarizes the main data on the prevention of hospital infections in neonatal intensive care units. According to the literature, ensuring bacteriological safety in relation to the development of hospital infections depends on many factors: hand hygiene of medical personnel, organization of venous access control, disinfection of medical equipment and premises, compliance with the rules of asepsis and antiseptics when performing invasive manipulations, the introduction of modern approaches in the care of premature infants.Conclusion. There are many tasks in the intensive care unit that require innovative strategies to ensure the safe care of premature newborns. Joint efforts to standardize the processing of specialized equipment, maintain the cleanliness of the environment, comply with vascular access care protocols, adequate hand hygiene, and the active introduction of parents into newborn care are an integral part of the program aimed at preventing nosocomial infections. Active cooperation between the neonatal intensive care unit and the epidemiological service of the institution will allow us to develop a rational policy for risk management and monitoring of hospital infections.

Constraining differential rotation in γ Doradus stars from the properties of inertial dips

The presence of dips in the gravity mode period spacing versus period diagram of γ Doradus stars is now well established thanks to recent asteroseismic studies. Such Lorentzian-shaped inertial dips arise from the interaction of gravito-inertial modes in the radiative envelope of intermediate-mass main sequence stars with pure inertial modes in their convective core, and allow us to study stellar internal properties. This window onto stellar internal dynamics is extremely valuable in the context of the understanding of angular-momentum transport inside stars, as it allows us to probe rotation in their core. We investigate the signature and the detectability of a differential rotation between the convective core and the near-core region inside γ Doradus stars from the properties of inertial dips. We studied the coupling between gravito-inertial modes in the radiative zone and pure inertial modes in the convective core in the sub-inertial regime, allowing for a two-zone differential rotation from the two sides of the core-to-envelope boundary. We solved the coupling equation numerically and matched the result to an analytical derivation of the Lorentzian dip properties. We then used typical values of measured near-core rotation and buoyancy travel time to infer ranges of parameters for which differential core to near-core rotation would be detectable in current Kepler data. We show that increasing the convective core rotation with respect to the near-core rotation leads to a shift of the period of the observed dip to lower periods. In addition, the dip gets deeper and thinner as the convective core rotation increases. We demonstrate that such a signature is detectable in Kepler data, given appropriate dip-parameter ranges and near-core structural properties. Studying the dip properties in asteroseismic data thus allows us to access core to near-core radial differential rotation and to better understand the transport of angular momentum at convective--radiative interfaces in intermediate-mass main sequence stars.

Exploration & Exploitation: A Unified Framework for Data Purification & Augmentation in Recommendation Systems

In the context of recommendation scenarios, the utilization of data purification and data augmentation methodologies has demonstrated their efficiency in enhancing the quality of representations. Nevertheless, within an open environment, the constrained nature of interaction data and the diverse range of interaction intentions present formidable challenges, giving rise to insufficient generalization ability and generalization bias in these methodologies. To address this issue, in this paper we introduce Exploitation & Exploration: A Unified Framework for Data Purification & Augmentation in Recommendation Systems, which not only ensures the precise purification of current data but also delves into potential noisy data for further exploration. To be specific, based on the traditional collaborative filtering method calculating user-item correlation, we first implement an efficient multi-head SENet block to remove potential noise from the interaction data. After this, we deploy a diffusion module to remove the added adversarial noise based on its ability to denoise all kinds of noise. And finally we use mutual-learning method to coordinate two parts' learning. We conducted experiments on three publicly available datasets, evaluating our model against current state-of-the-art algorithms in recommendation robustness tasks. The experimental results validate the effectiveness of our model.

Evaluation of the Hydrodynamic Impacts of Tidal Turbine Arrays in Jiaozhou Bay

In this paper, a hydrodynamic model of Jiaozhou Bay was developed using the Regional Ocean Modeling System and validated against observed tidal levels and current data. The model accurately characterizes the tidal and current features of the region. Based on this model, the spatial and temporal distributions of flow fields and tidal energy resources were analyzed. A 100-turbine tidal power plant was simulated utilizing a momentum-based approach that accounts for resource distribution, bathymetry, topography, and turbine parameters. The resulting hydrodynamic changes, including velocity variations peaking at 0.5 m/s within the turbine deployment zone and tidal level shifts confined to the bay (maximum change in ~10 cm), emphasize the importance of localized environmental assessments. However, the findings also highlight broader considerations for the sustainable development of tidal energy in semi-enclosed bays worldwide, where strategic siting and design can mitigate larger ecological disturbances. These findings may provide a scientific foundation for balancing clean energy extraction with minimal environmental impact, thus contributing to global efforts to develop more resilient and sustainable coastal energy systems.

Rabies transmitted from vampires to cattle: An overview

Rabies is a zoonotic infectious disease of global distribution that impacts human and animal health. In rural Latin America, rabies negatively impacts food security and the economy due to losses in livestock production. The common vampire bat, Desmodus rotundus, is the main reservoir and transmitter of rabies virus (RABV) to domestic animals in Latin America. Desmodus rotundus RABV is known to impact the cattle industry, from small farmers to large corporations. We assessed the main patterns of rabies in cattle attributed to D. rotundus RABV across Latin America. Epidemiological data on rabies from Latin America were collected from the Pan American Health Organization spanning the 1970–2023 period. Analyses revealed an average of 450 outbreaks annually for the countries where D. rotundus is distributed, with at least 6 animals dying in each outbreak. Brazil, Colombia, Peru, and Mexico were the Latin American countries with the highest number of rabies outbreaks during the study period and are the most affected countries in recent years. Findings suggest a re-emergence of bat-borne rabies in the region with more outbreaks reported in recent years, especially during the 2003–2020 period. Rabies outbreaks in cattle in the 2000–2020 period were significantly more frequent than in previous decades, with an increase in cross-species transmission after 2002. The size of outbreaks, however, was smaller in recent years, involving lower cattle mortality. Peru, El Salvador, and Brazil showed a strong association (R = 0.73, p = 0.01) between rabies incidence in D. rotundus (rates per million humans: 1.61, 0.94, and 1.09, respectively) and rabies outbreaks in cattle (rates per million cattle: 465.85, 351.01, and 48.22, respectively). A sustained, standardized, and widespread monitoring of D. rotundus demography and health could serve to inform an early warning system for the early detection of RABV and other bat-borne pathogens in Latin America. Current data can be used to forecast when, where, and in which intensity RABV outbreaks are more likely to occur in subtropical and tropical Latin America. A decrease in the size of outbreaks could suggest that strategies for epidemic management (e.g., education, early diagnosis, vaccination) have been effective. The increase in the number of outbreaks could suggest that the factors facilitating cross-species transmission could be on the rise.

Re-evaluation of the impact of wall retention on Tritium-self-sufficiency in fusion reactors

Abstract In recent years several publications have claimed that the retention of tritium (T) in the first wall armor material poses a limitation on when a fusion reactor becomes T-self-sufficient. While the prediction on wall retention therein are correct, the model applied to assess the T-self-sufficiency is based on wrong assumptions and thus, the importance of T-retention in the first wall is greatly overestimated. In this publication the predictions on T-retention in the first wall armor components are included in state of the art residence time models of the entire T-cycle. These calculations show that T-wall-retention only affects T-self-sufficiency when the T-breeding ratio (TBR) is so low that the power plant is only marginally T-self-sufficient. For TBR values that allow for a finite T-doubling time and maintain a T-reserve inventory, the T-production must be so high, that the T-wall-retention is insignificant. The paper will explain the error in the previous T-self-sufficiency estimates, how to correct them and what this means for the conclusions drawn by previous publications. Then an augmented residence time model will be presented, that can include diffusion/trapping model based, time dependent wall loss data. This augmented model results in orders of magnitude higher T-retention in the first wall compared to current assumptions in residence time models. Still, it is negligible compared to the T-content in the entire T-cycle. Thus it can be concluded that based on current material data T-retention in the first wall armor will not affect T-self-sufficiency.

EXPRESS: Design and Analysis of Efficient Sequencing Policies for Linear Cold Storage Devices

In this paper, we investigate the problem of sequencing data requests for linear devices, such as magnetic tapes, to minimize response time in cold-storage solutions for archival data. Tapes are the technology of choice for long-term storage due to their reliability, low costs, security, and significant energy savings. However, physical limitations on tape pose challenges to policy implementation, which must be scalable on low-power hardware. We provide a theoretical and numerical analysis of existing policies and introduce new ones, identifying cases where each is applicable and evaluating their theoretical performance in terms of the number of requested files. In particular, we show that the standard first-in, first-out (FIFO) policy can be arbitrarily inefficient and investigate novel constant-ratio approximations and polynomial-time procedures. If data on the frequency with which each file is accessed is available, we consider a dynamic programming procedure to minimize a stochastic variant of the problem, providing a constant-time approximation for arbitrary file requests. We also investigate a quality criterion based on makespan and explore online variants of the problem. Our numerical analysis, conducted on both synthetic and real-world data from an industry partner, offers insights into when each policy is most appropriate, identifying cases where the proposed algorithms significantly outperform traditional policies, like FIFO, in terms of average reading times. This study has managerial implications, as current data retrieval practices in data centers are often limited to traditional policies with unknown theoretical performance. Our methodological and numerical analysis provides evidence of the value in appropriately sequencing requests based on tape structure, guiding algorithm choice and highlighting underlying trade-offs in response times.

Exploring voyeurism: a review of research

Introduction and Objective: Voyeurism is characterized by recurrent and intense sexual arousal derived from observing unsuspecting individuals who are naked, disrobing, or engaging in sexual activity. Suggested risk factors for developing voyeurism include childhood sexual abuse, substance misuse, hypersexuality, emotional dysregulation, poor mental health, maladaptive coping strategies, and external pressures The aim of this publication is to discuss various aspects of voyeurism based on the latest literature.Review Methods: The PubMed database was searched to find scientific articles in which the terms “voyeurism” or “voyeuristic” appear in the title, abstract, or keywords.Brief Description of the State of Knowledge: Estimating the global prevalence of voyeurism is challenging due to inconsistent data, with reported rates ranging from over 10% to approximately 30–40%. Studies consistently indicate that voyeuristic behavior is more common among men. It often exhibits a compulsive and repetitive nature and can serve as a precursor to other sexual crimes, such as sexual sadism or pedophilia. Treatment primarily involves cognitive behavioral therapy (CBT), with pharmacological support using SSRIs like fluoxetine and paroxetine, showing effectiveness. Summary: The authors highlight the importance of further exploration into this topic and emphasize the need for a more accurate understanding of voyeurism's prevalence in the general population, as current data may be inconclusive.

Combining local monitoring data and scientific models to prioritize conservation for European ground squirrel and safeguard grassland habitats

ContextPromoting grassland habitat networks within agricultural landscapes is essential for supporting biodiversity. However, the characteristics of these networks are often poorly documented, making it difficult to prioritize conservation strategies and effectively protect grassland-dependent species.ObjectivesWe set to identify conservation priorities for (semi)natural grasslands by assessing habitat network characteristics based on a combination of monitoring data and scientific model output for European Ground Squirrel (EGS), a keystone grassland specialist, in agricultural settings of northern Serbia.MethodsWe used the spatially explicit model, LARCH, to determine the current habitat networks and available monitoring data on presence/absence and habitat suitability together with Circuitscape to better understand the characteristics of those networks. The combination of modeling results and monitoring data was used to prioritize conservation measures for each network to support a stable and viable EGS metapopulation.ResultsWe identified 15 habitat networks. Our analysis showed that two of these need no interventions, but most of them need a mix of improving habitat quality and connections within and between the networks to support local populations and the metapopulation overall.ConclusionsResults revealed areas in which spatial adaptation measures (e.g., grassland restoration and corridor development) should be deployed to accommodate the long-term survival of EGS. It might be considered to stop conservation efforts in some abandoned networks as the network characteristics are too poor, and resources should be used to improve habitat networks that are still occupied. Our findings may guide the conservation of (semi)natural grasslands and future sustainable land-use planning in intensively farmed landscapes.

Efficacy of probiotic, prebiotic, synbiotic and postbiotic supplementation on gastrointestinal health in cats: systematic review and meta-analysis.

The clinical efficacy of the use of probiotics, prebiotics, synbiotics and postbiotics (biotics) in cats is unknown, despite their use in daily practice. The objectives of the study is to evaluate the effectiveness of biotic supplementation in treating and preventing gastroenteropathies, and in reducing gastrointestinal signs associated with antibiotics in cats. A systematic review was conducted by searching four databases for publications before August 2, 2024, following a pre-registered protocol. Eligible publications were trials involving healthy cats or those with gastroenteropathies, supplemented with biotics (and an inactive control), studying outcomes such as faecal consistency, faecal microbiota or vomiting. Risk of bias and quality of reports were assessed. Effects were synthesised by meta-analyses and vote counting based on direction of effect. Certainty of evidence was rated using GRADE approach. Twenty reports were included, presenting unclear or low risk of bias. The evidence did not permit a high-confidence evaluation of the effectiveness of biotics, although five of the seven probiotic trials showed beneficial effects on faecal consistency. Synbiotics presented no clinically relevant effect in reducing antibiotics-associated vomiting, with very low certainty, in a meta-analysis including 32 adult cats. Probiotics significantly reduce the Bacillota/Actinomycetota ratio, with low certainty, in a meta-analysis involving 34 healthy young-adult cats. Following vote counting, probiotics improved immune profile in young cats, and increased butyric acid concentration in healthy cats. Current data highlight the need for further research, especially focused on at-risk groups and sick cats, before advocating the use of biotic supplementation.

Streamlining life cycle assessment for complex Mechanical Electrical and Plumbing products – Lessons from lighting

Life Cycle Assessment (LCA) is a framework supporting quantification of a product’s environmental impacts. Such data is required for comprehensive assessment of carbon emission impacts over the full life-cycle of products and buildings. With policymakers and the private sector pursuing decarbonisation goals, the need to streamline development of LCA data for Mechanical, Electrical and Plumbing (MEP) items has increased. MEP practitioners are tailoring existing LCA frameworks to accommodate supply chain complexity and unique use-phase scenarios. In lighting, LCA leadership is being driven by designers from consulting/engineering firms and manufacturers committed to identifying data gaps, inconsistencies, and uncertainty in the application of LCA. In 2025, lighting’s first Industry-Average LCA Report will be published as the result of an industry-led, international, collective analysis of five commonly used architectural luminaires. The findings suggest LCA development may be streamlined by articulating the role of manufacturers and designers in accelerating the closure of identified data gaps and adoption of consistent, industry-agreed interpretation of LCA for complex MEP items. Strategies include approaching industry LCA as a design innovation tool rather than compliance issue; assembling designer-manufacturer forums to incentivize commercial cooperation; improving global harmonisation and harnessing Industry-Average Environmental Product Declarations (EPDs) and other tools as an introduction to more specific analysis. Practical Application With increasing significance in the growth of, and requirement for, the adoption of Life Cycle Assessment (LCA) within the built environment, this paper offers leading practitioners and manufacturers an approach that can help identify current data gaps, areas of inconsistency and uncertainty within the discipline of Mechanical Electrical and Plumbing (MEP) LCA. It suggests how engaging multiple stakeholders, particularly manufacturers and designers, can deliver preliminary results that support wider industry progress within this emerging field of data collection and analysis. This paper also provides lighting manufacturers, sustainability specialists and MEP consultants with a more comprehensive understanding of the environmental impact of lighting.