WSP Sverige (Sweden)

Lameness in dairy cows, primarily caused by claw lesions, generates significant welfare and economic challenges. Hoof trimming is a key preventive measure, with scientific support for 2 to 3 trimmings per lactation. However, the optimal timing of these trimmings has not yet been fully explored. This retrospective cohort study aimed to investigate the association between timing of 2 hoof trimmings during first lactation and subsequent hoof health and culling in second lactation. Data from 10,349 primiparous cows across 185 Swedish dairy herds (2015-2018) were analyzed. Multivariable mixed-effect logistic (models L1 and L2) and multinomial logistic regression models (models ML1 and ML2) assessed associations with hoof health in early second lactation (within 90 DIM) and survival during second lactation (within 300 DIM). Explanatory variables included timings of the first and second trimmings, interval between trimmings, hoof health at trimming, and breed. Herd was incorporated as a random effect or cluster to account for herd-level variations. The L1 model indicated that most trimming combinations other than a late first trim (>120 d after calving) coupled with a late second trim (<61 d before calving) significantly reduced the odds of claw lesions. However, the ML2 model showed that the association varied somewhat depending on the type of claw lesion found. The L2 model generally displayed lower odds of culling (dead, euthanized, and slaughtered) for cows trimmed early in first lactation and further from second calving than 60 d. Although the ML2 model revealed no association between timing of trimming and mortality (dead and euthanized), it did find a significant association with being sent to slaughter. In summary, strategic timing of hoof trimming, early in first lactation and well before second calving, can improve hoof health and survival in dairy cows and consequently have the potential to improve animal welfare and sustainability within the dairy sector.

Abstract Simulation of coupled thermo-hydro-mechanical-chemical (THMC) processes in fractured rocks is relevant to many areas of applied geoscience. Groundwater flow and reactive transport (hydro-chemical processes) in hard rocks are primarily controlled by networks of rock fractures, and therefore best modelled in a discrete fracture network, or DFN. By contrast, heat and stress (thermo-mechanical processes) are mediated via the rock mass, and thus best represented as a continuum. Here, we present an approach using dual, coincident meshes, each simulating the relevant processes in their ‘natural’ media. A sequential coupling between thermo-mechanical and hydro(-chemical) processes is achieved by computing the effective stress on individual fracture planes, and updating their mechanical apertures and hydraulic properties at selected times during model simulations. The simulated processes are modelled in PFLOTRAN, using a linear elastic constitutive model for rock deformation. Several updates to the PFLOTRAN code were required to enable this, as verified against analytical test cases and benchmarked against alternative finite element codes. We present an example application using data from a spent nuclear fuel repository in Finland, which simulates the evolution of thermal stress due to radiogenic heating from spent fuel canisters. The results demonstrate how continuum-based thermo-mechanical processes exert an important influence on near-field flows around the repository that can only be accurately captured in a DFN, thus demonstrating the advantages of a dual-media approach.

The paper addresses safety concerns associated with electric micromobility vehicles, particularly e-scooters, which accounted for 1% of trips but nearly 4% of traffic accidents in Sweden, 2019. To mitigate potential risks from increased micromobility usage, we developed robust AI algorithms to detect drunk driving. Based upon our own developed Virtual Reality simulations, involving 30 participants, we utilized hand-tracking technology to enhance realism and reduce nausea. Results indicated that LSTM (Long Short-Term Memory network) model successfully identified 86% of drunk riders. A Transformer method was tested with further aggregated data where we have achieved 100% precise identification of drunk drivers. LSTM methods that we tested in the project have shown significant improvement for detecting drunk drivers, compared with machine learning methods e.g. Random Forest and Recurrent Neural Networks (RNNs). This research contributes to Vision Zero, zero fatalities and severe injuries from road traffic in the Nordics by 2050, by providing robust sensing algorithm for identifying e-scooter misuse, with future work focusing on refining models, expanding data collection, and integrating advanced neural networks. Our findings offer valuable insights for stakeholders like shared e-scooter operators and urban transport administrations to enhance urban mobility safety.

<strong class="journal-contentHeaderColor">Abstract.</strong> Sedimentary recycling of phosphorus is a key aspect of coastal eutrophication. Here, we present data on benthic fluxes of dissolved inorganic phosphorus (DIP) from the Baltic Sea, an area with a long eutrophication history. The presented dataset contains 499 individual fluxes measured in situ with three types of benthic chamber landers at 59 stations over 20 years, and data cover most of the Baltic Sea sub-basins (Hyl&eacute;n et al., 2025; <a href="https://doi.org/10.5281/zenodo.14812160" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.14812160</a>). The dataset further contains information about bottom-water dissolved oxygen (O₂) concentrations, sedimentary organic carbon (OC) content and sediment type. The DIP fluxes differ considerably between basins depending on OC loading and the level of O₂ depletion and generally increase from the coast to the central basins. Several stations have been visited on multiple occasions, also at times with different O₂ concentrations, which enables investigation of the immediate effects of shifting bottom-water O₂ concentrations on the benthic DIP release. The Baltic Sea-wide benthic DIP release is estimated to be 391 &ndash; 489 kton y^-1 based on a data integration based on sediment type and O₂ conditions during three years with varying extents of hypoxia and anoxia (2004, 2013 and 2018). The dataset reveals a lack of flux measurements in winter months, coastal areas and sandy sediments; these should be targeted in future studies. Overall, the data is of high quality and will be important for marine management and studies on mechanisms in benthic phosphorus cycling.

Abstract Prestressed concrete provides several advantages over traditional reinforced concrete; however, some markets remain skeptical about the use of post‐tensioned structures. A crucial factor in these structures is assessing and quantifying the final force introduced into the element. This study evaluates the application of distributed optical fiber sensors (DOFS) to monitor the response of beams during tendon force introduction, long‐term behavior, and loading to failure. An experimental campaign was conducted involving four beams: two standard and two post‐tensioned. Additionally, the study compares the effectiveness of steel fiber reinforced concrete to determine its potential for further optimizing beam design. Key aspects analyzed include tendon force and corresponding instantaneous and deferred losses, load‐deformation behavior, initial crack formation, and subsequent crack development. The results demonstrated that using DOFS in a straightforward manner allows for detailed beam response analysis across different phases. Simple hypotheses and limited sensors can accurately evaluate all tendon losses. Furthermore, fiber optics can detect potential crack candidates even in the compression stage, due to strain concentrations that lead to cracking during the loading phase.

Objectives Dockless electric scooters (e-scooters) have emerged as a popular mode of short-distance transportation in urban environments, offering convenience and flexibility in rental and usage. However, users often engage in unsafe behaviors while riding, posing risks to themselves and others. In this study, we aim to identify unsafe riding behaviors through analysis of riding trajectories, to reduce safety incidents and promote safer e-scooter usage. Methods This study explores the classification of single and tandem e-scooter riding behaviors using a data-driven approach. Leveraging trajectory data from Gothenburg, Sweden, collected over 11 days in November 2023; we utilize Long Short-Term Memory (LSTM) neural networks to analyze dynamic temporal features. Results The LSTM model demonstrated significant performance advantages over both RNN and Random Forest models, achieving an accuracy of 92.65%, precision of 91.69%, recall of 93.85%, F1 score of 95.56%, and an AUC of 0.9169. Conclusions Additionally, optimizing the input sequence length to 240 s of continuous trajectory features balanced computational efficiency with prediction accuracy and stability. Dynamic trajectory features such as acceleration, turning angle, speed, and start SOC play pivotal roles in differentiating riding patterns. The proposed method can assist city authorities and e-scooter operators in real-time risk detection, operational monitoring, and targeted safety interventions, contributing to safer shared micromobility systems.

<strong class="journal-contentHeaderColor">Abstract.</strong> The chemical signature of surface waters is influenced by the interactions with soil particles and old groundwater. In permafrost landscapes ground ice restricts the flow of water in soils, and this implies a limited influence of, e.g., weathering on the chemical signature of the runoff. The aim of this study was to test to what extent freeze-thaw processes, hydrology and water-age play for shaping the chemical and isotopic signature of surface water and shallow groundwater in a catchment in West Greenland. Measuring runoff in remote catchments is challenging, and we therefore use a validated hydrological model to estimate the daily runoff over multiple years. We have also used a particle tracking simulation to determine the age of groundwater, and isotopic and chemical data from various water types (surface water, groundwater, lake water and precipitation) collected during different hydrological situations. Together this shows that even though the age of the groundwater rarely exceeds 4 years, runoff is dominated by subsurface flow, and overland flow is restricted to the early snowmelt period and heavy rain events. Our monitoring of the active layer indicates a rapid thaw, especially in connection with running water, and melting of ground ice quickly becomes an important fraction of the runoff. Taken together our data indicate that, similar to in other climatic settings and despite the lack of truly old groundwater and a shallow active layer, there is a profound influence from soil processes on the chemical and isotopic signature of the runoff.

Mycoplasma bovis is an important pathogen causing pneumonia, mastitis, and arthritis in cattle all over the world entailing reduced animal welfare and economic losses. In this longitudinal study, we investigated the presence of M. bovis antibodies in bulk tank milk (BTM) and in milk from primiparous (PP) cows at 4 sampling occasions over 2 yr. Herd characteristics associated with a positive antibody test result in PP cows were investigated. The participating dairy herds (n = 149) were situated in southern Sweden, samples were collected and analyzed with ID Screen antibody ELISA. Information on herd characteristics was retrieved from the national DHI database. To identify herd characteristics associated with the presence of antibodies in PP cows, mixed linear regression with herd and sample as random factors were used. The apparent herd-level prevalence of M. bovis infection based on antibodies in BTM was 17%, but with the addition of PP cows, the prevalence increased to 28%. The results showed that larger herds and introduction of cattle was associated with higher antibody levels in PP cows. In conclusion, this study showed a clear difference in the apparent prevalence of M. bovis infection based on antibodies in BTM or in PP cows: The number of positive herds was almost doubled when including PP cows. This motivates repeated sampling of a few PP cows to find newly infected herds in an early stage. Finally, the results showed that introduction of cattle influences the level of M. bovis antibodies. This is important in the control and prevention of further spread of the infection. It is essential for free herds to know their M. bovis status, and antibody testing is highly recommended if introducing cattle.