Luleå University of Technology

We derive new upper bounds on outage probability (OP) and spectral efficiency (SE) for a simultaneous wireless information and energy transfer system under spatial correlation and optimal phase configuration at intelligent reflecting surface (IRS) when users are served based on round-robin (RR) scheduling, share common source to IRS links and adopt nonlinear energy harvesting. Diversity order for this system is characterized. We then extend our study to a multi-antenna source and analyze OP and SE under random and equal phase shift configurations at IRS. We design beamformers at the source and at IRS under different strategies, namely RR scheduling and simultaneous service with and without signal-to-interference-plus-noise ratio (SINR) constraint. Numerical results are presented to validate the accuracy of our statistical modeling and mathematical analysis and quantify the gain in performance relative to random and equal phase shifts. We illustrate that higher number of users can be served by increasing number of IRS elements while keeping OP fixed. We identify the operational regime where RR scheduling yields better performance than serving users simultaneously without SINR constraint. We show that increasing IRS elements can help maintain target harvested power even under stricter SINR constraint. Impact of estimation error on performance is illustrated.

Air compressors are critical components in many industries whose catastrophic failure results in huge financial losses and downtime leading to accidents. Hence, real time fault diagnosis of air compressor is essential to predict the health condition of air compressor and plan scheduled maintenance thereby reducing financial losses and accidents. Fault diagnosis using transfer learning aids in real time fault detection. In the present study, five air compressor conditions were considered namely, check valve fault, inlet and outlet reed valve fluttering fault, inlet reed valve fluttering fault, outlet reed valve fluttering fault, and good condition. The raw vibration data was converted to radar plot images that were pre-processed and classified using four pre-trained networks (ResNet-50, GoogLeNet, AlexNet, and VGG-16). The hyperparameters like epochs, batch size, optimizer, train-test split ratio, and learning rate were varied to find out the best network for air compressor fault diagnosis. ResNet-50 among all other pre-trained networks produced the maximum classification accuracy (average of five trials) of 98.72%.

This article introduces a novel method for converting 3D voxel maps, commonly utilized by robots for localization and navigation, into 2D occupancy maps for both unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs). The generated 2D maps can be used for more efficient global navigation for both UAVs and UGVs, in enabling algorithms developed for 2D maps to be useful in 3D applications, and allowing for faster transfer of maps between multiple agents in bandwidth-limited scenarios. The proposed method uses the free space representation in the voxel mapping solution to generate 2D occupancy maps. During the 3D to 2D map conversion, the method conducts safety checks and eliminates free spaces in the map with dimensions (in the height axis) lower than the robot's safety margins. This ensures that an aerial or ground robot can navigate safely, relying primarily on the 2D map generated by the method. Additionally, the method extracts the height of navigable free space and a local estimate of the slope of the floor from the 3D voxel map. The height data is utilized in converting paths generated using the 2D map into paths in 3D space for both UAVs and UGVs. The slope data identifies areas too steep for a ground robot to traverse, marking them as occupied, thus enabling a more accurate representation of the terrain for ground robots. The proposed method is compared to the existing state-of-the-art fixed projection method in two different environments, over static maps and with progressively expanding maps. The methods proposed in this article have been implemented in the widely-used robotics frameworks ROS and ROS2, and are open-sourced. The code is available at: https://github.com/LTU-RAI/Map-Conversion-3D-Voxel-Map-to-2D-Occupancy-Map .

A number of bis(glycolato)borate (BGB) anion‐based salts, comprising Li⁺, Na⁺, K+, Mg²⁺ and Ca²⁺ cations, has been synthesized and characterized. Fluorine‐free electrolytes based on LiBGB and organic solvents, such as dimethyl sulfoxide (DMSO), triethyl phosphate (TEP), and trimethyl phosphate (TMP) have been created and their transport properties, thermal and electrochemical stabilities, and lithium compatibility are examined. The ionic conductivities of the 1 M LiBGB‐TEP and 1 M LiBGB‐TMP electrolytes are ca. 2–3 times lower than for the 1 M LiBGB‐DMSO electrolytes (2.05, 2.65 vs. 5.70 mS cm⁻¹ at 25 °C), and as compared to the state‐of‐the‐art 1 M lithium hexafluorophosphate (LiPF6) in EC:DEC (EC:DEC=1 : 1 in vol., LP40) they display lower ionic conductivities, but the formers’ redox stability on aluminum (Al) and glassy carbon electrodes are much better. Concentrated (>1 M) LiBGB‐DMSO electrolytes display enhanced redox stability, but worse Al passivation. Among the electrolytes, 1 M LiBGB‐TMP achieves the best long‐term stability over 300 h at 0.1 mA/cm² for Li plating‐stripping while the Li compatibility needs to be further improved. Overall, this study introduces a family of versatile fluorine‐free orthoborate salts and electrolytes for mono‐ and divalent batteries, and a fundamental understanding of their transport and electrochemical properties, aiming towards battery applications.

The tire pressure monitoring system (TPMS) is crucial for road safety, fuel efficiency, and vehicle performance. This study focuses on nitrogen‐filled pneumatic tires due to their uniform pressure management and thermal stability advantages over air‐filled tires. Using machine learning, the research analyzes TPMS data to enhance understanding of tire behavior and vehicle safety. It employs various feature extraction methods and lazy‐based classifiers to analyze vibration signals collected under idle, high‐speed, normal, and puncture conditions using MEMS accelerometers. The study examines autoregressive moving average (ARMA), histogram, and statistical features individually and in combinations (statistical‐histogram, histogram‐ARMA, statistical‐ARMA, and statistical‐histogram‐ARMA) to improve predictive accuracy. By integrating these features, the study aims to optimize predictive modeling of TPMS. Empirically, the research achieved 97.92% accuracy using the local weighted learning (LWL) algorithm, demonstrating the effectiveness of combined statistical, histogram, and ARMA features in enhancing TPMS predictive capabilities.

The rise in global temperature and accumulation of petroleum-based wastes in the environment forces the scientific focus towards renewable alternatives. In the present work, an under-exploited resource – spruce bark – is investigated as a raw material for production of bio-oil as a liquid energy carrier. To enhance the energy-content of the produced bio-crude, ultimately being produced through hydrothermal liquefaction, the polysaccharides were extracted through organosolv fractionation and converted to lipids by oleaginous microorganisms. The effect originating from tannins was also investigated by performing a pre-extraction before the organosolv fractionation. It was found that performing the organosolv fractionation and upgrading the isolated organosolv lignin to bio-oil greatly reduced the oxygen content of the oil fraction thereby improving its energy content, and introducing upgraded polysaccharides in the form of lipids, as well as pre-extracted tannins, caused clear changes in the product distribution of the final bio-oil and kept a final product with low oxygen content. The other factor largely influencing the product distribution originated from the various heating rates tested by altering operational mode of the HTL process between batch and semi-continuous. Ultimately, performing the organosolv fractionation and individual upgrading of the polysaccharides had a beneficial effect on reducing the final solids content and enhancing the liquid oil yield.

We report the synthesis of two pyridinium‐based room temperature protic ionic liquids (PILs), pyridinium bisulfate, [HPyr][HSO4] and pyridinium sulphate, [HPyr]2[SO4] and investigation of the kinetics of their water sorption behaviour and its influence on their density, ionic conductivity, and potential windows. The PILs were synthesized by the reaction of pyridine base with an acid, H2SO4, under solventless conditions, and confirmed by FTIR spectroscopy and 1H NMR spectra. The appearance vibration bands in the 3095–3252 cm⁻¹ range for −NH⁺ stretching in the FTIR spectra and a peak at a chemical shift of 8.439 ppm in the 1H‐NMR of the liquids confirm their synthesis as no such bands/peaks can be seen in that of the pure pyridine spectra. The PILs’ hygroscopic nature was examined by exposing them (5 mL each sample with exposed surface area 3.143 cm²) to air for varied time intervals at a relative humidity, RH=58±5 % and T=20±5 °C. Coulometric Karl‐Fischer (KF) titration was used to determine how much moisture each PIL sample absorbed at each time interval. The findings reveal that when the PIL was exposed to air for longer periods of time, more moisture was absorbed, and the results correspond well with the pseudo first‐order kinetic model. The densities and conductivities of several samples of the two PILs were examined, and it was discovered that as the percentage water content of the PILs grew, density decreased but conductivities increased. Furthermore, it was discovered that when temperature rose, the conductivity of each of the PILs increased, and the results fit well to the Arrhenius linear equation since the regression coefficient, R², for each of the samples approached the perfect fit value of one. The electrochemical window (EW) data, the mechanism of moisture oxidation within the EWs of each PIL at Pt and Au electrodes, and the electrocatalytic role played by the Pt and Au surface oxides during ethanol oxidation are evaluated and discussed in light of their future sustainable energy applications.

Background Individuals reporting self-injury are at greater risk of several adverse outcomes, including suicide. There is reason to be concerned how these individuals cope when stressful life events increase. This study aimed to investigate the trajectories of anxiety and depressive symptoms and the predictive value of self-injury history in individuals with psychiatric symptoms during the unique and stressful conditions of the COVID-19 pandemic. Methods In a longitudinal population cohort study (N = 1810) ranging from 2020 to 2022, anxiety (measured by Generalized Anxiety Disorder, GAD-7) and depressive symptoms (measured by Patient Health Questionnaire, PHQ-9) were self-reported monthly during 12 months. Latent growth curve models with and without self-reported self-injury history as predictors were conducted. Results Overall, anxiety and depressive symptoms decreased from baseline, but remained at moderate severity at follow-up. Individuals reporting suicidal or nonsuicidal self-injury reported significantly higher symptom severity at baseline. In addition, individuals reporting suicidal self-injury demonstrated a slower rate of decline in the symptom load over the course of 12 months. Conclusions Over the course of 12 months, anxiety and depressive symptoms decreased in individuals with psychiatric symptoms, but still indicate a psychiatric burden. Individuals with a history of self-injury could be more vulnerable in face of stressful conditions such as those experienced during the COVID-19 pandemic.

Adopting digital technologies in different organizations has become a trend over the last decade, yet our understanding regarding impact of digital technologies on strategising needs to be more cohersive. This paper reviews existing research on how digital transformation intersects with strategic management to adress this gap. Specifically, the aim is to explore how the digital context changes strategising. Based on a systematic review of empirical evidence from 163 journal papers, we showcased the manifestation of strategising in the digital age in terms of strategic practitioners, practices and praxis. By consolidating these findings, a typology of strategic actions in the digital age is developed and discussed, highlighting the interplay among changes in strategy‐as‐practice parameters. This framework clarifies in strategic scenarios of digital transformation and identifies various strategic directions and actions. Overall, we argue that although digital transformation has created additional strategic options, it has yet to change the underlying assumptions of strategising in firms.

The IEEE Reliability Society has a technical committee (TC) that deals with the special challenges in reliability modeling, which arise in connection with systems of systems (SoSs).

The Paleoproterozoic Stollberg Zn-Pb-Ag plus magnetite ore field contains SVALS-type stratabound, limestone-skarn hosted sulphide deposits within volcanic (bimodal felsic and mafic rocks)/volcaniclastic rocks metamorphosed to the amphibolite facies. The sulphide ores consist of semi-massive to disseminated to vein-network sphalerite-galena and pyrrhotite (with subordinate pyrite, chalcopyrite, arsenopyrite and magnetite). Thermochemical considerations and stabilities of minerals in the systems K-Al-Si-O-H and Fe-S-O and sulphur isotope values for sulphides of δ³⁴SVCDT = +1.12 to +5.71 ‰ suggest that sulphur most likely formed by inorganic reduction of seawater sulphate that was carried in hydrothermally modified seawater fluid under the following approximate physicochemical conditions: T = 250o–350 oC, δ³⁴SΣS = +3 ‰, I = ∼1 m NaCl and a total dissolved S content of ∼0.01 to 0.1 moles/kg H2O. However, a magmatic contribution of sulphur cannot be discounted. Carbon and oxygen isotope compositions of calcite in altered rocks spatially associated with mineralisation show values of δ¹³CVPDB = −2.3 to −0.8 ‰ and δ¹⁸OVSMOW = +9.5 to +11.2 ‰, with one anomalous sample exhibiting values of δ¹³CVPDB = −0.1 ‰ and δ¹⁸OVSMOW = +10.9 ‰. Most carbonates in ore show lighter C and O isotope values than those of Proterozoic (Orosirian) limestones and are likely the result of premetamorphic hydrothermal alteration involving modified seawater followed by decarbonation during regional metamorphism. The isotopically light C and O isotope values are consistent with those for carbonates spatially associated with other SVALS-type deposits in the Bergslagen ore district and suggest that such values may be used for exploration purposes.

Introduction: Using the COVID-19 pandemic as an example of a national and international crisis, it has been possible to show how critical care nurses (CCNs) were affected by their work situation with impact on health and wellbeing. This study sought out to investigate how CCNs stress was affected and to provide some answers as to how to react and organize care in a future crisis. The specific focus was CCNs’ stressors related supervision of nurses untrained in intensive care and how these were handled in a salutogenic perspective. Aim: The aim of this study was to analyze CCNs’ experiences of supervision of nurses without training in intensive care during the COVID-19 pandemic, and to analyze these experiences with the help of the salutogenic concept sense of coherence. Materials and Methods: The phenomena under study were explored during the years of 2021–2022 through in-depth interviews and interpreted using deductive content analysis. Results: By analyzing CCNs experiences of supervising nurses without training in intensive care with the lens of sense of coherence, it was possible to show in what way these concepts influenced how to cope with the demanding situation. Sense of coherence was influenced by the inevitable prioritization of patient care and nursing interventions. This prioritization caused moral distress, but was also enhanced or decreased by CCNs sense of coherence. Conclusion: When recruiting and introducing new personnel in a future crisis to any field of healthcare, but particularly to the intensive care, we would, on the basis of these findings, suggest that well-established plans are vital for how to move personnel throughout the organization, and for how to introduce the field of intensive care. Plans for how to model care with the help of RNs without specialist training should be put in place. A communication plan for the organization is also of importance to enhance transparency.

Wood is an important construction material, but a significant problem hindering its widespread use is susceptibility to biodeterioration and biodegradation. To protect wood against degradation, a surface coating can be used, and it is important to be able to predict the ability of the coating to prevent fungal growth. The currently available standard method to determine the antifungal efficiency of a coating has two weaknesses, viz. no evaluation of the moisture content in the wood material, and no possibility to study antifungal effect of the coating towards an individual fungus. A new quantitative method of determining the antifungal efficiency of coatings is therefore proposed, where a coating is applied to wood and exposed to an individual fungus in a Petri dish. Six commercial water-based coatings containing synthetic biocides were studied on filter paper (EN 15457) and with the new test method on wood blocks. The results show the importance of studying the antifungal efficiency of a coating using individual fungi instead of a mixture of fungi, since individual fungi interact differently with a given biocide in the coating. The moisture content of the wood substrate during the test was affected by how the fungus was established on the coating. This new test approach shows promise in screening the antifungal efficiency of wood coatings containing preservative substances applied to wood material surfaces.

Clutch systems are crucial components of automotive systems, essential for transferring engine power to the wheels through gear shifts. A failed clutch can halt gear shifts and power transmission, rendering a vehicle immobile. Effective fault diagnosis is vital for ensuring reliability, preventing breakdowns, and addressing root causes promptly. Consequently, condition monitoring of the clutch is essential for maintaining system reliability and minimizing unwanted breakdowns. This paper presents an innovative condition-monitoring technique derived from vibration analysis to detect faults in the clutch system. The study involves extracting statistical, histogram, and autoregressive moving average features from acquired vibration signals. The J48 decision tree algorithm is utilized to select the most significant features, which are then classified using tree-based classifiers across three load conditions (no load, 5 kg, and 10 kg) and six clutch conditions. The experimental results demonstrate that the feature fusion strategy significantly enhances classification accuracy. The obtained results state that the classification accuracies for no load, 5 kg load, and 10 kg load were 98.33%, 100.00%, and 99.16%, respectively, while applying feature fusion strategies. This study highlights the effectiveness of feature fusion in improving fault diagnosis accuracy for clutch systems, presenting a robust method for real-time condition monitoring in automotive applications.

X-ray computed tomography (CT) is utilised in some sawmills today, primarily for enhancing value yield and for process automation, which includes log sorting and sawing optimisation. Nevertheless, there is a scarcity of recent research utilising CT to assess the local cutting process. As a preliminary study, this paper addresses this gap by using CT to investigate the connections between local cutting force and local wood properties including density, knots, and annual ring width. Workpieces of Scots pine (Pinus sylvestris L.), from Sweden and Poland, were CT-scanned in laboratory conditions. Quasi-linear cutting tests were then performed on both clear and knotty regions of the workpieces using a custom-made laboratory stand with a Stellite-tipped tooth mounted on piezoelectric sensors. It was found that density influences cutting forces for both clear and knotty wood, and this effect increased noticeably with increasing uncut chip thickness. Changes in wood density, such as between sapwood and heartwood or between clear wood and knot, caused dynamic changes in cutting forces and temporary disturbances to the stability of the system. Normalisation of cutting forces by local density allowed the conclusion that density is not the only property affecting cutting forces. Other structural properties, e.g. annual ring width and latewood–earlywood proportion may affect the cutting process as well, which requires deeper analysis in the future research. This preliminary study demonstrates the feasibility and usefulness of coupling CT data with cutting force measurements and suggests further research on the relationship between cutting force and wood properties.