Forecasting Future Procurement Potential of Swedish Forest Biomass Using Forest Inventory Data

In the last 20 years the use of forest biomass for energy production and sawlog and pulpwood production has increased by 68%, 11% and 31% in Sweden. As Sweden is trying to achieve net zero greenhouse gas emissions by 2045, the high demand for biomass can also be expected in future. Therefore, a method to project the amount of spatially available biomass assortments for industries was developed. Available amounts of different forest assortments were estimated and visualised in a web-based tool using forest inventory data and nationwide projection analyses of available biomass for 2035–2039. In this interval, the greatest amount of available biomass and roundwood will be in Northern Sweden. Results also indicate that already existing harvesting intensity is very high compared to the available biomass in the future. The industry can expect noticeably more available biomass in the coming 100 year period. With increased competition between large pulp mills and biorefineries, the supply areas can exceed 200 km to satisfy raw material demand. The long distance and high volume supply chain requirements will demand further improvement in transportation solution nationally and cross-border in the Baltic Sea Region

Audio Event Detection using Weakly Labeled Data

Acoustic event detection is essential for content analysis and description of multimedia recordings. The majority of current literature on the topic learns the detectors through fully-supervised techniques employing strongly labeled data. However, the labels available for majority of multimedia data are generally weak and do not provide sufficient detail for such methods to be employed. In this paper we propose a framework for learning acoustic event detectors using only weakly labeled data. We first show that audio event detection using weak labels can be formulated as an Multiple Instance Learning problem. We then suggest two frameworks for solving multiple-instance learning, one based on support vector machines, and the other on neural networks. The proposed methods can help in removing the time consuming and expensive process of manually annotating data to facilitate fully supervised learning. Moreover, it can not only detect events in a recording but can also provide temporal locations of events in the recording. This helps in obtaining a complete description of the recording and is notable since temporal information was never known in the first place in weakly labeled data.Comment: ACM Multimedia 201

Predicting delay factors when chipping wood at forest roadside landings

Chipping of bulky biomass assortments at roadside landings is a common and costly step in the biomass-to-energy supply chain. This operation normally involves one chipping unit and one or several transport trucks working together for simultaneous chipping and chip transport to a terminal or end user. Reducing the delay factors in these operations is a relevant ambition for lowering supply costs. A method to estimate organizational delay based on: (1) the capacity ratio between the transport and the chipper, (2) the use of buffer storage, and (3) the number of transport units involved is suggested here. Other delays will also be present, and some of these may relate to the working conditions at the landing. A method to set a landing functionality index based on characteristics of the forest landing is also suggested. A total of 14 roadside chipping operations were assessed and the operators were interviewed to address the impact of machinery configuration and landing characteristics on machine utilization. At most sites, the chipper was the more productive part, and the chipper utilization was to a large extent limited by organizational delay. Still the utilization of the transport units varied between 37 and 97%, of which some 36% of the variation was explained by the landing functionality index. Knowledge from the work presented here should be a good starting point for improving biomass supply planning and supply chain configuration.acceptedVersio

Observation of Coherently Coupled Cation Spin Dynamics in an Insulating Ferrimagnetic Oxide

Many technologically useful magnetic oxides are ferrimagnetic insulators, which consist of chemically distinct cations. Here, we examine the spin dynamics of different magnetic cations in ferrimagnetic NiZnAl-ferrite (Ni$_{0.65}$Zn$_{0.35}$Al$_{0.8}$Fe$_{1.2}$O$_4$) under continuous microwave excitation. Specifically, we employ time-resolved x-ray ferromagnetic resonance to separately probe Fe$^{2+/3+}$ and Ni$^{2+}$ cations on different sublattice sites. Our results show that the precessing cation moments retain a rigid, collinear configuration to within $\approx$2$^\circ$. Moreover, the effective spin relaxation is identical to within $<$10% for all magnetic cations in the ferrite. We thus validate the oft-assumed ``ferromagnetic-like'' dynamics in resonantly driven ferrimagnetic oxides, where the magnetic moments from different cations precess as a coherent, collective magnetization

Das dritte und vierte Relief von Gundük

peer reviewedThe Gundük rock relief ensemble in a cave located in the northern highlands of Iraq is probably the oldest known example of its kind in the Near East. First reported in the 19th century but never accurately documented, unfortunately two of the three known reliefs were intentionally damaged beyond repair in the decades to follow. This article presents a new art-historical analysis of the preserved third relief as well as a fourth previously unknown carving, based on recent photogrammetric capture. The images can be dated to the Early Dynastic III or Early Akkadian period with motifs, stylistic details and a composition obviously deriving from then-contemporaneous art in southern Mesopotamia

Parthian Rock-Reliefs from Amadiya in Iraqi-Kurdistan

editorial reviewedThe ancient fortress of Amadiya is situated atop a mesa at the foot of the Zagros Mountains in Iraqi-Kurdistan. In front of the Mosul Gate there are two rock-reliefs depicting larger than life figures in traditional Parthian dress. This article presents detailed illustrations of these sculptures, using digital photogrammetry to enhance eroded features

Hexamorphism of Dantrolene: Insight into the Crystal Structures, Stability, and Phase Transformations

Dantrolene represents yet another interesting example of abundant molecular crystal polymorphism existing in at least six different neat polymorphs, three of which can be obtained via crystallization (I-III) and an additional three (IV- VI) via solid-state dehydration from three different monohydrates (MH-I-MH-III). The reasons for polymorph formation were rationalized by analyzing the crystal structures of the polymorphs and hydrates used in their preparation. The thermodynamic relations among the polymorphs were established from calorimetric data, solubility measurements, and lattice energy calculations

Macrospin model of an assembly of magnetically coupled core-shell nanoparticles

Highly sophisticated synthesis methods and experimental techniques allow for precise measurements of mag-netic properties of nanoparticles that can be reliably reproduced using theoretical models. Here, we investigate the magnetic properties of ferrite nanoparticles by using theoretical techniques based on Monte Carlo methods. We introduce three stages of sophistication in the macromagnetic model. First, by using tailor-made Hamil-tonians we study single nanoparticles. In a second stage, the internal structure of the nanoparticle is taken into consideration by defining an internal (core) and external (shell) region, respectively. In the last stage, an assembly of core-shell nanoparticles is considered. All internal magnetic couplings such as interatomic and intra-atomic exchange interactions or magnetocrystalline anisotropies have been estimated. Moreover, the hysteresis loops of the aforementioned three cases have been calculated and compared with recent experimental measurements. In the case of the assembly of nanoparticles, the hysteresis loops together with the zero-field-cooling and field-cooling curves are shown to be in a very good agreement with the experimental data. The current model provides an important tool to understand the internal structure of the nanoparticles together with the complex internal spin interactions of the core-shell ferrite nanoparticles