The improper aggregation of commodities can have important consequences when estimating a system of group demand equations. Generally, aggregates are created under the assumptions that intra-group preferences are homothetic and the consumer's utility function is weakly separable over some partition. These assumptions place severe restrictions on the model that can significantly impact parameter and elasticity estimates. An alternative to imposing weak separability is to employ the Generalized Composite Commodity Theorem, which requires the relative intra-group commodity prices to be independent of the group price index. This study compares the results of estimating a demand system for composite beef, pork, and poultry products under the assumptions of weak separability and the Generalized Composite Commodity Theorem. Another important issue related to aggregation is the specification of an appropriate group price index. Price indices consistent with linear homogeneous preferences (a subset of the homothetic class of preferences) and non-homothetic intra-group preferences are identified and it is shown that several of the commonly employed indices are biased in the absence of complete price data. / Master of Science

Nothing is perfect, and this includes the ability to maintain homeostasis within the cell with age. Factors such as aging, chemicals, and gene dysfunction disrupt cellular homeostasis, leading to increased stress and compromising the ability of animals to maintain a healthy lifespan. Dysregulated homeostasis can be detrimental on an organismal level, impacting locomotion, and on a cellular level causing proteins to misfold and become aggregates, which are toxic to cells. Toxic protein aggregation and loss of locomotory function are key hallmarks of several age-related diseases. My Ph.D. work examined the collapse of homeostasis on electrotaxis, the age-associated increase in proteotoxicity, the decline in longevity, and neuronal and muscle health. On a behavioural level I demonstrated that loss of various components of the MT-UPR, ER-UPR, and HSR modulated the speed of animals. Additionally, I found that activation of stress responses due to chemicals and exercise reduced and increased the speed of animals respectively. On a cellular level I elucidated potential mechanisms by which Mesencephalic Astrocyte Derived Neurotrophic Factor (MANF) affects the stress response to maintain homeostasis and prevent protein aggregation. I observed the novel localization and role of MANF in lysosomes to potentially act as a critical regulator of the stress response to maintain proteostasis, neuronal health and longevity, thereby bringing balance to the cell. Furthermore, the broad tissue expression of MANF revealed its localization to muscles. This supports the ability of MANF to act as more than a neurotrophic factor as it was found to be required for muscular health in animals in an age-dependent manner. Overall, my Ph.D. research has provided new insights into the stress response and behaviour and the precise role of MANF in mediating stress response signaling to promote organismal and cellular fitness. / Dissertation / Doctor of Science (PhD) / Cellular perturbations or stress disrupt homeostasis, activating multiple stress responses. Activation of the stress response can determine the fate of an organism and is crucial to its health. Although the stress response pathways are generally understood, little is known about how the stress responses preserve animal behaviour or how they are regulated to promote organismal survival. My work has provided a basis for how stress responses affect behaviour positively and negatively in animals. I found that the stress response required mesencephalic astrocyte derived neurotrophic factor (MANF) to promote organismal survival. My thesis determined that MANF acts as more than a neurotrophic factor. MANF was found to not only be essential in neuronal health but also longevity and muscle health. Overall, this thesis demonstrated the impact of stress response on behaviour and the potential mechanism by which MANF is cytoprotective in whole organisms.

Carrier aggregation is a technology in wireless communications which allows a user to use multiple cells simultaneously for communication. In order to select cells, it is crucial to estimate their potential throughput for a given user. As a part of this estimate, we investigate how many MIMO layers a given channel can expect to use in the future, and whether machine learning can be used to predict the number of layers. Simulated user traces are used to generate training data, and special attention is directed at the construction of features based on user history. Random forests and multi-layer perceptrons are trained on the generated data, and we show that the random forests achieve better performance than baseline models, while the MLP models fail to learn and do not reach the expected performance. The importance of the used features is analysed, and we find that the history-based features are especially useful for predicting future channel ranks and thus are promising for use in a cell set selection system for carrier aggregation.

2025 / Mid-infrared photothermal (MIP) microscopy can detect mid-infrared absorption from intrinsic chemical bond vibrations with optical resolution. Proteins have one of the strongest mid-infrared absorption in the amide I region originating from their backbone peptide bonds. My thesis work focuses on developing and applying MIP towards the study of protein synthesis and assemblies in their natural environment. The metabolic activity of proteins can be measured by MIP imaging of the red-shifted amide I peak due to isotopic labeling. We quantified protein synthesis by wide-field MIP imaging of the original and shifted amide I peak of E. coli cells cultured with 13C-glucose. By probing protein synthesis of hundreds of bacteria at the single-cell resolution within seconds, the susceptibility of antibiotics was determined after 1 hour of treatment, which showed great promise for rapid antimicrobial susceptibility testing. Further integrated with fluorescence imaging, we presented a mid-infrared photothermal — fluorescence in situ hybridization platform (MIP-FISH) platform that enabled simultaneous genetic identification and metabolic analysis of microbes. We demonstrated the identification of metabolic active single bacterial cells within a complex human gut microbiome sample. The amide I region is also sensitive to the secondary structure of proteins. Protein aggregates in the form of amyloid fibrils, associated with many neurodegenerative diseases, share the structural characteristic of β-sheet enrichment. We demonstrated the mapping of secondary structure of protein aggregates in live cells modeling Huntington’s disease. By comparing MIP spectra of label-free and green fluorescent protein (GFP)-tagged huntingtin inclusions, we observed the perturbation of GFP fusions to the secondary structure of aggregates. Additionally, we revealed that huntingtin inclusions partition into a β-sheet-rich core and ɑ-helix-rich shell and this structural partition exists only in cells with the [RNQ+] prion state. / 2027-01-28T00:00:00Z

La propreté inclusionnaire reste un enjeu majeur en élaboration des métaux par voie liquide. La flottation, principal procédé retenu en métallurgie secondaire pour éliminer les particules d’inclusions, consiste à injecter des bulles de gaz au sein du réacteur. Lors de leur ascension, les bulles vont capter les plus grosses inclusions et favoriser la collision et l’agrégation des particules. Dans le but de quantifier les phénomènes influents à l’échelle des inclusions sur la dynamique d’agrégation entre deux inclusions à proximité des bulles, un modèle numérique 3D a été développé. L’écoulement local est modélisé par un cisaillement plan permanent et résolu par une méthode de Boltzmann sur réseau. Le couplage entre les particules et le fluide a été assuré par une méthode de frontière immergée permettant de calculer la perturbation hydrodynamique engendrée par la présence des particules et de mettre à jour les interactions entre particules pour leur suivi lagrangien. Les simulations numériques réalisées ont mis en évidence que les effets hydrodynamiques ont une influence non négligeable sur le comportement des inclusions. Des sections efficaces de collision ont pu être extraites, à partir desquelles ont été calculés des noyaux d’agrégation, données macroscopiques rendant compte des effets à petite échelle. Une première application de ce travail a été menée avec le calcul des fréquences d’agrégation d’un train de bulle dans un réacteur canal à partir de résultats de simulations DNS. Les noyaux d’agrégation ont également été exploités en vue de déterminer, à partir de résultats RANS de l’hydrodynamique d’une poche d’acier, l’évolution de la concentration d’inclusions par un bilan de population global. / Inclusion cleanliness remains a major challenge faced in process metallurgy in liquid phase. Flotation, the main process used in secondary metallurgy to remove inclusions, consists in injecting gas bubbles into the reactor. Rising gas bubbles entrap the biggest inclusions at their surface or in their wake. Besides, they promote collision and aggregation among particles. A 3D numerical model has been developed in order to quantify the roles of the prevailing phenomena on aggregation dynamics between inclusions in the vicinity of bubbles. At inclusion (mesoscopic) scale, the turbulent flow is locally modeled by a steady plane shear flow which is solved using a lattice-Boltzmann method. The coupling between both liquid and solid phases is ensured using an immersed boundary method. This method resolves the hydrodynamic perturbation induced by particles, and hence their interactions that are, in turn, used to update their Lagrangian tracking. The conducted numerical simulations bring out the influence of hydrodynamic effects on inclusion behavior. Collision cross sections have been determined from which ensuing aggregation kernels have been calculated. Such cross sections could provide macroscopic models to represent local particle dynamics. A first application of these results is presented to calculate aggregation frequencies in bubble swarms in a channel flow reactor that was simulated using DNS. Additionally, evolution of inclusion populations in molten steel has been determined from RANS simulation of a liquid steel ladle by means of a global population balance implementing the aggregation kernels determined in the present work.

This thesis deals with meetings between peoples during prehistoric times in the northern part of Norrland, Sweden. Particular attention is paid to the possible occurrence of more temporary meetings between people in larger groups at aggregation camps during the period ca 7000 – 0 BC. The study has had the aim of increasing our understanding of how peoples’ meetings and contact networks may have been framed. Thirteen sites that previous research has interpreted to be aggregation camps within our field of study have been analysed and interpreted. These are: Jokkmokk, Purkijaur, Nelkerim, Porsi, Lundfors, Norrfors, Överveda, Rappasundet, Hälla, Lillberget, Glösa, Sörånäset and Ställverksboplatsen (the Ställverket site). The Ställverket site at Näsåker (Nämforsen) has been the object of particular study. It has also been viewed in a broader context by analysis and interpretation of other ancient remains in the neighbouring area. I have argued that some interpretations arrived at in earlier research are problematical and that none of the thirteen sites can be said with certainty to have been an aggregation camp. Thus aggregation camps seem not usually to have been a part of the contact network in the area of study. Instead of using aggregation camps as meeting-places, the people involved seem, at certain times and places, to have maintained contact with each other by means of meetings at the base camps, notably the winter sites. These sites seem to have been rather sedentary and are positioned at fairly even distances from one another. I call this model the base camp model. Some grounds for applying the base camp model seem to exist at certain places in the inland region from the end of the Mesolithic era up to 0 BC. After that contact networks seem to change. In the coastal district it seems possible to apply it to some places from the transition between the Mesolithic – Neolithic Age up to about 2500 BC. Thereafter the picture is unclear. The study does also emphasise however that more in-depth studies are needed to strengthen the viability of the base camp model’s applicability, that there are still big gaps in the material and that much work still remains to be done in order to solve the problems of how aggregation camps can best be defined and how they can be identified archaeologically.

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Mittels spontaner Raman-Streuung im Überschallstrahl wurden kleine Moleküle und Molekülaggregate untersucht. Es wird gezeigt wie Schwingungs- und Rotationstemperaturen im Jet mittels des Stokes/Anti-Stokes-Intensitätsverhältnisses bestimmt werden können. In Studien kleiner Wassercluster konnten Kopplungskonstanten der gebundenen OH-Oszillatoren verschiedener Ringcluster von Trimeren bis Pentameren bestimmt werden, die auch zum Verständnis der Dynamik in kondensierten Phasen relevant sind. Außerdem wird die experimentelle Ermittlung von Enthalpiedifferenzen verschiedener Monomerkonformere zweier isomerisierungsdynamisch sehr unterschiedlicher Systeme vorgestellt. Des Weiteren wurde die Weiterentwicklung der bestehenden Raman-Technik durch Kopplung mit einer IR-Laseranregung realisiert und erste Tests des neuen Aufbaus durch Studien des Methanol-Dimers durchgeführt.

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Demand forecasting performance is subject to the uncertainty underlying the time series an organisation is dealing with. There are many approaches that may be used to reduce demand uncertainty and consequently improve the forecasting (and inventory control) performance. An intuitively appealing such approach that is known to be effective is demand aggregation. One approach is to aggregate demand in lower-frequency 'time buckets'. Such an approach is often referred to, in the academic literature, as temporal aggregation. Another approach discussed in the literature is that associated with cross-sectional aggregation, which involves aggregating different time series to obtain higher level forecasts.This research discusses whether it is appropriate to use the original (not aggregated) data to generate a forecast or one should rather aggregate data first and then generate a forecast. This Ph.D. thesis reveals the conditions under which each approach leads to a superior performance as judged based on forecast accuracy. Throughout this work, it is assumed that the underlying structure of the demand time series follows an AutoRegressive Integrated Moving Average (ARIMA) process.In the first part of our1 research, the effect of temporal aggregation on demand forecasting is analysed. It is assumed that the non-aggregate demand follows an autoregressive moving average process of order one, ARMA(1,1). Additionally, the associated special cases of a first-order autoregressive process, AR(1) and a moving average process of order one, MA(1) are also considered, and a Single Exponential Smoothing (SES) procedure is used to forecast demand. These demand processes are often encountered in practice and SES is one of the standard estimators used in industry. Theoretical Mean Squared Error expressions are derived for the aggregate and the non-aggregate demand in order to contrast the relevant forecasting performances. The theoretical analysis is validated by an extensive numerical investigation and experimentation with an empirical dataset. The results indicate that performance improvements achieved through the aggregation approach are a function of the aggregation level, the smoothing constant value used for SES and the process parameters.In the second part of our research, the effect of cross-sectional aggregation on demand forecasting is evaluated. More specifically, the relative effectiveness of top-down (TD) and bottom-up (BU) approaches are compared for forecasting the aggregate and sub-aggregate demands. It is assumed that that the sub-aggregate demand follows either a ARMA(1,1) or a non-stationary Integrated Moving Average process of order one, IMA(1,1) and a SES procedure is used to extrapolate future requirements. Such demand processes are often encountered in practice and, as discussed above, SES is one of the standard estimators used in industry (in addition to being the optimal estimator for an IMA(1) process). Theoretical Mean Squared Errors are derived for the BU and TD approach in order to contrast the relevant forecasting performances. The theoretical analysis is supported by an extensive numerical investigation at both the aggregate and sub-aggregate levels in addition to empirically validating our findings on a real dataset from a European superstore. The results show that the superiority of each approach is a function of the series autocorrelation, the cross-correlation between series and the comparison level.Finally, for both parts of the research, valuable insights are offered to practitioners and an agenda for further research in this area is provided.