Effect of gender, nationality and attitudes on weight reduction strategies

Health Economics and Policy,

Agri-food chain relationships in Europe – empirical evidence and implications for sector competitiveness

The roles of business relationships in selected European agri-food chains are analysed. Using survey data from 1,442 farmers, food processors and retailers in two commodity sectors (meat and cereals) and across six different EU countries, we test the empirical relevance of several theory-based determinants influencing the choice of relationship type and the sustainability of inter-enterprise relationships. This is undertaken for the overall dataset and separately for different chain stages (farmer-processor versus the processor-retailer relationships), commodities and individual countries. Overall, we find that sector and enterprise-specific determinants seem to influence the choice of a certain relationship type while chain-internal, dyadic factors affect the sustainability of relationships. A logistic regression analysis reveals that the preference for a relationship type, while being highly chain-specific, depends on the long-term orientation and the strive for independence of an enterprise and the product-quality requirements within a corresponding market. As for the sustainability of the analysed relationships, structural equation modelling results suggest that its most important determinant is effective communication, with its two components, adequate communication frequency and high information quality, being equally important. The existence of personal bonds and an equal power distribution between buyers and suppliers are the second most important determinants, followed by the negative impact of key staff leaving. The analysis also reveals that the relative importance of these determinants differs significantly across the two considered chain stages and between the countries investigated. Agribusiness managers, seeking to improve their supplier or buyer relationships, need to consider the crucial role of effective communication and the positive contribution that the existence of personal bonds can make to the development and maintenance of sustainable interactions.business relationships, agri-food chains, competitiveness, Agribusiness,

IAB-Haushaltspanel im Niedrigeinkommensbereich Welle 2 (2007/08) : Methoden- und Feldbericht

"Das Institut für Arbeitsmarkt- und Berufsforschung hat im September 2006 TNS Infratest Sozialforschung mit der Durchführung des 'Panels Arbeitsmarkt und soziale Sicherung' (PASS) beauftragt. Die Erhebung soll eine neue Datengrundlage schaffen, die es ermöglicht, Funktionsweise und Folgen des Sozialleistungssystems SGB II auf der Ebene der betroffenen Haushalte zu untersuchen. Dazu müssen die Lebens- und Problemlagen von Leistungsempfängern und Personen einer Kontrollgruppe über einen längeren Zeitraum hinweg erfasst werden. Konkretes Ziel der Studie ist es, die Wege in und aus dem Bezug von SGB II-Leistungen sowie die damit verbundenen Konsequenzen im Zeitverlauf zu beschreiben und zu erklären. Die zweite Welle des Panels startete im Herbst 2007. Hierfür wurde die Stichprobe der Leistungsbeziehenden um Bedarfsgemeinschaften ergänzt, die nach dem Zeitpunkt der Stichprobenziehung für die erste Welle neu in den Leistungsbezug eingetreten sind. In dem Bericht dokumentieren wir die verschiedenen Schritte der Feldarbeit und die Ergebnisse. Das zweite Kapitel geht kurz auf den Pretest ein. Das dritte Kapitel stellt die Feldarbeit während der Hauptuntersuchung dar und gibt sowohl einen Überblick über den Ablauf und die Organisation als auch über den Rücklauf und die Ausschöpfung. Im Anschluss daran wird im vierten Kapitel die Datenaufbereitung erläutert. Dazu gehört auf der einen Seite die Erstellung einheitlicher Datensätze, auf der anderen Seite die Datenprüfung. Daneben wird kurz die Vercodung der offenen Angaben zur beruflichen Tätigkeit und zum Wirtschaftszweig beschrieben. Im abschließenden fünften Kapitel wird die Gewichtung behandelt." (Autorenreferat, IAB-Doku)Datengewinnung, Befragung, IAB-Haushaltspanel, Datenaufbereitung, Datenqualität, Sozialgesetzbuch II

IAB-Haushaltspanel im Niedrigeinkommensbereich Welle 3 (2008/09) : Methoden- und Feldbericht

"PASS soll eine Datengrundlage schaffen, die es ermöglicht, Funktionsweise und Folgen des Sozialleistungssystems SGB II auf der Ebene der betroffenen Haushalte zu untersuchen. Dazu müssen die Lebens- und Problemlagen von Leistungsempfängern und Personen einer Kontrollgruppe über einen längeren Zeitraum hinweg erfasst werden. Die ersten beiden Wellen des Panels wurden von Herbst 2006 bis Herbst 2008 durchgeführt, die dritte Welle startete im Herbst 2008 und wird mit dieser Berichterstattung Ende 2009 abgeschlossen sein. In der dritten Welle wurde die Stichprobe der Leistungsbeziehenden wiederum um Bedarfsgemeinschaften ergänzt, die nach den Zeitpunkten der Stichprobenziehung für die erste und zweite Welle neu in den Leistungsbezug eingetreten sind. Für die bevölkerungsrepräsentative Stichprobe der Kontrollgruppe wurde dagegen auf eine Auftstockung verzichtet, da anzunehmen ist, dass einerseits Veränderungen in der Grundgesamtheit durch die Stichprobe abgebildet werden und dass andererseits auf Migration basierende Entwicklungen innerhalb des kurzen Zeitraums vernachlässigbar sind. In dem folgenden Bericht dokumentieren wir die verschiedenen Schritte der Feldarbeit und deren Ergebnisse. Das zweite Kapitel geht kurz auf den Pretest ein. Das dritte Kapitel stellt die Feldarbeit während der Hauptuntersuchung dar und gibt sowohl einen Überblick über den Ablauf und die Organisation als auch über den Rücklauf und die Ausschöpfung. Im Anschluss daran wird im vierten Kapitel die Datenaufbereitung erläutert. Dazu gehört auf der einen Seite die Erstellung einheitlicher Datensätze und auf der anderen Seite die Datenprüfung. Daneben wird kurz die Vercodung der offenen Angaben zur beruflichen Tätigkeit und zum Wirtschaftszweig beschrieben. Im abschließenden fünften Kapitel wird die Gewichtung behandelt." (Autorenreferat, IAB-Doku)IAB-Haushaltspanel, Datenaufbereitung, Datengewinnung, Datenqualität, Bedarfsgemeinschaft, Antwortverhalten, Befragung

Search for Supersymmetry in events with an isolated lepton, at least 2-9 jets and missing transverse momentum with the ATLAS detector

This thesis presents a search for the supersymmetric partners of quarks (squarks) and glu- ons (gluinos) in proton-proton collision events with exactly one electron or muon, multiple jets and missing transverse momentum in the final state. The lepton signature suppresses the pure QCD background and the restriction to one lepton reduces the main backgrounds to processes with W boson decays which can be further suppressed via a requirement on the transverse mass. The data used amount to an integrated Luminosity of 36.1 fb−1 taken in 2015 and 2016 with the ATLAS experiment at the LHC with a centre of mass energy of 13 TeV. The search is performed in different signal regions, requiring at least 2-6 jets that are interpreted in a full statistical combination. An additional 9-jet signal region targets longer decay chains. The background in the 9-jet region is estimated by a data driven tech- nique, based on the invariance of the transverse mass distribution in events with different jet multiplicities. No significant excess of events above the standard model expectation was found. The 2-6-jet signal regions are interpreted in simplified models with squark and gluino one-step decays with a W boson and exclude gluino masses up to 2.1 TeV and squark masses up to 1.25 TeV at 95% confidence level. The 9-jet signal region is interpreted in simplified models with gluino two-step decays with a W and a Z boson and in a subset of the phe- nomenological minimal supersymmetric standard model (pMSSM). In the two-step models gluino masses are excluded up to 1.75 TeV and in the pMSSM models up to 1.7 TeV at 95% confidence level

Improved selective background Monte Carlo simulation at Belle II with graph attention networks and weighted events

When measuring rare processes at Belle II, a huge luminosity is required, which means a large number of simulations are necessary to determine signal efficiencies and background contributions. However, this process demands high computation costs while most of the simulated data, in particular in case of background, are discarded by the event selection. Thus, filters using graph neural networks are introduced at an early stage to save the resources for the detector simulation and reconstruction of events discarded at analysis level. In our work, we improved the performance of the filters using graph attention and investigated statistical methods including sampling and reweighting to deal with the biases introduced by the filtering.Comment: to be published in ACAT 2022 proceedings in the Journal Of Physics: Conference Serie

Key Factors Influencing Economic Relationships and Communication in Finnish Food Chains

The aim of this report is to discuss the role of the relationship type and communication in two Finnish food chains, namely the pig meat-to-sausage (pig meat chain) and the cereal-to-rye bread (rye chain) chains. Furthermore, the objective is to examine those factors influencing the choice of a relationship type and the sustainability of a business relationship. Altogether 1808 questionnaires were sent to producers, processors and retailers operating in these two chains of which 224 usable questionnaires were returned (the response rate being 12.4%). The great majority of the respondents (98.7%) were small businesses employing less than 50 people. Almost 70 per cent of the respondents were farmers. In both chains, formal contracts were stated to be the most important relationship type used with business partners. Although for many businesses written contracts are a common business practice, the essential role of the contracts was the security they provide regarding the demand/supply and quality issues. Relative to the choice of the relationship types, the main difference between the two chains emerged especially with the prevalence of spot markets and financial participation arrangements. The usage of spot markets was significantly more common in the rye chain when compared to the pig meat chain, while, on the other hand, financial participation arrangements were much more common among the businesses in the pig meat chain than in the rye chain. Furthermore, the analysis showed that most of the businesses in the pig meat chain claimed not to be free to choose the relationship type they use. Especially membership in a co-operative and practices of a business partner were mentioned as the reasons limiting this freedom of choice. The main business relations in both chains were described as having a long-term orientation and being based on formal written contracts. Typical for the main business relationships was also that they are not based on the existence of the key persons only; the relationship would remain even if the key people left the business. The quality of these relationships was satisfactory in both chains and across all the stakeholder groups, though the downstream processors and the retailers had a slightly more positive view on their main business partners than the farmers and the upstream processors. The businesses operating in the pig meat chain seemed also to be more dependent on their main business relations when compared to the businesses in the rye chain. Although the communication means were rather similar in both chains (the phone being the most important), there was some variation between the chains concerning the communication frequency necessary to maintain the relationship with the main business partner. In short, the businesses in the pig meat chain seemed to appreciate more frequent communication with their main business partners when compared to the businesses in the rye chain. Personal meetings with the main business partners were quite rare in both chains. All the respondent groups were, however, fairly satisfied with the communication frequency and information quality between them and the main business partner. The business cultures could be argued to be rather hegemonic among the businesses both in the pig meat and rye chains. Avoidance of uncertainty, appreciation of long-term orientation and independence were considered important factors in the business cultures. Furthermore, trust, commitment and satisfaction in business partners were thought to be essential elements of business operations in all the respondent groups. In order to investigate which factors have an effect on the choice of a relationship type, several hypotheses were tested by using binary and multinomial logit analyses. According to these analyses it could be argued that avoidance of uncertainty and risk has a certain effect on the relationship type chosen, i.e. the willingness to avoid uncertainty increases the probability to choose stable relationships, like repeated market transactions and formal written contracts, but not necessary those, which require high financial commitment (like financial participation arrangements). The probability of engaging in financial participation arrangements seemed to increase with long-term orientation. The hypotheses concerning the sustainability of the economic relations were tested by using structural equation model (SEM). In the model, five variables were found to have a positive and statistically significant impact on the sustainable economic relationship construct. Ordered relative to their importance, those factors are: (i) communication quality, (ii) personal bonds, (iii) equal power distribution, (iv) local embeddedness and (v) competition

Ultra-high-granularity detector simulation with intra-event aware generative adversarial network and self-supervised relational reasoning

Simulating high-resolution detector responses is a computationally intensive process that has long been challenging in Particle Physics. Despite the ability of generative models to streamline it, full ultra-high-granularity detector simu- lation still proves to be difficult as it contains correlated and fine-grained information. To overcome these limitations, we propose Intra-Event Aware Generative Adversarial Network (IEA-GAN). IEA-GAN presents a Transformer- based Relational Reasoning Module that approximates an event in detector simulation, generating contextualized high-resolution full detector responses with a proper relational inductive bias. IEA-GAN also introduces a Self- Supervised intra-event aware loss and Uniformity loss, significantly enhancing sample fidelity and diversity. We demonstrate IEA-GAN’s application in gen- erating sensor-dependent images for the ultra-high-granularity Pixel Vertex Detector (PXD), with more than 7.5 M information channels at the Belle II Experiment. Applications of this work span from Foundation Models for high- granularity detector simulation, such as at the HL-LHC (High Luminosity LHC), to simulation-based inference and fine-grained density estimation

Ultra-High-Resolution Detector Simulation with Intra-Event Aware GAN and Self-Supervised Relational Reasoning

Simulating high-resolution detector responses is a storage-costly and computationally intensive process that has long been challenging in particle physics. Despite the ability of deep generative models to make this process more cost-efficient, ultra-high-resolution detector simulation still proves to be difficult as it contains correlated and fine-grained mutual information within an event. To overcome these limitations, we propose Intra-Event Aware GAN (IEA-GAN), a novel fusion of Self-Supervised Learning and Generative Adversarial Networks. IEA-GAN presents a Relational Reasoning Module that approximates the concept of an ''event'' in detector simulation, allowing for the generation of correlated layer-dependent contextualized images for high-resolution detector responses with a proper relational inductive bias. IEA-GAN also introduces a new intra-event aware loss and a Uniformity loss, resulting in significant enhancements to image fidelity and diversity. We demonstrate IEA-GAN's application in generating sensor-dependent images for the high-granularity Pixel Vertex Detector (PXD), with more than 7.5M information channels and a non-trivial geometry, at the Belle II Experiment. Applications of this work include controllable simulation-based inference and event generation, high-granularity detector simulation such as at the HL-LHC (High Luminosity LHC), and fine-grained density estimation and sampling. To the best of our knowledge, IEA-GAN is the first algorithm for faithful ultra-high-resolution detector simulation with event-based reasoning