3 In the last couple of decades there has not happened much in the “farriery”- department. The work procedure, methods and farrier´s tools have stayed the same over time, which have led to a huge workload that is wearing the active participants out. So think if you were able to ease the working process of horseshoeing for a farrier. The farriery is still first and foremost a profession based on handicraft that has to relay on the farrier´s good memory, sight and sense. The workplaces for a farrier is most of the time at the hiring horse owner`s stables, which makes it harder for the farrier´s to have influence over their working situation. In Sweden shoes horses by both educated and uneducated people, but there is hopes to legalise the profession title by year 2030. One of the greatest advantages through this project, has been to observe and the participant in a farrier´s everyday work. Experimentally mockups and visually shown images have been used as the basis for the discussions with people within the horse industry. The farrier`s work a ethics and work environment are very unexplored subjects in modern time, which influenced the work material in the project´s needs and analysis. The inspiration for the project’s end-result is, among other things, based on horsey´s and the farrier´s ancient origin. As well as the requisites of technology in the work. The end-result is based to decrease the unnecessary repeating work that happens everytime a shoeing emerges. With the help of the Hoof scanner, can the farrier´s have a profile for every single horse i.e. visually images of the hoof, choice of shoes, need of elaboration work, necessary balance adjustments, history and clarified pictures. The functions are able to adjust to every farrier´s need of scene. Documented and visual information can be transcribed (pay it forward) between farrier, veterinary and horse owner.

Palmolja sägs vara världens mest resurseffektiva oljegröda och återfinns i bland annatlivsmedel, oleokemikalier och biobränsle. Mer än varannan produkt i dagligvaruhandlarinnehåller palmolja. Den höga efterfrågan har gjort palmoljeindustrin attraktiv att investera i och att många aktörer är involverade. En lång aktörskedja gör industrin svår att kontrollera, ansvarstagandet brister och en komplex hållbarhetsproblematik uppstår. För uppnå hållbarhet krävs samspel mellan ekologi, samhälle och ekonomi. Idag överutnyttjas naturens resurser vilket leder till att samspel mellan dimensionerna inte nås. För att få bättre förståelse och inblick i den komplexa hållbarhetsproblematiken tog vi del av experters och aktörers olika perspektiv. För studien valdes en kvalitativ intervjumetod som kartlägger miljökonsekvenser som ansågs störst. Sedan återges lösningsmöjligheter att skapa en mer hållbar palmoljeindustri. Resultatet visade att möjliga lösningstågärder bör baseras på ett tydligt definierat och ökat ansvarstagande för problem och konsekvenser som uppstår på grund av palmoljeindustrin. / Palm oil is known for being an efficient and productive crop and can be found in for example food, chemicals and biofuel. Up to every second product in grocery stores contains palm oil. Today's high demand of palm oil makes the industry attractive for investments while involvement from several actors makes the industry hard to control and lack of responsibility occurs. Those factors are of major menace for a sustainable palm oil industry. To achieve sustainability an interaction between ecology, society and economy needs to arise. Nature's resources are today over-exploited which leads to a non-interaction within the earlier mentioned dimensions. This study maps what we consider the greatest environmental issues and possible measures are to create a more sustainable industry. The result shows that increased and clearly defined responsibility for all actors involved in the industry needs to appear and improve to create sustainability.

Affective states of animals are emotions with positive or negative valance. Positive and negative affective states affect animal welfare, and can bias interpretation of information positively or negatively, respectively. Judgement bias tests measure affective states based on responses to ambiguous cues, intermediate to cues with learnt positive and negative outcomes. Responses closer to those of positive cues indicate positive affective state. However, animals need extensive training to learn initial associations to reference cues. Therefore, I here aimed to validate an alternative affective state test based on instinctive avoidance of patterns resembling eyespots. Responses to ambiguous eyespot cues similar to responses to full eyespot cues could indicate negative affective state. To test this, behavioural responses of red junglefowl (Gallus gallus) chicks to ambiguous cues from a validated judgement bias test were compared to responses to cues resembling eyespots. In a second cohort of birds, I developed simplified tests with only one ambiguous cue in each tests. I predicted that responses in both tests would correlate positively. In the original tests, shorter distance and latency to approach ambiguous cues correlated positively with latency to approach one of the eyespot cues, a full eyespot cue. This pattern was only observed in females. In the simplified tests, at 4 weeks of age, shortest latency to approach cues correlated among tests. This pattern was not observed when chicks were tested at 2 weeks of age. Overall, the eyespot test is a promising alternative affective state test, but further studies exploring sex- and age-effects, are needed.

Mastitis is an inflammation that is caused in the udder tissue of cattle and which annually causes high costs within productions and the profitability of farms. The purpose of this study is to determine if udder inflammation affects both the amount of milk that produces and investigate how the protein and fat -content are affected. To be able to implement the study, I have used data from a farm in Värmland where mastitis is a common disease affecting the cows, and which reduces profitability annually. From the year 2015, a total of 134 cows on the farm where the study occurred were treated with antibiotics by a veterinarian, where up to half of the cows were affected by a clinically visible infection. Two groups have been used in the study where 45 cows affected by mastitis have been examined through test milking results and then compared with a control group consisting of healthy individuals where I have used cows that have not been visibly affected by mastitis. The results for the study of how the milk volume is affected showed a significant difference for a decrease in the quantity last year (P =0,036). Based on the results, it is concluded that clinical mastitis reduces the amount of milk and the content of the milk. / Mastit är en inflammation som orsakas i juvervävnaden hos nötkreatur och som årligen orsakar stora kostnader inom produktionen och lönsamheten på gårdar. Syftet med denna studie var att fastställa om juverinflammationer kan påverkar en nedgång inom den mängd mjölk som produceras samt undersöka hur protein- samt fetthalten påverkas eftersom innehållet är en viktig del av lönsamheten. För att kunna genomföra studien har jag använt mig av data från en gård i Värmland där mastit är en vanlig förekommande sjukdom som drabbar korna, och som årligen drar ner på lönsamheten. Från år 2015 har totalt 134 kor på gården där studien genomförts varit behandlade med antibiotika av veterinär där uppemot hälften av korna drabbades av en klinisk synlig infektion. Två grupper har använts i studien där 45 kor drabbade av mastit har undersökts genom provmjölkningsresultat och som sedan jämförts med en kontrollgrupp bestående av friska individer där kor som ej har varit synligt drabbade av mastit använts. Resultatet för undersökningen av hur mjölkmängden påverkas visade en signifikant skillnad för en minskning av mängden sista året (P=0,036) men ingen signifikant skillnad över fett och proteinhalten kunde ses. Utifrån resultatet dras slutsatsen att klinisk mastit minskar mjölkmängden medan innehållet av fett och protein förblir opåverkat.

Syfte: Studien tar sin utgångspunkt i hur elever på Hippologigymnasiet ser på hästen som moti-verande faktor i deras lärande. Syftet med denna undersökning är att beskriva och försöka skapa bättre förståelse för på vilket sätt hästen direkt eller indirekt betyder för motivationen till lärande. Med utgångspunkt i Antonovskys (2007) teori om KASAM, känsla av sammanhang, kopplat till stallets sociala arena, samspelet med hästen och målinriktning studeras faktorer som har betydelse för elevernas motivation till lärande. Metod: Studien baseras på kvantitativ och kvalitativ data från 49 enkäter (svarsfrekvens 74 %) samt på en gruppintervju med fyra elever. Resultat: Studien visar att egenskaper som disciplin, ansvar, handlingsförmåga och ledarskap utvecklas i stallmiljön. Regler och normer i stallet utgör en fostrande social arena som präglar de som vistas där sedan tidig ålder, av betydelse för den egna motivationen till lärande. Motivation-en till lärande stärks då eleverna känner ett sammanhang när egna erfarenheter tillsammans med nya kunskaper gör att de klarar av utmaningar man ofta ställs inför i stallmiljön i samspelet med hästen. Detta skapar meningsfullhet som ökar graden av elevers känsla av sammanhang, KASAM, och därmed en viktig faktor för motivationen till lärande. Studien visar även på samband mellan målsättning och motivation med hästen som utgångspunkt, eleverna är mycket målinriktade och redan i samband med val av skola vet majoriteten (92 %) inom vilket område de studera efter avslutat gymnasium. Dessutom visar resultatet att de som har egen häst planerar sin studietid i högre grad än de som inte har egen häst. Slutsats; Hästen är en betydelsefull faktor för motivationen till lärande direkt eller indirekt.

Den negativa attityden kring palmolja har uppkommit för att industrin ur ett hållbarhetsperspektiv brister i sociala, ekonomiska och ekologiska aspekter. Produktionen finns i utvecklingsländerna, främst i Malaysia och Indonesien. Intresset för palmolja har ökat i Liberia, som tillsammans med Sverige är studieländer i den här undersökningen. Industrin har en stor miljöpåverkan, det förekommer dåliga arbetsförhållanden med låga löner och brist på rättigheter. Palmoljeindustrin har samtidigt i utvecklingsländerna gett möjlighet till ökad välfärd, då industrin är det som primärt ger inkomst för lokalbefolkningen.Studiens resultat visar att en uteslutning av palmolja i produkter inte är en lösning på problemet. En möjlig lösning till problemet är istället att samarbeta och jobba för hållbar odling av palmolja. / The negative attitude towards palm oil has arisen because of the sustainability of industry in social, economic and ecological aspects. Production is in developing countries, mainly in Malaysia and Indonesia. The interest in palm oil has increased in Liberia, which together with Sweden are study countries in this survey. The industry has a major environmental impact, there are poor working conditions with low wages and lack of rights. At the same time, in the developing countries, the palm oil industry has provided an opportunity for increased welfare, as the industry is the primary source of income for the local population.The study results show that an exclusion of palm oil in products is not a solution to the problem. A possible solution to the problem is instead to cooperate and work for sustainable cultivation of palm oil.

In today's highly competitive industries, engineers are driven to not only design a better product to fulfill users' needs but also demanded to develop a product in a short time to occupy the market. With the development of data collection and visualization technology, the application of data visualization into product development to enhance the ability of better product design is a significant trend.  Data visualization becomes more and more important since it could illustrate the valuable information, such as tacit needs and patterns which hidden from data, in a communicated way to help engineers get more inspiration for the conceptual design.   It is not hard to collect data; however, the challenge is to visualize the valuable information from a large number of data concisely and intuitively. In recent years, there are some visualization techniques available for product design, while, most of them are implemented in the later stage of product development, few methods are applicable for conceptual design. Therefore, this thesis is carried out to explore appropriate visualization techniques to provide support for conceptual design.   The aim of this thesis is, in an engineering environment, to investigate ways to visualize complex data legibly and intuitively to enhance engineers’ ability for conceptual design from better understanding the current machine. In order to achieve the objective, a conceptual design case of the improvement of wheel loader fuel consumption is applied, which consisted of plenty of data sets within various parameters, to explore how to reveal the hidden information of complex data for engineers.   As the result of this thesis, a prototype contains a series of visualization techniques is proposed to demonstrate data information from a wheel loader under several visualization situations. The final prototype has the functions of visualizing different operations separately; visualizing the overall fuel consumption in one operation; cluster's patterns visualization; visualizing the impact of one variable on the whole value.

Antimicrobial resistance is a major global health challenge. It threatens the achievement of multiple SDGs with disproportionately negative consequences for LMICs. AMR is associated with the misuse of antibiotics, which is especially dominant in livestock farming. On-farm biosecurity has been identified as an effective way to prevent diseases. This requires a change in the daily behaviours of farmers. While the application of social-psychological models gained immense popularity in veterinary and agricultural research, these models lack predictive and explanatory character, leading to the so-called intention-action gap. The emerging field of behavioural sciences likely offers a better explanation of human behaviour, however, studies published often lack use of an explicit theoretical framework. Therefore, this exploratory study aims to address this gap by using Kahneman’s Dual-Process Theory as a theoretical framework for behaviour science studies. To this end, a qualitative study with 15 smallholder poultry farmers in rural Ghana was conducted. The findings suggested the presence of cognitive biases and heuristics that hinder farmers’ uptake of biosecurity measures, such as temporal discounting, social cues, cognitive overload, psychological inertia and habits. However, all factors must be considered, including knowledge gaps, as well as practical and economic constraints. It is clear from the study that farmers are not a homogenous group and that any promotion of biosecurity is destined to fail if they do not take farmers' psychological and contextual reality into consideration. Therefore, this thesis concludes that additional insights and hypotheses can be generated using behavioural science and that it offers a better and more holistic theoretical framework than currently used behavioural change models. Suggestions for further work include more empirical study in farmer decision-making related to on-farm biosecurity from a behavioural lens. Specifically, the use of quantitative and experimental methods to investigate and confirm the hypotheses that emerged from this study.

The primary sector is of high importance to the economy and wellbeing of many countries. This is especially true for Ecuador, where 51 percent of the population living in rural areas earn their living through agriculture, livestock and fishing activities. Unfortunately, inequality has been growing between the rural and urban population, most noticeably in rural small-scale farmers that have less social capital and access to resources. Therefore, this study focuses on small-scale farmers, in a small town called Alluriquin, and how their way of farming can contribute to sustainable livelihoods. The empirical data has been collected through semi-structured interviews, where eleven different individuals have been interviewed. Previous research together with the theory of Amartya Sen will serve as the framework for this study. In Alluriquin, the results show that crops such as sugarcane, yucca, cacao, plantain and bananas as well as the big interest in both cattle raising and dairy farming, helps the locals to maintain a sustainable livelihood. It can be learned from the results of this study and previous research that farmers are facing a lot of different challenges on a daily basis, and even though they had different methods of dealing with these issues, the challenges seem to be manageable. The outcome of this study shows how these eleven individuals are able to maintain a sustainable livelihood, and how this way of farming is influenced by both internal and external factors that might be harmful if they are not considered. This way of life does provide the local community with a blueprint to follow so that they can guarantee their immediate wellbeing and prepare themselves and their families for any unforeseen circumstances, achieving sustainable livelihoods inside rural communities.

This thesis explores the application of machine learning techniques, a type of artificial intelligence that enables computers to learn from data, in hydroponic systems for predicting basil plant height. Hydroponics is a method of growing plants without soil, using nutrient-rich water instead. Conducted at Devoteam, an IT consulting firm in Malmö, the study involved the implementation of two hydroponic systems: Deep Water Culture and Nutrient Film Technique, focusing on monitoring and collecting data such as electrical conductivity, pH levels, water temperature. Utilizing five distinct machine learning models, namely Linear Regression, Decision Tree, Random Forest, Support Vector Regression, and K-Nearest Neighbours, we analyzed their performance in predicting basil plant height. Data were collected using a system equipped with a microcontroller unit, EC sensor, and water temperature sensor, supplemented by data from the open dataset, OpenAg. Our findings indicate that the Random Forest model consistently outperformed other models across datasets, demonstrating superior accuracy and predictive capability. This research provides insights into leveraging machine learning for optimizing hydroponic cultivation practices.