Miracle-dz/UniFAR-FTUs huggingface dataset:
Associations between Milk Fatty Acid Profile and Body Condition Score, Ultrasound Hepatic Measurements and Blood Metabolites in Holstein Cows

Simple Summary Metabolic disorders represent a crucial problem in early lactating dairy cows, which lead to major economic losses at the herd level. To allow the prompt detection of metabolic dysfunction with noninvasive and ready-to-use methods on the farm, milk matrix represents the best option. Among milk fine components, the fatty acid profile represents a fingerprint of the cow’s nutritional and metabolic status, being a suitable indicator of metabolic imbalance at the cow level. We performed an association study between milk fatty acid profile and a set of metabolic indicators, such as body condition score, ultrasound liver measurements, and blood metabolites, from 297 Holstein–Friesian cows. We extracted a few latent variables able to explain specific biological mechanisms from the milk fatty acid profile. Then, we explored the associations between these new synthetic variables, namely the factors, and the morphometric, ultrasonographic and hematic indicators of immune and metabolic status. The significant associations of fatty acid factors with blood and ultrasound indicators of inflammation and hepatic load showed the capacity of fatty acids to reflect the energy metabolic status of lactating cows, suggesting their potential usefulness as markers of digestive alterations and metabolic variations in cows during the critical period of early lactation. Abstract Dairy cows have high incidences of metabolic disturbances, which often lead to disease, having a subsequent significant impact on productivity and reproductive performance. As the milk fatty acid (FA) profile represents a fingerprint of the cow’s nutritional and metabolic status, it could be a suitable indicator of metabolic status at the cow level. In this study, we obtained milk FA profile and a set of metabolic indicators (body condition score, ultrasound liver measurements, and 29 hematochemical parameters) from 297 Holstein–Friesian cows. First, we applied a multivariate factor analysis to detect latent structure among the milk FAs. We then explored the associations between these new synthetic variables and the morphometric, ultrasonographic and hematic indicators of immune and metabolic status. Significant associations were exhibited by the odd-chain FAs, which were inversely associated with β-hydroxybutyrate and ceruloplasmin, and positively associated with glucose, albumin, and γ-glutamyl transferase. Short-chain FAs were inversely related to predicted triacylglycerol liver content. Rumen biohydrogenation intermediates were associated with glucose, cholesterol, and albumin. These results offer new insights into the potential use of milk FAs as indicators of variations in energy and nutritional metabolism in early lactating dairy cows.
Concept Detection in Philosophical Corpora

During the course of research, scholars often search large textual databases for segments of text relevant to their conceptual analyses. This study proposes, develops and evaluates two applications of word embedding algorithms for automated Concept Detection in theoretical corpora: Average Cosine Similarity Retrieval (ACS) and Word Mover’s Distance Retrieval (WMDR). Both strategies are evaluated against weighted keyword (KW) search using a test set from the Digital Ricœur corpus tagged by scholarly experts. In our experiments, WMDR outperformed weighted keyword search on the Concept Detection task, which suggests it is a promising strategy for Concept Detection and information retrieval systems focused on theoretical corpora. Besides these initial positive results, WMDRl has as its major characteristic the ability to use definitions as proxies for concepts; this provides search results that account for the semantic contexts of theoretical concepts.Au cours de la recherche, les chercheurs tâchent souvent de trouver des segments de texte pertinents dans d’énormes bases de données textuelles pour leurs analyses conceptuelles. Cet article propose, développe et évalue deux applications d’algorithmes de word embedding (plongement lexical) pour la Concept Detection (détection de concept) dans des corpus théoriques : dans l’Average Cosine Similarity Retrieval (ACS – Extraction de similitudes cosinus moyenne) et dans la Word Mover’s Distance Retrieval (WMDR – Extraction de distance de déplacement lexique). Les deux stratégies seront évaluées par rapport à une recherche par mot-clés pondérée avec un dispositif de test venant du corpus Digital Ricœur, qui est étiqueté par des experts érudits. Dans nos expériences, la WMDR était plus performante que la recherche par mot-clés pondérée durant la tâche de détection de concept, ce qui suggère que cela soit une stratégie prometteuse pour la détection de concept et pour des systèmes d’extraction d’information axés sur des corpus théoriques. En outre, la WMDR a comme caractéristique majeure la capacité de se servir de définitions en tant que des proxys pour des concepts. Cela fournit des résultats de recherche qui explique les contextes sémantiques de concepts théoriques.
The Evolution of Strategy (Over Six Decades and Thirty Models)

Over the last 50 years we have witnessed an impressive collective effort to develop the business sciences. Just like in other social sciences, ideas in business management evolve over time through an ongoing historical process. Discovering previous authors and models can be a very useful source of knowledge for carrying out their leadership task in the best way possible. But this does not seek to be a historical review leading to nostalgic contemplation, but rather an invitation to action. Classics can and should coexist with the latest bestsellers on the manager’s bookshelf. The task of the leader is to read well, select these strategic tools appropriately and know how to apply them to the context of his or her organisation. The 21st century manager must understand the evolution of strategy in order to be the architect of tomorrow’s decisions.
Vocal Behaviour of a Bottlenose Dolphin Pod during a Deadly Bycatch Event in the Gulf of Catania, Ionian Sea

Cetacean bycatch is increasing worldwide and poses a threat to the conservation of several delphinids. The bottlenose dolphin (Tursiops truncatus) is frequently involved in bycatch incidents, due to its coastal distribution and opportunistic behaviour. The acoustic behaviour of cetaceans during death-related events is a largely unexplored topic. During an acoustic monitoring survey of the bottlenose dolphin population inhabiting the Gulf of Catania (Ionian Sea), we documented the entangling and subsequent death of a sub-adult male in a fishing net. Here, we provide a detailed analysis of the vocal behaviour of the pod of bottlenose dolphins during the event. We identified a total of 720 vocalisations in a timespan of 138 min, including 436 signature whistles, 51 non-signature whistles, and 233 burst pulses. We recorded high vocal activity, with a peak characterised by emission rates of 36 signature whistles per minute and 70 burst pulses per minute. Although future studies are required, our results show massive vocal activity during net entangling, characterised by a significant emission of signature whistles and burst pulses, including bray series of gulps and squeaks. Therefore, we suggest that developing tools for automatically detecting the peaks of these sound types could be helpful in recognising bycatch events, in order to better quantify the impact of professional fishing on small cetaceans.
Green innovation and environmental awareness driven green purchase intentions

PurposeThe purpose of this study is to explore the role of environmental awareness, environmental concerns, and green innovation toward green purchase intentions. This paper theoretically extends the existing knowledge on the subject matter and adds value to the existing knowledge.Design/methodology/approachBased upon the existing literature and relevant theories the study developed several assumptions/hypotheses. To test the hypothesis, a comprehensive data set that was collected through online survey method was utilized. For the empirical analysis the study employed structural equation modeling technique.FindingsThe results from the study indicated that environmental awareness significantly reinforce green purchase intentions. Whereas, the authors could not find evidence for the direct influence of green innovation on green purchase intentions. The analysis show, green product knowledge and environmental concerns partially mediate the relationship among environmental awareness and green purchase intentions. However, green product knowledge and environmental concerns fully mediate the relationship among green innovation and green purchase intentions.Originality/valueThe study measures the role of green innovation, environmental awareness, environmental concerns, and green product knowledge toward green purchase intentions which is pivotal for sustainable consumption. Similarly, the study adds value to the existing research on the management of environmental awareness and protection through reinforcing green purchases.
Predictors of Academic Achievement at Different Levels of Socioeconomic Status

Success is a concept that is desired by everyone. In the Turkish education system, Anatolian high schools are considered one of the most prestigious schools which accept students via national central exams. The purpose of this study is to reveal indicators explaining the placement into Anatolian high schools, which is an important sign of success, in socioeconomically different regions. Logistic regression analyses were used as a prediction design. Data was collected from the 1049 10th grade high school students in Istanbul. According to findings, the indicators affecting the probability of studying in Anatolian high school differ between the low life quality indexed region (LLQR) and the high life quality indexed region (HLQR). In LLQR GPA, gender, number of people in the household, and mother’s monetary contribution were found as significant indicators. In HLQR GPA, father’s income and mother’s education level were found as significant indicators. These results are discussed using the main theories of educational sociology.
Differential spin Hall MRAM based low power logic circuits and multipliers

A Multiplier is an essential component that dictates the performance of modern computing systems. However, high power dissipation of complementary metal-oxide semiconductor (CMOS) multiplier circuits has become a major concern in sub 45 nm technology nodes. Recently, emerging non-volatile memory based hybrid circuits have gained a lot of attention due to the prominent feature of negligible static power consumption. Magnetic tunnel junction (MTJ) based spin-torque memories have been used for low power applications. However, spin-transfer torque magnetic random-access memory (STT-MRAM) based hybrid CMOS/MTJ circuits exhibit higher write energy and longer incubation delay. In this work, a differential spin Hall (DSH)-MRAM cell is employed for logic and circuit applications. It stores a pair of complementary bits with low write voltage and reduced area. The variability analysis of DSH-MRAM signifies the availability of sufficient margin between different resistance states. Different types of 8 × 8 and 4 × 4 hybrid CMOS/MTJ multipliers are analyzed using DSH based adders and logic gates. The proposed multipliers consume approximately 20% less power and exhibit 19% improvement in power-delay product characteristics compared to CMOS based multipliers.
Adaptation and Change in Creative Clusters: Findings from Vienna's New Media Sector

Abstract This paper investigates some of the features of technological heterogeneity in the New Media cluster in Vienna and the local and global factors that have shaped territorial learning conditions over time. Technological heterogeneity is given a central role in cluster evolution for the expansion of local capacities and opportunities for change. In this paper, it is argued that technological heterogeneity is an important but insufficient motor for cluster evolution. Rather, what is required are local technological capabilities and learning conditions for the exploitation of technologies for operations and procedures that are relevant for firm and cluster performance, as posited by evolutionary theories of technical change. These perspectives are used to interpret the complex, variegated and partially unpredictable features of technological heterogeneity in the New Media cluster in Vienna, revealing the importance of the capabilities embodied in people and local conditions of managing uncertainty mediated via heterogeneity in products, processes and client needs. For this sector, conditions of technological instability create increasing importance for local learning and networks if clusters are to be propelled more deeply into existent or more radically into novel specializations.
Assessing the skill of football players using statistical methods

Professional football is a business worth billions of pounds a year. Player recruitment is a key aspect of the business with expenditures directly related to it (in the form of transfer fees and wages) accounting for the majority of clubs’ budgets. The purpose of this study is to propose methods to assist player evaluation based on statistical modelling that could be used to support recruitment decisions. In this thesis we argue that if such methods are to serve as the basis of player valuation, they need to have predictive utility, since it is players’ future performance that clubs benefit from and thus should be paying for. We present examples of how simplistic approaches to quantifying a footballer’s skill lack such predictive character. The original contribution of this thesis is a framework for evaluating footballers’ worth to a team in terms of their expected contribution to its results. The framework attempts to address one of the key difficulties in modelling the game of football, i.e. its free-flowing nature, by discretising it into a series of events. The evolution of the game from one event to another is described using a Markov chain model in which each game is described by a specific transition matrix with elements depending on the skills of the players involved in this game. Based on this matrix it is possible to calculate game outcome related metrics such as expected goals difference between the two teams at the end of the game. It enables us to establish a link between a specific skill of a given player and the game outcome. The skill estimates come from separate, location specific, models, e.g. the shooting skill for each player is estimated in a model of converting shots to goals given the shot location. We demonstrate how recognising the involvement of random chance in individual performance, together with accounting for the environment in which the evaluated performance occurred, gives our statistical model a predictive advantage when compared to naive methods which simply extrapolate past performance. This predictive advantage is shown to be present when passing and shooting skills are evaluated in isolation, as well as when measures of passing and shooting skills are combined in the proposed comprehensive metric of player’s expected contribution to the success of a team.
John Boyd on competition and conflict

Abstract This article reprises central aspects of John Boyd’s thinking about competition and conflict, including his unwavering reliance on analogies and connections between disciplines as disparate as fighter tactics, decision theory, history, philosophy, and physics. We trace how elements of Boyd’s ideas about winning and losing have been incorporated (or neglected) in the doctrines of the U.S. military services. Given the richness of Boyd’s ideas there is much we can learn from the view of decision making underlying the Observation-Orientation-Decision-Action (OODA) loop, for which he is best known, as well as the analogical reasoning embodied in slide presentations such as his massive “Patterns of Conflict. ”
Effect of Addition Rubber Modified Montmorillonite on Some Properties of Heat Cured Polymethyl Methacrylate Resin

Aims : The goal of this research was to create a composite of rubber modified-montmorillonite (MMT) and heat cured Polymethyl Methacrylate (PMMA) resin to improve some of the mechanical and physical properties of heat cured (PMMA). Subjects and Methods : A total of 120 specimens were made and divided into four groups, (n=30) for each group. Group A, control group made of conventional heat cured PMMA with no reinforcement. Specimens of the other groups were reinforced by the rubber modified MMT composite with different percentages (2%, 4% and 8%) by weight. Group B (2% composite), group C (4% composite) and group D (8% composite). All specimens were evaluated as regard impact strength, transverse strength, water sorption, hardness, and roughness. Results: The results of this study revealed that, impact strength values of acrylic resin denture base were increase after the addition of rubber MMT –composite at any ratio. After addition of 2% rubber MMT-composite the flexure strength was nearly similar to that of control group. While, a significant reduction occurred after adding 4% and 8% composites. Water sorption was significantly increased by the addition of 4% and 8% of rubber –MMT composite ( P < 0.05). There was a significant decrease in the micro hardness after the addition of 4% and 8 % composite, while insignificant decrease occurred with 2% ratio. As regards to surface roughness there was significant increase in the surface roughness values after addition of rubber –MMT composite for all ratios (P < 0.05). Conclusion : The most favorable properties were observed by the addition of 2% rubber –MMT acrylic composite to the heat-cured acrylic resin . However, PMMA denture base material has drawbacks such as insufficient surface hardness, low flexure and impact strength. Clinically, failure of complete or partial denture prosthesis is most
Pedestrian trajectory prediction based on temporal attention

Aiming at the problem that pedestrian trajectory prediction network based on Encoder-Decoder structure is easy to lose part of trajectory information in the process of long sequence encoding and decoding, Generative Adversarial Network based on Temporal Attention (TA) is proposed in this paper. It is used to assign influence weights to the trajectory information of the encoding and decoding layer, so that the model can make full use of the trajectory information useful for predicting the trajectory in the future and reduce the influence of redundant information. This paper adds a TA to the encoding and decoding layers of the Generative Adversarial Network, and trains it on the ETH and UCY datasets. Experimental results show that the proposed network has better prediction accuracy than existing methods.
Sparse seismic reflectivity inversion using an adaptive fast iterative shrinkage‐thresholding algorithm

Seismic reflectivity inversion using l1‐norm regularization produces sparse solutions by applying an l1‐norm constraint. The fast iterative shrinkage‐thresholding algorithm is one of the most effective methods to solve l1‐norm regularized inversion problems. A large number of iterations are commonly required in the fast iterative shrinkage‐thresholding algorithm because its solution converges slowly towards the sparse solution. To improve its convergence rate, we introduce a modifying strategy for the traditional fast iterative shrinkage‐thresholding algorithm. When implementing the soft‐thresholding operator, the thresholding value is adaptively adjusted by assigning the reciprocal of the solution in the previous iteration as a weight to the thresholding value of the current iteration. In this way, small variables in the solution produce large coefficients applied to the thresholding value, which causes small variables to quickly converge to zero. The adaptive fast iterative shrinkage‐thresholding algorithm shows significantly improved computational efficiency and accuracy compared to the traditional fast iterative shrinkage‐thresholding algorithm. It produces good results for both numerical and field examples of l1‐norm regularized seismic reflectivity inversion.
Legitimação e Circulação do discurso em aulas de ciências: um modelo multidimensional de análise

O objetivo deste texto é refletir sobre o processo de circulação e legitimação do discurso em aulas de ciências, por meio da estratégia de ensino de rodas de conversa. Para a análise da circulação e legitimação do discurso, aqui considerada como fazendo parte do processo de produção de conhecimento, utilizamos um modelo multidimensional de análise no qual fazemos uso de ferramentas analíticas propostas por dois campos teóricos, a Teoria do Código de Legitimação e as Interações Discursivas. Para esta análise utilizamos dados da própria sala de aula para identificar como o processo de circulação e legitimação afeta as próprias condições de sua produção. As análises dos perfis semânticos revelaram pouca variação entre os diferentes níveis de gravidade e densidade semântica e as análises das interações discursivas evidenciaram a importância dos movimentos epistêmicos realizadas pela professora e o tipo de abordagem comunicativa utilizada nas Rodas de Conversa. Com base nos resultados, entendemos que este modelo multidimensional de análise possui potencial para uma compreensão mais abrangente sobre o processo de circulação e legitimação do discurso científico em sala de aulas de ciências
Structural Characterization of Nanocellulose/Fe3O4 Hybrid Nanomaterials

The rise of innovation in the electrical industry is driven by the controlled design of new materials. The hybrid materials based on magnetite/nanocellulose are highly interesting due to their various applications in medicine, ecology, catalysis and electronics. In this study, the structure and morphology of nanocellulose/magnetite hybrid nanomaterials were investigated. The effect of nanocellulose loading on the crystal structure of synthesized composites was investigated by XRD and FTIR methods. The presented study reveals that the interaction between the cellulose and magnetic nanoparticles depends on the nanocellulose content. Further, a transition from cellulose II to cellulose I allomorph is observed. SEM and EDS are employed to determine the variation in morphology with changes in component concentrations. By the calculation of magnetic interactions between adjacent Fe3+ and Fe2+ ions within composites, it is determined that ferromagnetic coupling predominates.
Research in mechanical behavior of RC joints with specially shaped columns under high axial force

Because of special section shape,the joints with specially shaped columns under high axial compression ratio will damage more seriously than the joints with ordinary rectangular columns when suffering earthquakes.Through the low frequency cyclic loading experiment of an exterior joint and a middle joint with specially shaped column,the development and destruction of concrete cracks of the joints with specially shaped columns under high axial force were analyzed,the shearing strength of the joints core were calculated by experiment data,and the shear mechanism of the joints with specially shaped column was investigated combined with the stirrup strain distributed in joint core.It is shown that the joint with specially shaped column under high axial force have larger shear,and the concrete in web of joint core will be cracking more seriously,so joints become the weakness site of the structure with specially shaped columns,thus restricting the storey height of structure.