Miracle-dz/UniFAR-FTUs huggingface dataset:
ESTRATÉGIAS BIOCLIMÁTICAS DE PROJETOS PARA MELHORES DESEMPENHOS AMBIENTAIS EM UNIVERSIDADES NO SUL BAIANO

This research aims to point out alternatives of better environmentalperformance for educational institutions based on the principles of industrialecology, green infrastructure and bioclimatic architecture. Based on theTechnical Literature Review and field visits, proposals were prepared toaddress the needs raised in the systemic diagnosis of the UFSB SosigenesCosta campus in Porto Seguro. The aim of this paper is to recommend designsolutions that provide better building energy efficiency by switching fromconventional to cleaner energy sources to reduce campus operating costs,from natural ventilation systems and architectural solutions developedfrom local bioclimatology and environmental comfort parameters focusedon improving learning capacity in teaching environments. Actions wereproposed with the objective of contributing to the reduction of impacts andcosts in educational institutions, making their headquarters into examplesthat bring people closer to sustainability.
Differences in baking quality between wheat flours

Summary A study was made of six pairs of wheat flours, members of each pair being similar in protein content and other characteristics but differing in baking performance. Interchange of flour components showed that the origin of quality differences in all cases resided in the gluten protein. Measurements of loaf volume as a function of lipid content were made using defatted flours reconstituted with variable amounts of flour lipids. Loaf volumes for the poorer quality flours were below those for the paired samples over ranges of lipid content which varied from a small region near the natural lipid content to the complete range. Since lipid fractions behaved identically when exchanged between pairs of flours, this effect apparently reflected a gradation in protein quality. Preliminary results indicated that differences in protein quality were associated with the glutenin fraction although further work is needed to test the generality of this conclusion. No relation was found between baking quality and the amount of lipid bound by dough mixing.
Identification and host range assessment of Paratylenchus nanus (Tylenchida: Tylenchulidae) and Paratrichodorus minor (Triplonchida: Trichodoridae)

Adult and juvenile characters were used to identify Paratylenchus nanus Cobb, 1923 and Paratrichodorus minor (Colbran, 1956) Siddiqi, 1974 from soils under pasture in New Zealand. In glasshouse tests of 15 pasture plants, common in New Zealand, all good hosts (ratio of final to initial population >1) of P. nanus were grasses, namely Dactylis glomerata , Lolium multiflorum and L. perenne ( Neotyphodium endophyte-infected and-free), all new host records for this species. Good hosts of P.minor included those listed for P.nanus and Festuca arundinacea (endophyte-free) , Poa annua , Trifolium pratense , T. repens and T. subterraneum . Except for T. repens , these are all new host records for P.minor in New Zealand.
Effects of dietary fat inclusion at two energy levels on reproductive performance, milk compositions and blood profiles in lactating sows

Abstract This study was conducted to investigate the effects of dietary fat inclusion to create two energy levels on reproductive performance, milk compositions and blood profiles in lactating sows. Twenty-four multiparous sows were randomly assigned to four treatments according to a 2×2 factorial arrangement. Two energy levels (3365 and 3265 kcal/kg) were created by supplementing different fat levels (high and low). Higher energy level resulted in less (P<0.05) body weight and backfat loss, shorter wean-to-estrus interval, and greater body weight gain of piglets. Sows fed higher fat diet had higher (P<0.05) fat concentration in colostrum. Higher concentrations of triglyceride and creatinine and lower concentrations of luteinizing hormone at weanling were noted (P<0.05) in sows fed lower energy diet than those fed higher energy diet. In conclusion, feeding of higher energy diet during lactation may improve the reproductive performance of sows during lactation.
Genetic relatedness and spatial associations of dusky-footed woodrats (Neotoma fuscipes)

Abstract We studied the association between space sharing and kinship in a solitary rodent, the dusky-footed woodrat (Neotoma fuscipes). Genetic relatedness was inversely correlated with geographic distance for female woodrats but not for males, a pattern consistent with female philopatry and male dispersal. However, some female neighbors were unrelated, suggesting the possibility of female dispersal. Relatedness of female dyads was positively correlated with overlap of their home ranges and core areas, indicating that females were more likely to share space with relatives, whereas males showed no correlation between relatedness and the sharing of either home ranges or core areas. However, some females that shared space were not close relatives, and some closely related males shared space. House sharing was exhibited both by close relatives and by distantly related or unrelated woodrats, and was not correlated with relatedness. The kin structuring we describe likely resulted from a pattern of female philopatry and male dispersal, but also may have resulted from kin-directed behaviors by females.
Research on Mechatronic CAD / CAE Integration of Magnetic Levitation Precision Positioning Table

Modern manufacturing technology is moving towards high speed, precision and modularity, which is largely due to the continuous development of positioning platforms. Magnetic levitation technology can completely eliminate Coulomb friction, and has outstanding advantages such as high speed and no wear. This has broad application prospects in the field of high-speed, high-precision positioning platforms. In the product design process, CAE simulation analysis of parts / components is an important means to ensure its performance requirements and improve its design quality. The first step of CAE analysis is to establish an analysis model of parts / components. However, the current CAE software is characterized by powerful analysis functions and weak modeling functions, while the CAD software is characterized by very powerful modeling functions. Therefore, research on CAD / CAE integration of product parts / components has significant significance for improving its analysis efficiency and analysis accuracy. Based on this, this research used SolidWorks and ANSYS as software platforms, developed corresponding integrated systems. The mechanical and electrical performances of the magnetic levitation precision positioning table were also studied with examples.
Microgrid Protection Strategy Based on the Autocorrelation of Current Envelopes Using the Squaring and Low-Pass Filtering Method

To resolve the protection issues caused by high penetration of distributed energy resources, this paper proposes an efficient protection scheme for microgrids based on the autocorrelation of three-phase current envelopes. The proposed strategy uses a squaring and low-pass filtering approach for evaluating the envelope of the current signal. Then, the variance of the autocorrelation function is used to extract the hidden information of the distorted envelope to detect the fault signatures in the microgrid. Furthermore, the reactive power is used for determining the fault direction. The performance of the proposed protection scheme was verified on a standard medium-voltage microgrid by performing simulations in the MATLAB/Simulink environment (Version: R2017b). The proposed scheme was shown to be easy to implement and have good performance under looped and radial configuration for both grid-connected and islanded operation modes. The simulation results showed that the scheme could not only detect, locate, classify, and isolate various types of short-circuit faults effectively but also provide backup protection in case of primary protection failure.
Threatened species on the menu? Towards sustainable seafood use in zoos and aquariums

All zoos and aquariums use seafood to a greater or lesser extent, served in restaurants and cafes, and as an important component of animal feed. The majority of their millions of visitors are also seafood consumers. The sustainability of seafood supplies is of major concern: almost 70% of ocean fisheries are either fully exploited or overfished. Approximately 95% of the world's marine production depends on coastal ecosystems, such as estuaries, salt marshes, shallow bays and wetlands, mangroves, coral reefs and sea-grass beds, which are vulnerable to destructive fishing practices. Food webs have also been severely disrupted. However, fishing is still central to the livelihood and food security of 200 million people, especially in the developing world, with one in five people dependent on fish as their primary source of protein. This paper outlines a number of sustainable seafood initiatives that have been developed by aquariums and conservation organizations. We encourage zoos and aquariums to evaluate their seafood usage, to use available information to inform and increase the sustainability of their consumption, and to encourage changes in the behaviour of their visitors as seafood consumers.
AMNN: Attention-Based Multimodal Neural Network Model for Hashtag Recommendation

In the real-world social networks, hashtags are widely applied for understanding the content of an individual microblog. However, users do not always take the initiative in attaching hashtags when posting a microblog so that much effort has been invested for automatically hashtag recommendation. As a new trend, users no longer only post texts but prefer to share with multimodal data, such as images. To deal with these situations, we propose an attention-based multimodal neural network model (AMNN) to learn the representations of multimodal microblogs and recommend relevant hashtags. In this article, we convert the hashtag recommendation task into a sequence generation problem. Then, we propose a hybrid neural network approach to extract the features of both texts and images and incorporate them into the sequence-to-sequence model for hashtag recommendation. Experimental results on the data set collected on Instagram and two public data sets demonstrate that the proposed method outperforms state-of-the-art methods. Our model achieves the best performance in three different metrics: precision, recall, and accuracy. The source code of this article can be obtained from “https://github.com/w5688414/AMNN. ”
“You Can’t Hide Your Lyin’ Eyes”: Investigating the Relationship Between Associative Learning, Cue Awareness, and Decision Performance in Detecting Lies

Although skilled cue utilization is presumed to result primarily from domain-specific experience, individual differences in learning are theorized to play a significant role. Using a single-group correlational design, this study tested whether individuals’ domain-general associative learning capacity was related to performance in a complex real-world decision task presumed to rely heavily on cues: lie detection. A total of 21 participants completed an associative learning task in the form of a Space Invaders-like game. In the game, those who learn the cues are able to respond faster to the appearance of an enemy ship. Participants were also surveyed on their awareness of cues in the game. This was followed by a lie detection task. It was hypothesized that greater associative learning would be associated with greater awareness of cues in the learning task, and subsequently, superior accuracy in the lie detection task. Participants’ associative learning was correlated with their cue awareness (r pb = .782, p < .001). Further, learning was associated with better performance in the lie detection task (r = .544, p = .011); however, accuracy was found to be unrelated to the types of cues reportedly used during detection. These findings have implications for our understanding of cue acquisition and expertise development.
BrePartition: Optimized High-Dimensional kNN Search With Bregman Distances

Bregman distances (also known as Bregman divergences) are widely used in machine learning, speech recognition and signal processing, and kNN searches with Bregman distances have become increasingly important with the rapid advances of multimedia applications. Data in multimedia applications such as images and videos are commonly transformed into space of hundreds of dimensions. Such high-dimensional space has posed significant challenges for existing kNN search algorithms with Bregman distances, which could only handle data of medium dimensionality (typically less than 100). This paper addresses the urgent problem of high-dimensional kNN search with Bregman distances. We propose a novel partition-filter-refinement framework. Specifically, we propose an optimized dimensionality partitioning scheme to solve several non-trivial issues. First, an effective bound from each partitioned subspace to obtain exact kNN results is derived. Second, we conduct an in-depth analysis of the optimized number of partitions and devise an effective strategy for partitioning. Third, we design an efficient integrated index structure for all the subspaces together to accelerate the search processing. Moreover, we extend our exact solution to an approximate version by a trade-off between the accuracy and efficiency. Experimental results on four real-world datasets and two synthetic datasets show the clear advantage of our method in comparison to state-of-the-art algorithms.
Do endotoxin aggregates intercalate into phospholipid membranes in a nonspecific, hydrophobic manner?

The interaction of endotoxin aggregates with phospholipid liposomes of different composition was investigated applying fluorescence polarization spectroscopy with the fluorophore diphenylhexatriene and the resonance energy transfer technique using N-(7-nitro-2,1,3-benzoxadiazol-4-yl)-PE and N-(Rhodamine B sulfonyl)-PE. Fluorescence polarization data at constant temperature could be interpreted in favor of an intercalation of lipopolysaccharide into phospholipid liposomes even in the absence of Ca2+. Intercalation, however, could be clearly excluded from determinations performed as a function of temperature. Experiments employing the resonance energy transfer technique clearly showed that a nonspecific, hydrophobic intercalation of endotoxin aggregates into phospholipid liposomes only takes place in the presence of excess molar concentrations of divalent cations and/or after long-term incubation at elevated temperature (37°C). These findings indicate that under (near) physiological conditions nonspecific intercalation of aggregated lipopolysaccharide into phospholipid membranes represents an unlikely event. The significance of these results for an understanding of the fundamental mechanisms of cell activation by endotoxin is discussed.
Multisensorial Generative and Descriptive Self-Awareness Models for Autonomous Systems

In a computational context, self-awareness (SA) is a capability of an autonomous system to describe the acquired experience about itself and its surrounding environment with appropriate models and correlate them incrementally with the currently perceived situation to expand its knowledge continuously. This article introduces a bio-inspired framework for generative and descriptive dynamic models that support SA computationally and efficiently. Generative models facilitate predicting future states, while descriptive models enable the selection of the representation that best fits the current observation. Our framework is founded on the analysis and extension of three bio-inspired theories that have studied SA from different viewpoints, and we demonstrate how probabilistic techniques, such as cognitive dynamic Bayesian networks and generalized filtering paradigms, can learn appropriate models from multidimensional proprioceptive and exteroceptive signals acquired by the autonomous system. We discuss essential capabilities for SA and show how our modeling framework supports these capabilities in theory and through a case study where a mobile robot uses multisensorial data to determine its internal and environmental state as well as distinguishing among normal and abnormal behaviors.
Chitosan Oligosaccharide Addition to Buddhist Pine (Podocarpus macrophyllus (Thunb) Sweet) under Drought: Reponses in Ecophysiology and δ13C Abundance

Climate warming induces the necessity to increase the drought resistance of shade-obligate juvenile trees in sub-tropical forests. Chitosan oligosaccharide (COS) is a biopolymer derived from the marine resource that has attracted accumulative attention to induce and promote a plant’s resistance to abiotic stress. Buddhist pine (Podocarpus mascrophyllus (Thunb)Sweet) seedlings were cultured as the model material whose natural distribution in sub-tropical areas of China has suffered severe summer drought events in the last 113 years. A split-block design was conducted with a simulated drought event (drought vs. irrigated control), the COS addition, and two samplings at the ends of drought and re-watered treatments. The COS addition increased the resistance to drought by inducing a starch allocation towards roots where δ13C abundance and antioxidant enzyme activities were upregulated. The COS addition can promote biomass allocation to roots and increase the number of new roots. The COS addition to drought-treated Buddhist pine seedlings resulted in robust diameter growth. Therefore, COS is an available polymer to promote the resistance of Buddhist pine to drought. More work is suggested to clarify the dose of COS addition that can induce a prominent response of biomass accumulation and carbohydrate metabolism.
ANALÝZA A NÁVRH VIDEO ANALYTICKÉHO NÁSTROJA PRE MONITOROVANIE NEŠTANDARDNÉHO SPRÁVANIA

Modern video analytics tools focus on automatic evaluation of activities in the scene. In the area of automatic detection of video surveillance systems, there are several tools that deal with the detection of non-standard behaviour. The system design is based on real-time detection of non-standard behaviour of individuals or groups of people using video analysis from security cameras. The aim of proposal is to develop a system that will be able to identify the three most common non-standard activities such as public property damage, personal injury and persecution. It is necessary to collect data and create annotated databases for training and testing of deep learning models of neural networks. The contribution describes the advantages of the solution. Currently, the proposed solution is in the process of assessing the research project for funding in the Slovak Research and Development Agency.
Acid whey treatment and conversion to single cell protein via aerobic yeast activated sludge

In this study, a synthetic acid whey was made to mimic acid whey produced during cheese manufacture. A mixed yeast culture, primarily Vanrija albida, was used to degrade the wastewater and produce a single cell protein (SCP). The system was operated in batch mode at high and low loading rates. The COD-use efficiency of the biomass was 93 and 85% at the high and low loading rates, respectively. The pH was maintained at 3.5 to prevent bacterial contamination of the system. High loading and high oxygen transfer efficiency indicate that a full-scale yeast system would probably offer significant cost savings over both aerobic and anaerobic bacterial systems. The biomass produced has the potential to be a valuable commodity. The biomass amino acid profile was good with respect to the FAO protein nutrition guidelines for various farmed livestock species.
Configuring perceived fit to mitigate consumer animosity in the context of cross-border sport sponsorships

ABSTRACT Research question: While cross-border sport sponsorships are widespread, such partnerships introduce a notable complication – consumers in one country may dislike the sponsor’s country of origin (COO). This raises the question as to whether animosity towards a sponsor’s COO negatively affects sponsorship outcomes, and if so, how it can be addressed. For the latter, we examine holistic sponsor-object fit as well as a set of its constituent elements. Research methods: Data collection pertained to a brand engaged in a hypothetical sponsorship. Study 1 involves a Serbian brand sponsoring the Croatia national football team and for Study 2 German sponsors of the England national football team. Survey data are analyzed using a latent modeling approach. Results and findings: Study 1 shows that animosity reduces consumers’ attitude towards the sponsorship. However, higher perceived sponsor-object fit weakens this effect. Study 2 replicates this finding, and on a more granular level establishes the moderating properties of several sub-dimensions of fit. Congruence in color, personality and status ameliorate animosity. Implications: We outline implications for sponsors operating in environments where their COO invokes animosity and how sponsor-object fit may mitigate this.
The use of in vivo zebrafish assays in drug toxicity screening

Anecdotal evidence has long suggested that zebrafish may be a good model to predict toxicity of human drugs. As summarized in this review, several groups have recently conducted systematic evaluations of zebrafish toxicity end points using large numbers of pharmacologically relevant compounds. Assays of particular interest include those for cardiotoxicity, ototoxicity, seizure liability, developmental toxicity and gastrointestinal motility. Results suggest that zebrafish assays can attain an acceptable level of predictivity, ranging from “sufficient” (65 – 75% predictivity) to “good” (75 – 85% predictivity) based on guidelines established for novel in vitro tests by the European Centre for the Validation of Alternative Methods. Further validation will probably be required to definitely establish zebrafish as a standard model for toxicity testing.
An Induction Machine Design With Parameter Optimization for a 120-kW Electric Vehicle

Electric traction machines have been applied to both industrial variable-speed applications and electric vehicles. The induction machine (IM) is a potential candidate for traction machines due to the established industrial base. However, most of the existing studies on traction IM design rely on optimization algorithms or iterative calculation programs that subsequently give no clear understanding of the design requirements for field-weakening or extended speed operation. Hence, published procedures to guide IM design for traction applications are somewhat ad hoc to date. This article identifies the key IM design parameters required to achieve a traction characteristic within power supply constraints. As an example, a 120-kW electric vehicle traction machine is studied as a benchmark machine and then the proposed design procedure is employed to redesign the machine to improve its extended speed performance. Improvements in terms of efficiency and field-weakening capability are presented. The experimental results from the benchmark machine are used for validation of the subsequent simulation studies reported in this article. Finally, the identified parameters are shown to be similar with brushless permanent magnet machines. Thus, a generalized machine design philosophy can be concluded.