Miracle-dz/UniFAR-FTUs huggingface dataset:
Authenticity and exclusivity appeals in luxury advertising: the role of promotion and prevention pride

Purpose:This study aims to investigate how the effectiveness of luxury advertising can be improved by matching the emotional (promotion pride vs prevention pride) and luxury value (authenticity vs exclusivity) appeals within advertising messages.Design/methodology/approach:Three experiments were conducted. Studies 1A and 1B establish the influence of incidental emotions and regulatory focus on consumer preferences for divergent luxury value appeals (exclusivity vs authenticity) within advertisements. Study 2 shows the match-up effects of congruent emotional and luxury value appeals on advertising effectiveness.Findings:The authors offer causal evidence that promotion pride increases the preference for exclusivity appeals, whereas prevention pride increases the preference for authenticity appeals in luxury advertising.Research limitations/implications:The study offers a novel perspective into the ways consumers evaluate different value appeals in luxury advertising and establishes the important role played by emotions within such evaluations.Practical implications:Marketers of luxury products can increase the effectiveness of their advertising campaigns by considering the fit between emotional and luxury value appeals. Specifically, the authors show that the congruent matching of promotion pride with exclusivity appeals and of prevention pride with authenticity appeals within advertising messages can elicit more favorable consumer responses.Originality/value:The study is the first to illustrate novel "match-up" effects: it shows when and how different luxury value appeals (exclusivity vs authenticity) and emotions (promotion pride vs prevention pride) influence the effectiveness of luxury advertising.
Defect detection in additive manufacturing via a toolpath overlaid melt-pool-temperature tomography

Additive manufacturing of metals has emerged as a potential technology for companies to create highly integrated and individualized products. In particular, powder-based laser metal deposition has advantages such as flexibility and multimaterial capabilities. It is possible to mix powders and create alloys inside the melt-pool during the build process. Consequently, purpose made material combinations with set or even varying thermal properties can be realized. Inherently, the process becomes increasingly challenging because of the great number of variables. Analyzation of the manufactured part ensures top quality and detects errors and defects. To accomplish this, specimens have to be x-rayed or ground and cut into microsections. In order to save time and keep the parts’ integrity, a new method uses temperature data from the process to determine irregularities. During the additive manufacturing process, a 680 W diode laser melts the substrate and the powder locally. The powder is composed of 42% nickel and 58% iron. A pyrometer samples the temperature of the molten pool at a spectral range from 1.45 to 1.85 μm. The recorded data are mapped onto the toolpath of the process head. A script converts the time dependent signal to spatially resolved temperature points. The feedrate and the laser status aid to synchronize the data throughout. As a result, the overlaid melt-pool temperature visualizes the process and creates a tomography for the produced part. Initial experiments show that errors and defects like porosities and cavities are identifiable inside the manufactured structure. Furthermore, correlations between the visualization and errors detected with microsections are possible. Overall, this technique is an addition to the repertoire of data visualization and quality control in additive manufacturing and can be transferred to other machines and laser processes.
Effects of nectar robbing on nectar dynamics and bumblebee foraging strategies in Linaria vulgaris (Scrophulariaceae)

Differences in morphology among bumblebee species sharing a nectar resource may lead to variation in foraging behaviour and efficiency. Less efficient bumblebees might opportunistically switch foraging strategies from legitimate visitation to secondary robbing when hole-biting primary robbers are present. We observed various aspects of pollination and nectar robbing ecology of Linaria vulgaris in the Colorado Rocky Mountains, with emphasis on the role of bumblebee proboscis length. Bees can extract nectar from a nectar spur legitimately, by entering the front of the flower, or illegitimately, by biting or reusing holes in the spur. Although L. vulgaris flowers are apparently adapted for pollination by long-tongued bees, short-tongued bees visited them legitimately for trace amounts of nectar but switched to secondary robbing in the presence of primary robbers. Longer-tongued bees removed more nectar in less time than did shorter-tongued bees, and were less likely to switch to secondary robbing even when ∼100% of flowers had been pierced. As the proportion of robbed flowers in the population increased, the relative number of legitimate visits decreased while the relative number of robbing visits increased. Robbing decreased nectar standing crop and increased the proportion of empty flowers per inflorescence. Despite these potentially detrimental effects of robbers, differences in inflorescence use among robbers and pollinators, and the placement of holes made by primary robbers, may mitigate negative effects of nectar robbing in L. vulgaris. We discuss some of the reasons that L. vulgaris pollination ecology and growth form might temper the potentially negative effect of nectar robbing.
Characterization of a cDNA Encoding a Novel Subunit for Cytochrome c Oxidase (COX6b) from Rice

To date, there have been only a limited number of reports about the nuclear-encoded subunit for cytochrome c oxidase (COX) in the mitochondria of higher plants. In the present study, we characterized a cDNA encoding a novel subunit of COX (COX6b), which had not previously been reported in plants. It was found that the rice COX6b gene encodes 169 amino acids with a calculated molecular mass of 19 kDa. The deduced amino acid sequence of rice COX6b is longer than those of vertebrate and yeast COX6b subunits. Genomic Southern hybridization suggested that the rice COX6b subunit is encoded by at least two copies of COX6b genes. Northern hybridization showed that one of the genes (COX6b-1) is constitutively transcribed in different organs of rice. However, the steady-state mRNA levels slightly varied among organs.
Synthesis and biological evaluation of novel shikonin ester derivatives as potential anti-cancer agents

Shikonin has previously been reported to function as a potent anti-cancer drug that induces cell apoptosis via diverse pathways. To optimize the effectiveness of its pro-apoptotic functions, shikonin was chosen as the best compound for obtaining shikonin ester derivatives (3a–3n) because it possesses an ester group on the side chain hydroxyl position, and the biological activity was evaluated as a potent anti-proliferating inhibitor for many cancer cell lines. Among these compounds, compound 3j exhibited better anti-cancer activities against human hepatocellular carcinoma cell line (HepG2) with an IC50 value of 0.759 μM which was better than that of shikonin which was 1.288 μM. The flow cytometry results showed that compound 3j inhibited the cell growth and caused the cell cycle to be arrested at the G2/M phase. Meanwhile, obvious apoptosis induced by 3j was observed using the Annexin V combined with propidium iodide assay, showing that 3j induced apoptosis of HepG2 cells in a dose and time dependent manner. To investigate the underlying mechanism in the process of apoptosis induced by 3j, the western blot technique was used and the cleavage of caspase-9 was observed but not that of caspase-8. Furthermore, the elevated expression of the p53 protein was positively correlated with the decreased Bcl-2 protein levels and increased Bax protein and the cytochrome C levels. This indicated that the mitochondrial apoptosis pathway directed by p53 responded in the process of apoptosis was induced by 3j. Based on these data, we conclude that compound 3j has the best anti-proliferating and pro-apoptotic effect among the 14 newly synthesized compounds, and it could be a potent candidate for cancer therapy.
Financial Conditions Index and Economic Performance in Nigeria

The main aim of this study is to construct a financial conditions index for Nigeria and analyze its predictive power for future growth rate and inflationary trend. The study is based on yearly time series data from 1985 to 2018. The variables included in the construction of the index are riskless interest rate, stock market index, exchange rate, credit to private sector and interest rate spread. The weights attached to these variables are derived from ARDL coefficients, while the predictive power of the constructed index is examined within the VAR framework. The results from the ARDL model shows that credit to private sector and stock market index are the most significant factors for nominal GDP, hence having a substantial weight in the resultant financial conditions index. However, the results from VAR impulse response function and forecast error variance decomposition suggest that the constructed financial conditions index contain very little predictive information about future growth rate and inflationary trend.
Authentication Scheme Based On Blow Fish Cryptography In Categorized Sensor Networks

In categorized sensor network deployment, many applications uses different sensor nodes and communicate with sensor nodes. In WSN peer-to-peer sensor network consists of hundreds to several thousand sensor nodes connect locally with neighboring nodes and send data over the network. However, sensor networks meet challenges to provide security using Symmetric public key cryptosystem. Sensor networks are also vulnerable to several node attacks by an adversary. For this reason, message authentication schemes are required to prevent such node attacks from an attacker. This paper focuses on scalable Message authentication scheme, it is proposed based on Blue Fish Cryptography (BFC). The message authentication scheme proposed also provides source assurance of security.
Effects of different footwear on kinetics, kinematics and muscle forces during the barbell back squat; an exploration using Bayesian modelling

Abstract The current study aimed to explore the effects of different footwear on kinetics, kinematics and muscle forces during the barbell back squat in both male and female lifters using Bayesian modelling. Twelve male and twelve female lifters completed squats at 70% of their 1 repetition maximum, in four different footwear conditions (Adidas weightlifting shoe, Inov-8 weightlifting shoe, Cross-fit and minimal footwear). Three-dimensional kinematics were measured using an eight-camera motion analysis system, ground reaction forces using a force platform and muscle/joint forces using musculoskeletal modelling techniques. Differences between footwear were examined using Bayesian 4 (FOOTWEAR) * 2 (GENDER) mixed ANOVA’s. Peak quadriceps force was greater in the Adidas (male = 89.78/female = 70.56 N/kg), Cross-fit (male = 92.41/female = 70.82 N/kg) and Inov-8 (male = 91.57/female = 68.21 N/kg) conditions compared to minimal footwear (male = 82.61/female = 64.40 N/kg). In addition, peak patellofemoral stress and patellar tendon forces were greater in the Adidas (patellar tendon force: male = 64.67/female = 42.89 N/kg & patellofemoral stress: male = 143.21/female = 118.92 KPa/kg), Cross-fit (patellar tendon force: male = 67.89/female = 43.52 N/kg & patellofemoral stress: male = 146.02/female = 114.73 KPa/kg) and Inov-8 (patellar tendon force: male = 64.08/female = 41.04 N/kg & patellofemoral stress: male = 193.09/female = 169.09 KPa/kg) conditions compared to minimal footwear (patellar tendon force: male = 56.75/female = 39.92 N/kg & patellofemoral stress: male = 134.06/female = 108.91 KPa/kg). Finally, angular ROM was greater in the minimal footwear (male = 28.04/female = 33.75°) compared to the Adidas (male = 26.85/female = 30.73°) and Inov-8 (male = 26.92/female = 32.63°) conditions. The findings from the current investigation therefore indicate that weightlifting footwear may be able to enhance lower extremity muscle development and improve squat biomechanics owing to a reduced trunk angular ROM; however, this is likely to be at the expense of increased knee joint loading.
Using model organisms in an undergraduate laboratory to link genotype, phenotype, and the environment

We developed laboratory exercises using zebrafish (Danio rerio) and nematodes (Caenorhabditis elegans) for a sophomore-level Integrative Biology Laboratory course. Students examined live wildtype zebrafish at different stages of development and noted shifts occurring in response to fgf8a deficiency. Students were introduced to development in other fish species to demonstrate how variation in developmental systems affects phenotype. Finally, students cultured glp-1(bn18ts) C. elegans mutants under different conditions to illustrate how the environment and genetics act concurrently to modulate development. Undergraduate students responded positively to both the fish and C. elegans laboratory modules. These novel laboratory exercises are intended to promote an integrative view of biology and to help prepare undergraduate students for independent research with faculty.
Phylogeny and systematics of the ectemnorhinus-group of genera (Insecta: Coleóptera)

Adult and larval characters place the monophyletic Ectemnorhinus-group of genera firmly within the former Adelognatha and new concept of Brachycerinae. The group, previously with tribal or subfamily status, is most closely related to the genera Heterexis Broun and Oclandius Blanchard from the Auckland and Campbell Islands. A cladistic analysis of the genera based on 35 adult and 11 larval characters, resulted in the following six genera being recognised: Christensenia Brinck, Canonopsis C. O. Waterhouse, Disker Dreux & Voisin, Palirhoeus Kuschel, Bothrometopus Jeannel and Ectemnorhinus G. R. Waterhouse. Ectemnorhinus angusticollis (C. O. Waterhouse) is transferred to Bothrometopus, Mesembriorrhinus parvulus Jeannel, also transferred to Bothrometopus, is reinstated to species level. Ectemnorhinus curtus Jeannel is placed in synonymy with Ectemnorhinus fuscus Enderlein, which is removed from synonymy with Ectemnorhinus viridis G. R. Waterhouse and reinstated as valid. Ectemnorhinus hibernantium (Dreux & Voisin) is placed in synonymy with E. geniculatus Jeannel.
From Cuba to most of the neotropic: habenaria bicornis (orchidaceae) is widespread from Mexico to southeastern Brazil

Habenaria bicornis fue descrita por primera vez en 1835, para Cuba, y era conocida apenas para este pais y unos pocos registros de Panama, de 1920. En el presente estudio, demostramos que H. bicornis y H. goyazensis, esta ultima conocida para Brasil y Guiana, son especificas y la especie se distribuye desde Mexico hasta el sudeste de Brasil. El modelado de nicho y la recoleccion de datos indican que esta especie posee una preferencia por sabanas humedas de tierras bajas y es predicho que su distribucion incluye gran parte del Neotropico con habitats favorables. Los analisis filogeneticos moleculares con secuencias del ADN nuclear (ITS) y plastidial (matK) ubicaron H. bicornis en una posicion aislada proximo a la base del clado Neotropical, aunque con bajo soporte. En terminos de su morfologia, sus relaciones no estan aclaradas, ya que no hay similitudes evidentes entre H. bicornis y los subclados basales o cualquier otro subclado Neotropical. Los analisis citogeneticos indican un numero cromosomico basico de x=21, similar a las otras especies basales del Neotropico
An Institutional Approach to Digitalization in Sustainability-Oriented Infrastructure Projects: The Limits of the Building Information Model

The transport sector accounts for a large share of global Co2 emissions. To mitigate the impact of climate change, several sustainability-oriented large-scale infrastructure projects such as electric road systems and expanding rail systems have recently been on the policy agenda. A parallel development that is expected to accelerate the transition of the transport sector is digitalization, which, although ongoing for many decades, has recently been augmented by concepts such as artificial intelligence (AI) and smart city technologies. The integration of these digitalization tools at the organizational level poses not only opportunities but also some challenges for the actors involved in infrastructure projects. An approach that is currently promoted in the infrastructure sector is the Building Information Model (BIM), which is a decision-making instrument that leverages various digitalization tools and applications. However, although the economic implications of BIM are widely discussed in the literature, the (inter-) organizational dynamics involving multiple actors in infrastructure projects are not fully grasped. Large infrastructure projects are sociotechnical endeavors embedded in complex institutional frames; hence the institutional norms, practices and logics in them are significant. Responding to this, this paper adopted an institutional analysis and put the BIM approach in the (inter-) organizational context in infrastructure delivery. Drawing on empirical data from three organizations in infrastructure delivery in Spain, this paper analyzed the tensions among actors during BIM adoption and implementation.
Estimation of fecundity in barramundi, Lates calcarifer (Bloch), using an automatic particle counter

The use of a particle-size analyser for determining the fecundity of barramundi, L. calcarifer, is described. Fecundity was determined on 29 fish, 480-1 350 mm total length. The relationship between fecundity (F × 106) and length (L, mm) was exponential, F = 0.3089 e0.0035L. Fecundity in large fish was variable with the highest estimate being 46 × 106 eggs in a fish of 1240 mm length.
Decision Support Methodology Based on Covering-Based Interval-Valued Pythagorean Fuzzy Rough Set Model and Its Application to Hospital Open-Source EHRs System Selection

The target of current work is to propose a new approach to deal with multiattribute decision-making (MADM) problems with interval-valued Pythagorean fuzzy set (IVPFS) based on the concepts of covering-based rough set (CRS) and TOPSIS and give its application in MADM problems. To begin with, we integrate the fuzzy rough set (FRS), IVPFS and CRS and define the covering-based interval-valued Pythagorean fuzzy rough set (CIVPFRS). Firstly, the relative notions of the CIVPFRS model are introduced. In addition, the distance measure of interval-valued Pythagorean fuzzy numbers (IVPFNs) is defined; based on the proposed distance, the rough and precision degrees of CIVPFRS are discussed. Thirdly, on the basis of the theoretical analysis for CIVPFRS models, an interval-valued Pythagorean fuzzy TOPSIS method is designed to deal with the MADM problems with interval-valued Pythagorean fuzzy information (IVPFI). Last of all, the validity and merits of the proposed approach are illustrated by an example, and the sensitivity analysis of the parameters and the comparison with the existing related methods are carried out. β
Hurricane Wind and Storm Surge Effects on Coastal Bridges under a Changing Climate

Hurricanes and their cascading hazards have been responsible for widespread damage to life and property, and are the largest contributor to insured annual losses in coastal areas of the U.S.A. Such losses are expected to increase because of changing climate and growing coastal population density. An effective methodology to assess hurricane wind and surge hazard risks to coastal bridges under changing climate conditions is proposed. The influence of climate change scenarios on hurricane intensity and frequency is explored. A framework that couples the hurricane tracking model (consisting of genesis, track, and intensity) with a height-resolving analytical wind model and a newly developed machine learning-based surge model is used for risk assessment. The proposed methodology is applied to a coastal bridge to obtain its traffic closure rate resulting from the observed (historical) and future (projected) hurricane winds and storm surges, demonstrating the effects of changing climate on the civil infrastructure in a hurricane-prone region.
Current Control of the Coupled-Inductor Buck–Boost DC–DC Switching Converter Using a Model Predictive Control Approach

Coupled-inductor buck–boost dc–dc switching converter has emerged as an alternative to manage power in several hybrid system architectures. This is due to features such as a noninverting voltage step-up and step-down characteristic, high efficiency, wide bandwidth, and the possibility to regulate its input or output currents as has been reported in previous works. All of them are based on a small-signal linearized model around an operating point. In this article, a model predictive control strategy is proposed to increase the operation point domain. The proposal consists in the use of the mathematical model of the system in discrete time to obtain the optimal switching state to be applied in the converter based on a cost function optimization, which simultaneously improves the current tracking and reduces the converter power losses. Experimental results validate the proposal demonstrating that this is a good alternative for the control of this kind of power converters.
Hybrid Conditional Random Fields and K-Means for Named Entity Recognition on Indonesian News Documents

: The hybrid approach has been widely used in several Natural Language Processing, including Named Entity Recognition (NER). This research proposes a NER system for Indonesian News Documents using Hybrid Conditional Random Fields (CRF) and K-Means. The hybrid approach is to try incorporating word embedding as a cluster from K-Means and take as a feature in CRF. Word embedding is a word representation technique, and it can capture the semantic meaning of the words. The clustering result from K-Means shows that similar meaning word is grouped in the cluster. We believe this feature can improve the performance of the baseline model by adding the semantic relatedness of the word from the cluster features. Word embedding in this research uses Indonesian Word2Vec. The dataset is consisting of 51,241 entities from Indonesian Online News. We conducted some experiments by dividing the corpus into training and testing dataset using percentage splitting. We used 4 scenarios for our experiments, which are 60-40, 70-30, 80-20, and 90-10. The best performance for our model was achieved in 60-40 scenario with F1-Score around 87.18% and also improves about 5.01% compared to the baseline models. We also compare our proposed methods with several models, which are BILSTM and BILSTM-CRF, from previous research. The experiments show that our model can achieve better performance by giving the best improvement of around 4.3%.