Miracle-dz/UniFAR-FTUs huggingface dataset:
Perceived impacts of tourism in the Arctic

ABSTRACT This research delineates the perceptions of tourism in the Arctic. It deploys a qualitative study to disentangle the complicity of perceived impacts amongst three types of tourism stakeholders: (1) residents, (2) tourists, and (3) tourism professionals working in hotels, tour operations, restaurants, tourist information centers, and tourism planning agencies within the study region. This study transpires in Finnmark, which is one of the most visited Arctic destinations. Sixty-eight personal interviews are conducted in six towns and cruise ships sailing through the study region. Consequently, the study presents six thematic views entailing (1) monetary contribution, (2) cultural proliferation, (3) community vitality, (4) personal enhancement, (5) environmental degradation, and (6) social disturbance surface as the perceived impacts of tourism among the stakeholders. Unlike most impact studies in the existing literature, this research shows that monetary contribution is not necessarily the key perceived benefit of tourism. Instead, social factors, such as achieving a vibrant community life, could also be a valuable contribution of tourism in the case of this region in northern Norway. Lastly, discussions from theoretical and practice perspectives are rendered along with suggestions for future research.
Efectos de los niveles de nitrógeno ureico en la síntesis proteica durante la fermentación de mezclas de caña (Saccharum officinarum) y boniato (Ipomea batata Lam.)

Para determinar el efecto del nivel de nitrogeno en la sintesis proteica de la microbiota se realizo un experimento segun diseno completamente aleatorizado en arreglo factorial (3 x 4) con 4 repeticiones. Los factores estuvieron dados por tres niveles de urea (0.5, 1 y 1.5 %) y por los tiempos de muestreo (0.48, 72 y 96 hr). Se observaron interacciones entre los niveles de urea y el tiempo de muestreo para NH3, pH, urea residual, PB y PV. El pH disminuyo (P 0.001) a las 48 hr y posteriormente ascendio de forma notable en aquellos con mayor nivel de nitrogeno, momento en que se redujeron los tenores de urea residual y se obtuvieron las mayores concentraciones de NH3 ( 8.50, 11.24 y 16.65 meq/litro para 0.5, 1 y 1.5 % y 96 hr de muestreo, respectivamente). Los acidos organicos encontrados fueron el lactico y acetico con valores que fluctuaron en el tiempo, independientemente del nivel de urea y representaron con respecto al total de acidos producidos 84 y 15%, respectivamente. La materia seca (MS) se redujo en el tiempo (11 unidades porcentuales) y fue ligeramente superior para 1.5% de urea (27.57 contra 26.82 y 26.17 con 0.5 y 1% de urea). El almidon se concentro desde 31.52 a 46.57 % al inicio y final de la fermentacion, sin diferencias estadisticas segun el tiempo de fermentacion. Los valores de proteina bruta (PB) ascendieron (P 0.001) a medida que se incremento el nivel de nitrogeno anadido y se mantuvo hasta las 72 hr. A partir de aqui, se produjo una reduccion de los valores. En la proteina verdadera (PV) no se observo efecto por el nivel de urea, pero si mostro un incremento a medida que transcurrio el tiempo a partir de las 48 hr. Se obtuvo una sintesis real de proteina (SRP) de 4.65, 6.44 y 5.62 unidades y una eficiencia de utilizacion del nitrogeno (EUN) de 77.8, 84 y 76.5 % para 0.5, 1 y 1.5 % de urea, respectivamente. Se concluye que en las fermentaciones de mezclas de cana y boniato en las condiciones estudiadas, se logro la mayor sintesis de proteina microbiana y la mejor eficiencia de utilizacion del nitrogeno a las 96 hr con la adicion de 1 % de urea.
FACTORES BIÓTICOS Y CONCENTRACIÓN DE ÁCIDO CARMÍNICO EN LA COCHINILLA (Dactylopius coccus COSTA) (HOMOPTERA: DACTYLOPIIDAE) Biotic factors and concentration of carminic acid in cochineal insects (Dactylopius coccus Costa) (Homoptera: Dactylopiidae)

A B S T R A C T The cochineal insect, Dactylopius coccus Costa (Homoptera: Dactylopiidae), grows on the pricklypear cactus, Opuntia ficus-indica (L.) Mill. (Cactaceae), and is exploited for its capacity to produce natural dyes based on carminic acid. Cochineal insects were introduced in Chile in 1989, and exports of dry cochineal began in 1994 and grew to cover approximately 15% of the world market. However, the current price of dry cochineal is nearing production costs; hence, it has become necessary to increase yields without increasing costs. This work reports on the effect of biotic factors on the concentration of carminic acid (CAC) in cochineal insects. CAC was positively affected by the density of cochineal insects around the insect, that was analyzed by plant age, and by the nutritional status of the plant, and was negatively affected by the age of the cladode. Additionally, CAC was significantly affected by season: 16.9% of dry weight in the Autumn and 19.1% in the Spring. This knowledge may be used in designing cultural strategies to increase carminic acid accumulation in cochineal insects.
Analysis of the Apartment Market in Behavioral Tax using PRMR and LRMR

This study analyzed the PRMR and LRMR of the apartment market. The data were collected from January 2006 to June 2014. The trade data of 360 apartments were used. Each data is analyzed for 60 days before and after the implementation date; Before 60 days means -60 days from the implementation to -1 day, and after 60 days means +1 day from the implementation to +60 days. These data shows a statistical significance, which is calculated through the statistical analysis. The result says that the permanent decrease in the acquisition tax rate increased the profit realization of the profit investors. And the apartment owner do not realize loss often because the apartments are used for a living place. In other words, it is considered that the implementation of other policy of tax increase except the third acquisition tax increase led investors’ cognitive bias to decrease that had been existed.
Remaining Useful Life Prediction Using a Novel Feature-Attention-Based End-to-End Approach

Deep learning plays an increasingly important role in industrial applications, such as the remaining useful life (RUL) prediction of machines. However, when dealing with multifeature data, most deep learning approaches do not have effective mechanisms to weigh the input features adaptively. In this article, a novel feature-attention-based end-to-end approach is proposed for RUL prediction. First, the proposed feature-attention mechanism is directly applied to the input data, which gives greater attention weights to more important features dynamically in the training process. This helps the model focus more on those critical inputs, and the prediction performance is therefore improved. Next, bidirectional gated recurrent units (BGRU) are used to extract long-term dependencies from the weighted input data, and convolutional neural networks are employed to capture local features from the output sequences of BGRU. Finally, fully connected networks are used to learn the above-mentioned abstract representations to predict the RUL. The proposed approach is validated in a case study of turbofan engines. The experimental results demonstrate that the proposed approach outperforms other latest existing approaches.
Three-dimensional Image Sensor with MPPC for Flash LIDAR

Three-dimensional (3D) image sensors have many applications, including enabling autonomous vehicles to avoid obstacles and providing guidance, navigation, and control for spacecraft immediately before landing on a celestial body. Flash LIDAR is a system that can acquire a 3D image by emitting a diffuse pulsed laser beam, and hence is suitable for both obstacle detection and terrain measurement. In the 3D image sensors used for Flash LIDAR, a photosensor array and time measurement integrated circuit are vertically bonded. Here, we report the results of a detailed evaluation of the principles, functions, sensitivity, and time measurement accuracy of a prototype 1-k pixel (32 © 32 pixels) 3D image sensor based on a multi-pixel photon counting avalanche photodiode. By counting photons, a 3D image sensor is realized that has both high sensitivity and the ability to measure light intensity.
Effect of remote ischaemic preconditioning on walking in people with multiple sclerosis: double-blind randomised controlled trial

Background Remote ischaemic preconditioning (RIPC) is the exposure of body parts to brief periods of circulatory occlusion and reperfusion. Recent studies have also shown that RIPC can improve exercise performance in healthy individuals. Objective This study aimed to assess the effect of RIPC on walking in people with multiple sclerosis (MS). Methods This was a double-blind randomised controlled clinical trial. We used three cycles of RIPC delivered by occluding the upper arm with a blood pressure (BP) cuff inflated to a pressure of 30 mm Hg above the systolic BP. In patients in the sham intervention group, the BP cuff was inflated only to 30 mm Hg below diastolic BP. Outcome measures included the Six-Minute Walk Test (6MWT), gait speed, the Borg rate of perceived exertion (RPE) scale, the tolerability of the RIPC using a Numerical Rating Scale for discomfort from 0 to 10, and adverse events. We identified responders meeting the minimal clinically important difference (MCID) established in the literature in each group. Results Seventy-five participants completed the study (RIPC: 38 and Sham: 37). The distance walked during the 6MWT improved by 1.9% in the sham group and 5.7% in the RIPC group (p=0.012). The number of responders meeting MCID criteria in the RIPC group was significantly greater compared with the sham intervention group. No serious adverse events occurred. Conclusion Single cycle of RIPC resulted in immediate improvement in walking distances during 6MWT in people with MS. Trial registration numbers NCT03153553
Mycobacterium tuberculosis Surface-binding Antibodies Influence Early Infection Events

Mycobacterium tuberculosis Surface‐Binding Antibodies Influence Early Infection Events Casey Perley Department of Molecular Genetics and Microbiology Duke University Date:_______________________ Approved: ___________________________ Richard Frothingham, Supervisor ___________________________ Jörn Coers ___________________________ Jen‐Tsan Ashley Chi ___________________________ Micah Luftig ___________________________ Gregory Taylor An abstract of a dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Molecular Genetics and Microbiology in the Graduate School of Duke University. 2015
PENGARUH GAYA BELAJAR VISUAL, AUDITORIAL, DAN KINESTETIK TERHADAP PRESTASI BELAJAR SISWA SMA DIAN ANDALAS PADANG

Penelitian ini bertujuan mendeskripsikan pengaruh gaya belajar visual, auditorial, dan kinestetik terhadap prestasi belajar siswa pada Jurusan IPA SMA Dian Andalas Padang. Pengumpulan data dilakukan dengan angket dan dokumentasi. Populasi berjumlah 135 orang dan sampel berjumlah 110 orang yang ditentukan dengan teknik proportionate stratisfied random sampling. Uji hipotesis dilakukan dengan analisis regresi linear berganda dan sederhana dengan taraf signifikansi 0,05. Hasil penelitian sebagai berikut. Pertama, terdapat pengaruh yang signifikan gaya belajar visual, auditorial dan kinestetik terhadap prestasi belajar. Kedua, terdapat pengaruh signifikan gaya belajar visual terhadap prestasi belajar. Ketiga, terdapat pengaruh yang signifikan gaya belajar auditorial terhadap prestasi belajar. Keempat, terdapat pengaruh yang signifikan gaya belajar kinestetik terhadap prestasi belajar. Kelima, hasil uji determinasi menunjukkan sumbangan relatif gaya belajar visual, auditorial, dan kinestetik terhadap prestasi belajar siswa sebesar 33,8%. Sumbangan relatif masing- masing terhadap prestasi belajar, yakni: gaya belajar visual 27,4%, gaya belajar auditorial 23,2%, dan gaya belajar kinestetik 27,2%.
Avirulence geneavrPpiAfromPseudomonas syringaepv.pisiis not required for full virulence on pea

Abstract The open reading frame encoding the avirulence gene avrPpiA1 , previously cloned from race 2 of Pseudomonas syringae pv. pisi , has been subcloned and shown to express peptides corresponding to all six possible start codons. The half-life of the peptides was found to be approximately 5 min in Escherichia coli . Transposon insertions which inactivate the gene in P. syringae pv. pisi were located both within the open reading frame and in the upstream regulatory sequence, the hrp -box. Homologues of the gene were present only in races 5 and 7, which expressed the avirulence phenotype. The gene was present on the chromosome in all race 2 isolates tested, but was plasmid-borne in the type strains of races 5 and 7. In contrast to the homologue avrRpm1 cloned from P. syringae pv. maculicola , marker-exchange mutagenesis of the gene in races 2 and 7 of P. syringae pv. pisi was not found to affect pathogenicity towards the susceptible host as indicated by symptom development or bacterial growth in the plant.
Pupal diapause induction in larvae destined for non-diapause of the flesh fly, Boettcherisca peregrina : Diptera : Sarcophagidae

The flesh fly adults of temperate colonies, Boettcherisca peregrinq lay larvae destined for non-diapause and diapause under long and short days, respectively and mature larvae destined for diapause enter diapause at the pupal stage, Mature larvae are inhibited pupariation with water immersion treatment, and the pupariation takes place after transfer from the immersed to the dry conditions. We found that 74% of the mature larvae entered diapause, when the larvae destined for non-diapause were treated with water immersion under short days at 20eC fbr 13 days. Funheg 609,6 of progeny of adult experienced diapause at pupal stage entered diapause with water immersion treatment under the same condition. Furthermore, when the progeny of diapause terminated adult fly experienced only short days was exposed only short days for all larval period, they entered diapause at a rate of 22-J23% with or without water immersion treatment. From these results, we conclude that diapause incidence on B. penegrina larvae may be dominated by short days signal exposed after larviposition, but adults have a same effect on progeny to diapause or non-diapause pupae.
Increased hunting effort buffers against vole scarcity in an urban Kestrel Falco tinnunculus population

Capsule In years with low vole abundance birds visited hunting grounds more frequently and for longer. Aims To describe diet composition, hunting behaviour, habitat choice and reproductive success of urban Kestrels during changing vole abundance. Methods For five years, we studied the hunting effort of Kestrels in a medium-sized city during the breeding season. Pitfall traps were used for determining vole abundance. Kestrel diet composition was determined from pellet analyses. The number of eggs and offspring was recorded during at least two consecutive visits for each nest and each breeding stage. Results In contrast to larger European cities, the Common Vole Microtus arvalis was a key part of the Kestrels' diet and did not fluctuate significantly according to vole availability. Reproductive success was quite high and stable throughout years with different vole abundance. In years of low vole abundance, the arrival frequency at hunting grounds and time spent there increased. During years with a low vole population, Kestrels had less hunting success and the rate of successful visits decreased. Therefore, Kestrels probably had to change hunting grounds more frequently. During low vole years Kestrels used less demanding techniques, e.g. perching, despite the lower success of these hunting techniques, to avoid extremely high energetic costs. Conclusions An increase in hunting helps to maintain a proper diet and consequently reproductive success. Vole abundance did not change dramatically during the study period, as reported by studies from western and northern Europe. The proportion of ruderal habitats on the city periphery is higher than in more monotonous farmland habitats. Ruderal habitats can be important when Kestrels look for mammals other than voles, especially during vole scarcity.
Carbon Flux Variability From a Relatively Simple Ecosystem Model With Assimilated Data Is Consistent With Terrestrial Biosphere Model Estimates

Modeling the net carbon balance is challenging due to the knowledge gaps in the variability and processes controlling gross carbon fluxes. Terrestrial carbon cycle modeling is susceptible to several sources of bias, including meteorological uncertainty, model structural uncertainty, and model parametric uncertainty. To determine the impact of these uncertainties, we compare three model‐derived representations of the global terrestrial carbon balance across 1997–2009: (1) observation‐constrained model‐data fusion (CARBon Data Model FraMEwork, CARDAMOM), (2) the reanalysis‐driven Trends in Net Land‐Atmosphere Carbon Exchange (TRENDY) land biosphere model ensemble, and (3) the Coupled Model Intercomparison Project 5 (CMIP5) Earth System Model ensemble. We consider the spread in carbon cycle simulations attributable primarily to parametric uncertainty (CARDAMOM), structural uncertainty (TRENDY), and combined structural and simulated meteorological uncertainty (CMIP5). We find that the spread across the CARDAMOM ensemble long‐term mean—produced by parameter uncertainty—is larger than the spread of TRENDY and CMIP5 for net biosphere exchange (NBE) but similar for gross primary productivity (GPP). The carbon flux dynamics of CARDAMOM compares to models in TRENDY as well as models in TRENDY compare to each other in many regions for NBE seasonal (nine of 12), NBE interannual (11 of 12), and GPP seasonal variability (7 of 12), although not for GPP interannual variability (2 of 12). The simple model structure of CARDAMOM and systematic assimilation of observations is sufficient to produce carbon dynamics within the range of more complex models. These results are encouraging for the use of model‐data fusion products with empirically estimated uncertainty for global carbon cycle studies.
Automated retinopathy of prematurity screening using deep neural network with attention mechanism

Retinopathy of prematurity (ROP) is an ocular disease which occurs in premature babies and is considered as one of the largest preventable causes of childhood blindness. However, insufficient ophthalmologists are qualified for ROP screening, especially in developing countries. Therefore, automated screening of ROP is particularly important. In this paper, we propose a new ROP screening network, in which pre-trained ResNet18 is taken as backbone and a proposed attention block named Complementary Residual Attention Block (CRAB) and Squeeze-and-Excitation (SE) block as channel attention module are introduced. Our main contributions are: (1) Demonstrating the 2D convolutional neural network model pre-trained on natural images can be fine-tuned for ROP screening. (2) Based on the pre-trained ResNet18, we propose an improved scheme combining which that effectively integrates attention mechanism for ROP screening. The proposed classification network was evaluated on 9794 fundus images from 650 subjects, in which 8351 are randomly selected as training set according to subjects and others are selected as testing set. The results showed that the performance of the proposed ROP screening network achieved 99.17% for accuracy, 98.65% for precision, 98.31% for recall, 98.48% for F1 score and 99.84% for AUC. The preliminary experimental results show the effectiveness of the proposed method.
Bifurcations and Chaos in Current-Driven Induction Motor

Abstract: In this paper, a model of PI-speed control current-driven induction motor based on indirect field oriented control (IFOC) is addressed. To assess the complex dynamics of a system, different dynamical properties, such as stability of equilibrium points, bifurcation diagrams, Lyapunov exponents spectrum, and phase portraits are characterized. It is found that the induction motor model exhibits chaotic behaviors when its parameters fall into a certain region. Small variations of PI parameters and load torque affect the dynamics and stability of this electric machine. A chaotic attractor has been observed and the speed of the motor oscillates chaotically. Numerical simulation results are validating the theoretical analysis.
‘I don’t want to go back into the closet just because I need care’: recognition of older LGBTQ adults in relation to future care needs

ABSTRACT There is increasing awareness in research about the social service needs of older LGBTQ adults. However, there are few studies that deal with differences in this community regarding elder care services. As a rule, transgender individuals are not included in these studies. This study focuses on how older Swedish LGBTQ adults reason about openness in an elder care context concerning their future needs for services and adopts Nancy Fraser’s theoretical framework of recognition. The material consists of fifteen semi-structured interviews with older LGBTQ adults. The results indicate that the main concern for older LGBTQ individuals is being accepted for their preferred sexual orientation and/or gender identity in elder care. However, there were differences regarding that concern in this LGBTQ group. There were also a variety of approaches in the group as to preferences for equal versus special treatment with respect to their LGBTQ identity. In addition, there were differences as to whether they prefer to live in LGBTQ housing or not. The findings contribute to existing knowledge by highlighting the diverse views on elder care services in both this group of interviewees and its subgroups. These findings emphasise the importance of the social work practice recognising different preferences and having an accepting approach. The results can further provide guidance on how to design elder care services for older LGBTQ adults.
Machine learning approaches for use in deblending

Machine learning has grown into a topic of much interest in the seismic industry. Recently, machine learning was introduced in the field of seismic processing for applications such as demultiple, regularization, and tomography. Here, two novel machine learning algorithms are introduced that can perform deblending and automated blending noise classification. Conventional deblending algorithms require a priori information and user expertise to properly select and parameterize a specific algorithm. The potential benefits of machine learning methods include their hands-off implementation and their ability to learn an efficient deblending algorithm directly from data. The introduced methods are supervised learning methods. Their specific tasks (deblending/noise classification) are learned from training data consisting of data example pairs of input and labeled output. For instance, training a deblending algorithm requires pairs of blended data with their unblended counterparts. The availability of training data or the possibility of creating training data are key to the success of these supervised methods. Another aspect is how well the algorithms generalize. Can we expect good performance on (unseen) data that vary from the training data? We address these aspects and further illustrate with synthetic and field data examples. The classification and deblending examples show promising results, indicating that these machine learning algorithms can support and/or replace existing deblending approaches.