Miracle-dz/UniFAR-FTUs huggingface dataset:
Will This Online Shopping Session Succeed? Predicting Customer's Purchase Intention Using Embeddings

Customers are increasingly using online channels to buy products. For e-commerce companies, this offers new opportunities to tailor the shopping experience to customers' needs. Therefore, it is of great importance for a company to know their customers' intentions while browsing their webpage. A major challenge is the real-time analysis of a customer's intention during browsing sessions. To this end, a representation of the customer's browsing behavior must be retrieved from their live interactions on the webpage. Typically, characteristic behavioral features are extracted manually based on the knowledge of marketing experts. In this paper, we propose a customer embedding representation that is based on the customer's click-events recorded during browsing sessions. Thus, our approach does not use manually extracted features and is not based on marketing expert domain knowledge, which makes it transferable to different webpages and different online markets. We demonstrate our approach using three different e-commerce datasets to successfully predict whether a customer is going to purchase a specific product. For the prediction, we utilize the customer embedding representations as input for different machine learning models. We compare our approach with existing state-of-the-art approaches for real-time purchase prediction and show that our proposed customer representation with an LSTM predictor outperforms the state-of-the-art approach on all three datasets. Additionally, the creation process of our customers' representation is on average 235 times faster than the creation process of the baseline.
Comprehensive Control Strategy of Fuel Consumption and Emissions Incorporating the Catalyst Temperature for PHEVs Based on DRL

PHEVs (plug-in hybrid electric vehicles) equipped with diesel engines have multiple model transitions in the driving cycle for their particular structure. The high frequency of start–stop of a diesel engine will increase fuel consumption and reduce the catalytic efficiency of SCR (Selective Catalyst Reduction) catalysts, which will increase cold start emissions. For comprehensive optimization of fuel consumption and emissions, an optimal control strategy of PHEVs that originated from the PER-TD3 algorithm based on DRL (deep reinforcement learning) is proposed in this paper. The priority of samples is assigned with greater sampling weight for high learning efficiency. Experimental results are compared with those of the DP (dynamic programming)-based strategy in HIL (hardware in loop) equipment. The engine fuel consumption and NOX emissions were 2.477 L/100 km and 0.2008 g/km, nearly 94.1% and 90.1% of those of the DP-based control strategy. By contrast, the fuel consumption and NOx of DDPG (Deep Deterministic Policy Gradient)-based and TD3(Twin Delayed Deep Deterministic Policy Gradient) -based control strategy were 2.557, 0.2078, 2.509, and 0.2023, respectively. By comparative results, we can see that the comprehensive control strategy of PHEVs based on the PER-TD3 algorithm we proposed can achieve better performance with comparison to TD3-based and DDPG-based, which is the state-of-the-art strategy in DRL. The HIL-based experimental results prove the effectiveness and real-time potential of the proposed control strategy.
No Job Demand Is an Island – Interaction Effects Between Emotional Demands and Other Types of Job Demands

Emotional demands are an inevitable feature of human services, and suggested to be a defining antecedent for workers’ stress and ill health. However, previous research indicate that emotional demands can have a favorably association to certain facets of human service workers’ motivation and well-being. Furthermore, recent research report that the effect of emotional demands on workers’ health and well-being seem to be contingent on the parallel level of other job demands. Still, initial investigations of interaction effects between emotional demands and other types of job demands have primarily focused on negative outcomes in terms of stress-related concerns and absenteeism. The present study investigated interaction effects between emotional demands and other types of job demands in relation to positive outcomes. In a larger sample of human service workers (social workers, n = 725), interaction effects were investigated between emotional demands and other job demands (quantitative demands, work pressure, and role conflict) for meaning in work and quality of work. Hypotheses stated that other job demands would moderate the relationship between emotional demands and positive outcomes, so that emotional demands would have a positive relation (i.e., act as a challenge) when the level of other demands is lower, but have a negative relation (i.e., act as a hindrance) when the level of other demands is high. Overall, the results provided support for the idea that emotional demands may act as a challenge. We found small but significant interaction effects between emotional demands and work pressure – in relation to meaning of work, as well as between emotional demands and quantitative demands, work pressure, and role-conflict, respectively – in relation to quality of work. Yet, the results did not support the assumption that emotional demands act as a hindrance when the level of other types of job demands is high. In sum, the results contribute by showing that emotional demands may promote human-service workers’ job attitudes when the level of parallel job demands is lower. We discuss the contribution of the study and the potential practical implications of the results, and give some suggestions for future research.
Fluence thresholds for grazing incidence hard x-ray mirrors

X-ray Free Electron Lasers (XFELs) have the potential to contribute to many fields of science and to enable many new avenues of research, in large part due to their orders of magnitude higher peak brilliance than existing and future synchrotrons. To best exploit this peak brilliance, these XFEL beams need to be focused to appropriate spot sizes. However, the survivability of X-ray optical components in these intense, femtosecond radiation conditions is not guaranteed. As mirror optics are routinely used at XFEL facilities, a physical understanding of the interaction between intense X-ray pulses and grazing incidence X-ray optics is desirable. We conducted single shot damage threshold fluence measurements on grazing incidence X-ray optics, with coatings of ruthenium and boron carbide, at the SPring-8 Angstrom compact free electron laser facility using 7 and 12 keV photon energies. The damage threshold dose limits were found to be orders of magnitude higher than would naively be expected. The incorporation of energy transport and dissipation via keV level energetic photoelectrons accounts for the observed damage threshold.
Identification of Endophytic Microbiota of Phytoplasma-Infected Russian Olive Trees “Elaeagnus angustifolia L.” in the Northwest of Iran

In this study, Russian olive trees exhibiting witches’-broom symptoms were collected from urban green areas in Tabriz, in the northwest of Iran. PCR analysis confirmed that phytoplasma caused the disease and, according to the resulting Sanger sequencing electropherogram, a mixed infection with two or more phytoplasma species within the Russian olive trees was revealed. Next-generation sequencing analyses, using the Illumina method, were performed on total DNA from the infected Russian olive plants to recognize the microbial genomic content and assemble the whole genome of the causative pathogen(s). The use of MetaphlAn2 and Kraken2 to analyze species composition revealed the very diverse and unique compositions of different Prokaryotic and Eukaryotic species within the infected plants. Several bacteria and fungi were discovered inside the samples, among which Mycoplasmatota was significantly dominating. Interestingly, the results also revealed a high level of endosymbiotic bacteria and Archaea (Methanobacteria) genome contents within the samples. Bowtie2, metaSPAdes, and CD-HIT pipelines were used to perform the initial genome assembly, and the whole genome of the notable phytoplasma species was assembled and submitted to Genbank.
Health Behavior and Cancer Prevention among Adults with Li-Fraumeni Syndrome and Relatives in Germany—A Cohort Description

Li-Fraumeni-syndrome (LFS) is a rare, highly penetrant cancer predisposition syndrome (CPS) caused by pathogenic variants (PVs) in TP53. Physical activity (PA) and a Mediterranean diet lead to cancer reduction or survival benefits and increased quality of life (QoL), but this is yet unstudied among LFS. TP53 PV carriers (PVC) and their relatives were questioned on dietary patterns (Mediterranean Diet Adherence Screener), PA (Freiburg Questionnaire), QoL (Short-form-Health-Survey-12), smoking, alcohol consumption and perception of cancer risk in a German bi-centric study from March 2020–June 2021. The study enrolled 70 PVC and 43 relatives. Women compared to men (6.49 vs. 5.38, p = 0.005) and PVC to relatives (6.59 vs. 5.51; p = 0.006) showed a healthier diet, associated with participation in surveillance (p = 0.04) and education (diet p = 0.02 smoking p = 0.0003). Women smoked less (2.91 vs. 5.91 packyears; p = 0.03), psychological well-being was higher among men (SF-12: males 48.06 vs. females 41.94; p = 0.004). PVC rated their own cancer risk statistically higher than relatives (72% vs. 38%, p < 0.001) however, cancer risk of the general population was rated lower (38% vs. 70%, p < 0.001). A relative’s cancer-related death increased the estimated personal cancer risk (p = 0.01). The possibilities of reducing cancer through self-determined health behavior among PVC and relatives has not yet been exhausted. Educating families with a CPS on cancer-preventive behavior requires further investigation with regard to acceptance and real-life implementation.
How Our Microbiome Influences the Pathogenesis of Alopecia Areata

Alopecia areata is a multifactorial autoimmune-based disease with a complex pathogenesis. As in all autoimmune diseases, genetic predisposition is key. The collapse of the immune privilege of the hair follicle leading to scalp loss is a major pathogenic event in alopecia areata. The microbiota considered a bacterial ecosystem located in a specific area of the human body could somehow influence the pathogenesis of alopecia areata, as it occurs in other autoimmune diseases. Moreover, the Next Generation Sequencing of the 16S rRNA bacterial gene and the metagenomic methodology have provided an excellent characterization of the microbiota. The aim of this narrative review is to examine the published literature on the cutaneous and intestinal microbiota in alopecia areata to be able to establish a pathogenic link. In this review, we summarize the influence of the microbiota on the development of alopecia areata. We first introduce the general pathogenic mechanisms that cause alopecia areata to understand the influence that the microbiota may exert and then we summarize the studies that have been carried out on what type of gut and skin microbiota is found in patients with this disease.
DENIS J081730.0−615520: AN OVERLOOKED MID-T DWARF IN THE SOLAR NEIGHBORHOOD

Recent wide-field near-infrared surveys have uncovered a large number of cool brown dwarfs (BDs), extending the temperature sequence down to less than 500 K and constraining the faint end of the luminosity function (LF). One interesting implication of the derived LF is that the BD census in the immediate (<10 pc) solar neighborhood is still largely incomplete, and some bright (J < 16) BDs remain to be identified in existing surveys. These objects are especially interesting as they are the ones that can be studied in most detail, especially with techniques that require large fluxes (e.g., time-variability, polarimetry, and high-resolution spectroscopy) that cannot realistically be applied to objects uncovered by deep surveys. By cross-matching the DEep Near-Infrared Survey of the Southern sky (DENIS) and the Two Micron All Sky Survey point-source catalogs, we have identified an overlooked BD—DENIS J081730.0−615520—that is the brightest field mid-T dwarf in the sky (J = 13.6). We present astrometry and spectroscopy follow-up observations of this BD. Our data indicate a spectral type T6 and a distance—from parallax measurement—of 4.9 ± 0.3 pc, placing this mid-T dwarf among the three closest isolated BDs to the Sun.
Schottky barriers at hexagonal boron nitride/metal interfaces: A first-principles study

The formation of a Schottky barrier at the interface between a metal and hexagonal boron nitride (h−BN) is studied using density functional theory. For metals whose work functions range from 4.2 to 6.0 eV, we find Schottky barrier heights for holes between 1.2 and 2.3 eV. A central role in determining the Schottky barrier height is played by a potential step of between 0.4 and 1.8 eV that is formed at the metal|h−BN interface and effectively lowers the metal work function. If h−BN is physisorbed, as is the case on fcc Cu, Al, Au, Ag, and Pt(111) substrates, the interface potential step is described well by a universal function that depends only on the distance separating h−BN from the metal surface. The interface potential step is largest when h−BN is chemisorbed, which is the case for hcp Co and Ti (0001) and for fcc Ni and Pd (111) substrates
Hubble–Lemaître fragmentation and the path to equilibrium of merger-driven cluster formation

This paper discusses a new method to generate self-coherent initial conditions for young substructured stellar cluster. The expansion of a uniform system allows stellar sub-structures (clumps) to grow from fragmentation modes by adiabatic cooling. We treat the system mass elements as stars, chosen according to a Salpeter mass function, and the time-evolution is performed with a collisional N-body integrator. This procedure allows to create a fully-coherent relation between the clumps' spatial distribution and the underlying velocity field. The cooling is driven by the gravitational field, as in a cosmological Hubble-Lema\^itre flow. The fragmented configuration has a `fractal'-like geometry but with a self-grown velocity field and mass profile. We compare the characteristics of the stellar population in clumps with that obtained from hydrodynamical simulations and find a remarkable correspondence between the two in terms of the stellar content and the degree of spatial mass-segregation. In the fragmented configuration, the IMF power index is ~0.3 lower in clumps in comparison to the field stellar population, in agreement with observations in the Milky Way. We follow in time the dynamical evolution of fully fragmented and sub-virial configurations, and find a soft collapse, leading rapidly to equilibrium (timescale of 1 Myr for a ~ 10^4 Msun system). The low-concentration equilibrium implies that the dynamical evolution including massive stars is less likely to induce direct collisions and the formation of exotic objects. Low-mass stars already ejected from merging clumps are depleted in the end-result stellar clusters, which harbour a top-heavy stellar mass function.
Lung Cancer Risk in Men and Compliance with the 2018 WCRF/AICR Cancer Prevention Recommendations

Lung cancer is the most common and deadly form of cancer worldwide, especially in men. The 2018 World Cancer Research Fund/American Institute for Cancer Research (WCRF/AICR) updated cancer prevention recommendations, and a standard scoring system (2018 WCRF/AICR Score) was published. The purpose of this study was to develop the adapted version of the 2018 WCRF/AICR Score with respect to lung cancer prevention recommendation (Ad-LC WCRF/AICR Score) and to examine the association between lung cancer risk in men and the Ad-LC WCRF/AICR Score as well as its single components. A case–control study was conducted among 439 men aged 45–80 years (187 controls, 252 primary lung cancer cases). Lifestyle and dietary data were collected with a questionnaire including the 62-item food frequency questionnaire (FFQ-6®). The Ad-LC WCRF/AICR Score was used as a categorized and continuous variable. Odds ratios (ORs) and 95% confidence intervals (95% CIs) for lung cancer risk were calculated with the partly and fully adjusted model. One component of the score was independently associated with a lower risk of lung cancer in men, regardless of the set of confounders used. In the fully adjusted model following the recommendation “Limit smoking” was associated with a lower risk of lung cancer—in the never smokers by 87% (OR: 0.13; 95% CI: 0.04–0.37; p = 0.0002) and in the moderate smokers by 45% (OR: 0.55; 95% CI: 0.33–0.91; p = 0.0189) compared with the heavy smokers as a reference. By adding the single components making up the Ad-LC WCRF/AICR Score, the combination of three components or more, reducing the risk of lung cancer compared to lower compliance as a reference by 45% to 78% and by 39% to 66% for intermediate compliance (except two models out of seven) and higher compliance, respectively. In the fully adjusted model, the risk of lung cancer for the total Ad-LC WCRF/AICR Score was lower by 47% (OR: 0.53; 95% CI: 0.32–0.88; p = 0.0129) in higher compliance with the score compared to those with the lower compliance. Each one-point increase in the Ad-LC WCRF/AICR Score reduced lung cancer risk by 34% (OR: 0.66; 95% CI: 0.45–0.95; p = 0.0267). The results support previous evidence that limiting smoking reduces the risk of lung cancer in men. It also provides an insight into cancer research by showing that following the combined 2018 cancer prevention recommendations related to diet, lifestyle and body fatness was associated with a lower risk of lung cancer in men.
On Multiple Discount Rates with Recursive Time-Dependent Orders

This study adresses time-dependent orders that are shown to lead to recursive representations based upon a Max-Min dichotomy and introduce a structure that is naturally based upon time-varying multiple discounts. It is argued that this setup naturally provides an enriched understanding of the much discussed present biases. It is established how a multiple discounts version of present biais becomes available and directly builds upon the features of the order deﬁned from the head of the utilities sequence.
Transcriptome Response of Differentiating Muscle Satellite Cells to Thermal Challenge in Commercial Turkey

Early muscle development involves the proliferation and differentiation of stem cells (satellite cells, SCs) in the mesoderm to form multinucleated myotubes that mature into muscle fibers and fiber bundles. Proliferation of SCs increases the number of cells available for muscle formation while simultaneously maintaining a population of cells for future response. Differentiation dramatically changes properties of the SCs and environmental stressors can have long lasting effects on muscle growth and physiology. This study was designed to characterize transcriptional changes induced in turkey SCs undergoing differentiation under thermal challenge. Satellite cells from the pectoralis major (p. major) muscle of 1-wk old commercial fast-growing birds (Nicholas turkey, NCT) and from a slower-growing research line (Randombred Control Line 2, RBC2) were proliferated for 72 h at 38 °C and then differentiated for 48 h at 33 °C (cold), 43 °C (hot) or 38 °C (control). Gene expression among thermal treatments and between turkey lines was examined by RNAseq to detect significant differentially expressed genes (DEGs). Cold treatment resulted in significant gene expression changes in the SCs from both turkey lines, with the primary effect being down regulation of the DEGs with overrepresentation of genes involved in regulation of skeletal muscle tissue regeneration and sarcomere organization. Heat stress increased expression of genes reported to regulate myoblast differentiation and survival and to promote cell adhesion particularly in the NCT line. Results suggest that growth selection in turkeys has altered the developmental potential of SCs in commercial birds to increase hypertrophic potential of the p. major muscle and sarcomere assembly. The biology of SCs may account for the distinctly different outcomes in response to thermal challenge on breast muscle growth, development, and structure of the turkey.
Do investment-speciﬁc technological changes matter for business ﬂuctuations? Evidence from Japan

The observed decline in the relative price of investment goods to consumption goods in Japan suggests the existence of investment-speci(cid:133)c technological (IST) changes. We examine whether IST changes are a major source of business (cid:135)uctuations in Japan, by estimating a dynamic stochastic general equilibrium model with Bayesian methods. We show that IST changes are less important than neutral technological changes in explaining output (cid:135)uctuations. We also demonstrate that investment (cid:135)uctuations are mainly driven by shocks to investment adjustment costs. Such shocks represent variations of costs involved in changing investment spending, such as (cid:133)nancial intermediation costs. We then (cid:133)nd that the estimated series of the investment adjustment cost shock correlates strongly with the di⁄usion index of (cid:133)rms(cid:146) (cid:133)nancial position in the Tankan (Short-term Economic Survey of Enterprises in Japan). We thus argue that the large decline in investment growth in the early 1990s is due to an increase in investment adjustment costs stemming from (cid:133)rms(cid:146) tight (cid:133)nancial constraint after the collapse of Japan(cid:146)s asset price bubble. Hirose (2008), Sugo and Ueda (2008), Ichiue et al . (2008), Fujiwara et al . (2008), Kaihatsu and Kurozumi (2010), and Fueki et al . (2010). These studies, except the last three, estimate DSGE models for stationary variables using detrended data as in line with Christiano et al . (2005), Smets and Wouters (2003), and Levin et al . (2006). This approach di⁄ers from that of the present paper, since our DSGE model incorporates stochastic trends both in neutral technology and in IST so that we can explicitly examine whether the boom-bust cycle during the late 1980s and the early 1990s in Japan is driven by changes in the trends or by non-permanent shocks. scale for the jumping distribution in the Metropolis-Hastings algorithm so that the acceptance rate of 25% was obtained. and Gelman(cid:146)s was used to check the convergence of parameters.