Miracle-dz/UniFAR-FTUs huggingface dataset:
The Influences of gradient color on the weight perception and stability perception: A preliminary study

Gradient colors are widely used in product design. The variation of gradient colors muting a color as a series of steps from bright to dull creates a soft and gradual impression while also affecting people's perceptions. This study manipulates the types of gradient colors to explore the relationship between color gradients and perception of stability to determine whether weight perception plays a role. In the case of controlling for aesthetic differences, the study manipulated two types of color gradients (dark colors fading upward from the bottom versus downward from the top) and measured the perceptions of product stability. In the same hue, an upward gradient gives a stronger perception of stability. In addition, gradient colors significantly influence women's perception of stability more than men's. The study also investigated the mediating effect of weight perception: participants evaluated color fading-upward products with less weight relative to fading-downward colors. Furthermore, dark colors fading upward from the bottom lead to a stronger perception of weight, increasing the stability perception of the object. Finally, to aid future research, we discuss the practical implications of the current findings for areas such as sensory marketing, as well as possible directions for future research.
Disparity Estimation using a Color Segmentation

This thesis work is mainly motivated to solve the stereo correspondence problem. As solving the correspondence problem could result a precise disparity map allowing the interpolation of intermediate views in 3DTV, the disparity map estimation receives nowadays constant research interests by lots researchers worldwide. According to the state-of-art, the colour segmentation-based stereo matching algorithm achieves best performance among all algorithms. This thesis work dedicates to use image's colour segmentation information for the region's disparity modeling by polynomial function, and re ne the nal disparity map via a region merging process. The parameters of local matching algorithm have been studied and we address the at- tention at disparity polynomial model tting, disparity map re nement by region merging process in this thesis.
Integrating U-Nets Into a Multiscale Full-Waveform Inversion for Salt Body Building

In salt provinces, full-waveform inversion (FWI) is most likely to fail when starting with a poor initial model that lacks the salt information. Conventionally, salt bodies are included in the FWI starting model by interpreting the salt boundaries from seismic images, which is time consuming and prone to error. Studies show that FWI can improve the interpreted salt provided that the data have long offsets and low frequencies, which is not always the case. Thus, we develop an approach to invert for the salt body starting from a poor initial model, limited data offsets, and the absence of low frequencies. We leverage deep learning to apply multistage flooding and unflooding of the velocity model. Specifically, we apply a multiscale FWI using three frequency bandwidths. We apply a network after each frequency scale. After the first two bandwidths, the networks are trained to flood the salt, while the network after the last frequency bandwidth is trained to unflood it. We follow the unflooding step, with a final FWI. We verify the method on the synthetic BP 2004 salt model benchmark. We only use the synthetic data of short offsets up to 6 km and remove frequencies below 3 Hz. We also apply the method to real vintage data acquired in the Gulf of Mexico (GOM) region. The real data lack frequencies below 6 Hz and the streamer length is only 4.8 km. With these limitations, we manage to recover the salt body and verify the result by using them to image the data and analyze the resulting angle gathers.
SciNet: Codesign of Resource Management in Cloud Computing Environments

The rise of distributed cloud computing technologies has been pivotal for the large-scale adoption of Artificial Intelligence (AI) based applications for high fidelity and scalable service delivery. Systematic resource management is central in maintaining optimal Quality of Service (QoS) in cloud platforms and is divided into three fundamental types: resource provisioning, AI model deployment and workload placement. To exploit the synergy among these decision types, it becomes imperative to concurrently design (co-design) the provisioning, deployment and placement decisions for optimal QoS. As users and cloud service providers shift to non-stationary AI-based workloads, frequent decision making imposes severe time constraints on the resource management models. Existing AI-based solutions often optimize decision types independently and tend to ignore the dependencies across various system performance aspects such as energy consumption and CPU utilization, making them perform poorly in large-scale cloud systems. To address this, we propose a novel method, called SciNet, that leverages a co-simulated digital-twin of the infrastructure to capture inter-metric dependencies and accurately estimate QoS scores. To avoid expensive simulation overheads at test time, SciNet trains a neural network based imitation learner that aims to mimic an oracle, which takes optimal decisions based on co-simulated QoS estimates. Offline model training and online decision making based on the imitation learner, enables SciNet to take optimal decisions while being time-efficient. Experiments with real-life AI-based benchmark applications on a public cloud testbed show that SciNet gives up to 48% lower execution cost, 79% higher inference accuracy, 71% lower energy consumption and 56% lower response times compared to the current state-of-the-art methods.
Sigma-1 receptor knockout disturbs gut microbiota, remodels serum metabolome, and exacerbates isoprenaline-induced heart failure

Introduction Heart failure (HF) is usually the end stage of the continuum of various cardiovascular diseases. However, the mechanism underlying the progression and development of HF remains poorly understood. The sigma-1 receptor (Sigmar1) is a non-opioid transmembrane receptor implicated in many diseases, including HF. However, the role of Sigmar1 in HF has not been fully elucidated. Methods In this study, we used isoproterenol (ISO) to induce HF in wild-type (WT) and Sigmar1 knockout (Sigmar1−/−) mice. Multi-omic analysis, including microbiomics, metabolomics and transcriptomics, was employed to comprehensively evaluate the role of Sigmar1 in HF. Results Compared with the WT-ISO group, Sigmar1−/− aggravated ISO-induced HF, including left ventricular systolic dysfunction and ventricular remodeling. Moreover, Sigmar1−/− exacerbated ISO-induced gut microbiota dysbiosis, which was demonstrated by the lower abundance of probiotics g_Akkermansia and g_norank_f_Muribaculaceae, and higher abundance of pathogenic g_norank_f_Oscillospiraceae and Allobaculum. Furthermore, differential metabolites among WT-Control, WT-ISO and Sigmar−/−-ISO groups were mainly enriched in bile secretion, tryptophan metabolism and phenylalanine metabolism, which presented a close association with microbial dysbiosis. Corresponding with the exacerbation of the microbiome, the inflammation-related NOD-like receptor signaling pathway, NF-kappa B signaling pathway and TNF signaling pathway were activated in the heart tissues. Conclusion Taken together, this study provides evidence that a Sigmar1 knockout disturbs the gut microbiota and remodels the serum metabolome, which may exacerbate HF by stimulating heart inflammation.
International Environmental Modelling and Software Society (iemss) 7th Intl. Congress on Env. Modelling and Software, the Challenges of Incorporating Urine and Dung Patches in Process-based Modelling of Grazed Agricultural Systems

Animals are well known to be important in lateral transfers of nitrogen within the farm boundary. Those transfers can be categorised into those that are: (a) primarily random and small-scale dung and urine patches within a grazed paddock, (b) larger and systematic transfers resulting from preferred grazing and resting areas and (c) those that are additionally mediated by management actions such as manure management from housing systems. We review how key simulation models treat the random category of nitrogen transfers and develop recommendations for usage and further development. While urine patches are clearly understood to be important in N cycling in grazed pastures, few simulation models consider the effect of the patchy urine deposition, primarily because the inclusion of the deposition process greatly increases the complexity of the simulation model. Some modellers choose to ignore the effect – and if the primary aim is to model production rather than environmental effect then that position may be quite justifiable. Some authors have taken an approach to model the pasture and leaching at the scale of an isolated patch and then scale up to the paddock level post-simulation. These solutions require relatively little model development and are computationally-efficient but they cannot capture the effects of feedbacks into the system caused by changes in N fluxes and cycling. Far more complex solutions can be informative but they do not lend themselves to practical application at the paddock or farm level. Routine implementation of urine patches into a simulation model will require a balance between realism and pragmatism as it is not generally practical to include the full complexity involved in a whole farm model. 1 INTRODUCTION Grasslands occupy about 25% of the terrestrial surface (Lemaire et al., 2011) and contribute to the livelihoods of over 800 million people (Reynolds et al., 2005). As such they have an important role to play in satisfying the increasing worldwide demand for high-quality protein (Steinfield et al., 2006). Given their extent, grasslands are a crucial system to consider when evaluating local or global issues related to sustainable land management, especially in the face of ongoing land-use changes and climatic uncertainty. Although, compared to other farming types, grazing-based farming systems are often considered to be relatively environmentally benign, they have been following the general trend of agricultural activities with increasing usage of imported nutrients. This importation of nutrients results in an intensification of the farm system, usually through …
Limited effectiveness of selected bioeffectors combined with recycling phosphorus fertilizers for maize cultivation under Swiss farming conditions

The use of plant biostimulants, also known as bioeffectors (BEs), has attracted increasing attention as an environmentally friendly strategy for more sustainable crop production. BEs are substances or microorganisms that are applied to plants or the surrounding soil to stimulate natural processes to enhance nutrient uptake, stress tolerance, and plant growth. Here, we tested the effectiveness of five BEs to enhance maize growth and phosphorus (P) uptake from various recycled P fertilizers in a series of pot and field experiments. First, the impact of two bacterial BEs and one soil-specific plant-based BE on crop performance was assessed in a 4-week screening experiment conducted in two arable, P-deficient soils of differing soil pH (a silty clay loam of pH 7.1 and a silty loam of pH 7.8) amended with recycled P-fertilizers (rock phosphate, biogas digestate, green waste compost, composted dairy manure, and chicken manure pellets). Then, for each soil type, the plant growth-promoting effect of the most promising BE–fertilizer combinations was re-assessed in an 8-week experiment. In addition, over a period of up to 3 years, three field experiments were conducted with maize in which up to two bacterial BEs were used either alone or in combination with a plant-based BE. Our experiments show that while BEs in combination with specific P-fertilizers can promote maize growth within the first weeks of growth under controlled conditions, the observed effects vanished in the long term, both in pots and under field conditions. In a tracing experiment, in which we tested the persistence of one bacterial BE over a period of 5 weeks, we observed a drastic decrease in colony-forming units already 2 weeks after inoculation. As previously shown in other studies, our data indicate that the plant growth-promoting effects of BEs found under controlled conditions are not directly transferable to field conditions. It is suggested that the drastic decline in inoculated bacterial strains in the tracing experiment is the reason for the decline in plant growth effect.
Inter-domain routing

Internet is the hugest network the humanity has ever known. It provides a large number of various services to more than two billion users. This complex and growing topology lacks stability, which we can notice when a voice call is dropped, when a web page needs to be refreshed, etc. The initiator of this instability is the frequent events around the Internet. This motivates us to unleash a profound study to tackle Internet stability and suggest solutions to overcome this concern. Internet is divided into two obvious levels: AS (Autonomous System) level and router level. This distinction is reflected on the routing protocols that control the Internet traffic through two protocol types: exterior (inter-AS) and interior (intra-AS). The unique used exterior routing protocol is the external mode of BGP (External Border Gateway Protocol), while there are several used internal routing protocols. Therefore, stabilizing the Internet is correlated to the routing protocol stability, which directs such efforts to the investigation of routing protocol (BGP) behavior. Studying BGP behaviors results in that its external mode (eBGP) suffers from long convergence time which is behind the slow response to topology events and, in turn, the traffic loss. Those studies state also that BGP internal mode (iBGP) suffers from several types of routing anomalies that causes its divergence.Therefore, we propose enhancements for both BGP modes: eBGP and iBGP and try to meet the following objectives: Scalability, safety, robustness, correctness, and backward compatibility with current version of BGP. Our eBGP proposal eliminates the transient disconnectivity caused by slow convergence by suggesting a backup strategy to be used upon the occurrence of a failure. IBGP proposal (skeleton) gives an alternative to the existing internal configurations, that we prove its freeness of anomalies. Validation methods are essential to prove that the suggested enhancements satisfy the attended objectives. Since we are tackling an interdomain subject, then it is not possible to do validation in the real Internet. We suggested several validation methods to show that our enhancements meet the above objectives. We used simulation environment to implement eBGP backup solution and observe the convergence time and the continuous connectivity. We relied on two tools: brite and rocketfuel to provide us with inter and intra AS topologies respectively. And to prove the safety of our approaches we employed an algebraic framework and made use of its results.
Influence of ceramic thickness, background and cement shade on the translucency of zirconia reinforced lithium silicate and lithium disilicate ceramics

Background Although, the influence of cement and background shade on the final color and translucency of zirconia reinforced lithium silicate (ZLS) and lithium disilicate (LDS) ceramics has been previously investigated, there is still little data on the translucency of LDS and ZLS ceramics in decreased thickness (0.4 and 0.6 mm). The aim of this study was to investigate ceramic thickness’, background and cement shades’ effects on the zirconia reinforced lithium silicate (ZLS) and lithium disilicate (LDS) ceramics’ translucency. Material and Methods Totally 160 square-shaped A1 shade LDS and ZLS samples produced in 0.4 and 0.6 mm thicknesses were cemented with light and neutral shade resin cement on A2 and A3 shade composite resin backgrounds. The color notations of specimen were measured and translucency parameter (TP) values were calculated. Factorial ANOVA and Tamhane’s T2 multiple comparison statistical analyzes were used. Results Highest TP values (11.82±0.97) were obtained in ZLS specimens that were 0.4 mm in thickness, cemented on A2 background with light shade resin cement. While, the lowest TP values (9.60±0.55) were calculated in LDS samples that had 0.6 mm thickness, cemented on A3 background with neutral shade resin cement. Conclusions Material type, thickness, and background shade affected TP values of specimens. The cement and background shade used might change the final translucency of ZLS and LDS ceramics that had 0.4 and 0.6 mm thickness. Key words:Ceramics, lithium disilicate, spectrophotometry, zirconia, dental materials.
Flavonoid Composition and Antioxidant Activity of Tragia volubilis L. Methanolic Extract

Several species from the genus Tragia L. in the family Euphorbiaceae are part of the ethnomedicine of traditional cultures, and have a variety of uses. Tragia volubilis L. is a species spread through tropical America and Africa with several ethnomedical uses, particularly for wound healing and reproductive issues. In this study, we assess the phytochemical composition and antioxidant activity of the methanolic extract of the aerial parts of T. volubilis collected in southern Ecuador. The phytochemical screening of the extract shows the preliminary presence of carbohydrates, alkaloids, flavonoids, and tannins. The extract shows an Antioxidant Activity Index of 1.14, interpreted as strong antioxidant activity. Four flavonoid compounds were isolated through chromatographic procedures and identified through NMR spectroscopy: avicularin, quercitrin, afzelin, and amentoflavone. The biological activity of these compounds matches the ethnopharmacological uses of the species. This is the first phytochemical study of T. volubilis and supports its traditional medicinal uses.
Cogs in the autophagic machine—equipped to combat dementia-prone neurodegenerative diseases

Neurodegenerative diseases are often characterized by hydrophobic inclusion bodies, and it may be the case that the aggregate-prone proteins that comprise these inclusion bodies are in fact the cause of neurotoxicity. Indeed, the appearance of protein aggregates leads to a proteostatic imbalance that causes various interruptions in physiological cellular processes, including lysosomal and mitochondrial dysfunction, as well as break down in calcium homeostasis. Oftentimes the approach to counteract proteotoxicity is taken to merely upregulate autophagy, measured by an increase in autophagosomes, without a deeper assessment of contributors toward effective turnover through autophagy. There are various ways in which autophagy is regulated ranging from the mammalian target of rapamycin (mTOR) to acetylation status of proteins. Healthy mitochondria and the intracellular energetic charge they preserve are key for the acidification status of lysosomes and thus ensuring effective clearance of components through the autophagy pathway. Both mitochondria and lysosomes have been shown to bear functional protein complexes that aid in the regulation of autophagy. Indeed, it may be the case that minimizing the proteins associated with the respective neurodegenerative pathology may be of greater importance than addressing molecularly their resulting inclusion bodies. It is in this context that this review will dissect the autophagy signaling pathway, its control and the manner in which it is molecularly and functionally connected with the mitochondrial and lysosomal system, as well as provide a summary of the role of autophagy dysfunction in driving neurodegenerative disease as a means to better position the potential of rapamycin-mediated bioactivities to control autophagy favorably.
Micromachined piezoelectric Lamb wave resonators: a review

With the development of next-generation wireless communication and sensing technologies, there is an increasing demand for high-performance and miniaturized resonators. Micromachined piezoelectric Lamb wave resonators are becoming promising candidates because of their multiple vibration modes, lithographically defined frequencies, and small footprint. In the past two decades, micromachined piezoelectric Lamb wave resonators based on various piezoelectric materials and structures have achieved considerable progress in performance and applications. This review focuses on the state-of-the-art Lamb wave resonators based on aluminum nitride (AlN), aluminum scandium nitride (Al x Sc1−x N), and lithium niobate (LiNbO3), as well as their applications and further developments. The promises and challenges of micromachined piezoelectric Lamb wave resonators are also discussed. It is promising for micromachined piezoelectric Lamb wave resonators to achieve higher resonant frequencies and performance through advanced fabrication technologies and new structures, the integration of multifrequency devices with radio frequency (RF) electronics as well as new applications through utilizing nonlinearity and spurious modes. However, several challenges, including degenerated electrical and thermal properties of nanometer-scale electrodes, accurate control of film thickness, high thin film stress, and a trade-off between electromechanical coupling efficiencies and resonant frequencies, may limit the commercialization of micromachined piezoelectric Lamb wave resonators and thus need further investigation. Potential mitigations to these challenges are also discussed in detail in this review. Through further painstaking research and development, micromachined piezoelectric Lamb wave resonators may become one of the strongest candidates in the commercial market of RF and sensing applications.
Sync for Genes Phase 5: Computable artifacts for sharing dynamically annotated FHIR‐formatted genomic variants

Variant annotation is a critical component in next‐generation sequencing, enabling a sequencing lab to comb through a sea of variants in order to hone in on those likely to be most significant, and providing clinicians with necessary context for decision‐making. But with the rapid evolution of genomics knowledge, reported annotations can quickly become out‐of‐date. Under the ONC Sync for Genes program, our team sought to standardize the sharing of dynamically annotated variants (e.g., variants annotated on demand, based on current knowledge). The computable biomedical knowledge artifacts that were developed enable a clinical decision support (CDS) application to surface up‐to‐date annotations to clinicians.