Miracle-dz/UniFAR-FTUs huggingface dataset:
Fast and high precision phase recovery technology of single-shot ineterferogram based on depth convolution neural network

Phase retrieval from single interferogram is of great interest for the possibility of dynamic phase measurement. However, it is a very complicated process in reality since the unknowns and knows are highly unequal. In this paper, we propose a fast phase recovery method from single interferogram based on deep convolution neural network. The network is trained based on supervised learning to achieve the purpose of quickly obtaining unwrapped phase results from a single interferogram. To improve the detection accuracy, a modified set establishment model has been propose to improve the practicability of the fringe data. The simulation and experimental results show that the root mean square value of residual phase extraction error by this method is closed to 0. 01λ (λ = 632.8 nm), and the constructed depth convolution neural network model has significant flexibility and effective generalization ability for phase recovery of single frame interference fringe.
How important is the in-store environment for new brands?

New brand launches are notoriously risky, with high failure rates. Yet, most research focuses on the out-of-store factors inherent to their success/failure, overlooking strategies that can be employed in-store. The present research addresses this oversight by examining the influence of two in-store factors, distraction and shelf position, and their impact on a new brand’s visibility on the shelf. We draw on a unique data set featuring a real-life new brand entrant into the Australian market. Using an experimental design in a shopper laboratory, and mobile eye-tracking, we find that the new brand stands a greater chance of being noticed and visually attended to on the shelf when shoppers are distracted. This is attributed to shoppers dwelling longer in front of the fixture, being more open to new-to-the-consumer brands, and by negatively affecting the top-down processing of existing brands on the shelf. We also find that optimising shelf position, which is a common in-store marketing tactic for existing brands, may not produce the same return on investment for a new brand. The findings offer valuable theoretical and practical implications for improving the success rates of new brand launches, including selection of distribution channels, allocation of marketing resources, and the interplay between in-store and out-of-sore factors driving shopper behaviour.
Implementation of the CEFR in the Mexican Context

Mots-cles: cadre europeen commun de reference pour les langues, enseignement base sur les strategies d'apprentissage, anglais langue etrangere, plurilinguisme, autonomie d'apprentissage Abstract: The present paper outlines case study research conducted at the Universidad Popular Autonoma del Estado de Puebla3 (UPAEP), in Puebla, Mexico. It explains an ongoing initiative to implement the Common European Framework of Reference for Languages (CEFR) in the Departamento de Estudios de Lengua y Cultura4 (DELC). The purpose of this paper is to explain how Strategy-Based Instruction (SBI) was adapted in order to initiate the implementation of the CEFR in the Mexican university context; specifically at the UPAEP. It first describes the Mexican university context. Next, it presents the theoretical framework with a focus on learner variables, and how the Mexican sociolinguistic context influences these variables. Then, different language initiatives created at the university to develop the learner variables in the sociolinguistic context are described. This section is followed by a discussion of the results of implementing SBI and factors that influence these results. To conclude, the authors emphasize the importance of the sociocultural context when effectively adapting the CEFR and discuss issues for future research in the DELC regarding the implementation of the CEFR.
A Gourd-Shape HTS Plate-Loop with Flux Density Amplification Function

High-temperature superconducting (HTS) magnets have huge advantages for providing strong magnetic fields within a compact structure and saving energy. However, it is almost impossible for them to operate in persistent current mode (PCM) since the soldering technique without resistance is unavailable. A gourd-shape HTS plate-loop configured by partial central cutting REBCO HTS tape with a function of flux density amplification is proposed. It consists of two circular holes with different diameters connected by a single slit. The conventional copper coil with an iron core is positioned within the big loop. This arrangement allows for a higher flux density in the small loop compared to the big loop by the field cooling (FC) exciting method, which can be seen as a form of flux density amplification. Flux density amplifying function of the gourd-shape HTS loop is confirmed by performing experiments and numerical simulation in 77 K. The results suggest that the gourd-shape HTS loop design offers significant advantages. It can provide higher magnetic field strength than the big loop, operate in PCM without current leads, and have a wider operational temperature range than LTS magnets. These attributes make it highly promising for various applications, such as magnetic resonance imaging (MRI), accelerator technology, and other fields that require high magnetic fields. Additionally, this design has the potential to lower manufacturing costs and facilitate easier implementation of HTS permanent magnets, thus promoting the widespread utilization of HTS technology in the industrial sector.
HPV16 Intratypic Variants in Head and Neck Cancers: A North American Perspective

Human papillomavirus (HPV) is the major causative agent for cervical and many head and neck cancers (HNCs). HPVs randomly acquire single nucleotide polymorphisms (SNPs) that may become established via positive selection. Within an HPV type, viral isolates differing by <2% in the L1 region are termed “variants” and classified based on combinations of SNPs. Studies in cervical cancer demonstrate clear differences between HPV16 intratypic variants in terms of persistence of infection, tumor histology, cancer risk, and death. Much less is known about the frequency of HPV16 variants in HNC, and their effects on clinical outcomes. We combined HPV16 positive (HPV16+) HNC samples from a local Southwestern Ontario, Canada cohort with those from the Cancer Genome Atlas to create a larger North American cohort of 149 cases with clinical data and determined the distribution of intratypic variants and their impact on clinical outcomes. Most isolates were lineage A, sublineage A1, or A2, with roughly half exhibiting the T350G polymorphism in E6. Univariable analysis identified significant differences between 350T and 350G intratypic variants in clinical T, N, and O staging, as well as disease-free survival. Multivariable analysis failed to identify any clinical factor as a statistically significant covariate for disease-free survival differences between 350T and 350G. Significant differences in several measures of B-cell mediated immune response were also observed between 350T and 350G intratypic variants. We suggest that HPV genetic variation may be associated with HNC clinical characteristics and may have prognostic value.
LIDAR-INERTIAL NAVIGATION BASED ON MAP AIDED DISTANCE CONSTRAINT AND FACTOR GRAPH OPTIMIZATION

Abstract. The simultaneous localization and mapping (SLAM) is one of the well-developed positioning technology that provides high accuracy and reliability positioning for automatic vehicles and robotics applications. Integrating Light Detection and Ranging (LiDAR) with an Inertial Measurement Unit (IMU) has emerged as a promising technique for achieving stable navigation results in dense urban environments, outperforming vision-based or pure Inertial Navigation System (INS) solutions. However, conventional LiDAR-Inertial SLAM systems often suffer from limited perception of surrounding geometric information, resulting in unexpected and accumulating errors. In this paper, we proposed a LiDAR-Inertial SLAM scheme that utilizes a prior structural information map which is generated from opensource OpenStreetMap (OSM). In contrast to conventional solutions of OSM-aided SLAM approaches, our method extracts the vectorized models of road and building and synthetically generates dense point maps for LiDAR registration. Specifically, a structural map processing module extracts the road models and building models from OSM and generates a structure information map (SIM) with dense point clouds. Secondly, a map aided distance (MD) constraint is calculated by registering selected keyframes and the prior SIM. Finally, a factor graph optimization (FGO) algorithm is involved to integrate the relative transformation obtained from LiDAR odometry, IMU pre-integration, and the map aided distance constraints. To evaluate the proposed LiDAR-based positioning accuracy, experimental evaluation is implemented in an opensource dataset collected in the urban canyon environments. Experimental results demonstrates that with the help of the proposed MD constraint, the LiDAR-based navigation solution can achieve accurate positioning, with a root mean square deviation (RSME) of 4.7 m.
Enriched Sioux Falls scenario with dynamic and disaggregate demand

This paper presents an enriched, agent-based small scale scenario with dynamic demand and an integrated public transport system based on the commonly used Sioux Falls road network. The scenario aims to provide a realistic, fully dynamic demand with heterogeneous socio- demographic users and a high degree of spatial resolution. Real world survey and land-use data is used to generate a diverse synthetic population and accurate activity locations. The socio-demographic characteristics include age and sex on individual and income on household levels. The assignment of home and work locations employs land-use and building information, census data from the City of Sioux Falls, South Dakota as well as commonly used static OD-matrices from LeBlanc et al., 1975. This enriched Sioux Falls scenario can serve as a convenient test-case for the study of different transportation policies as well as a test bed for the extension and development of agent-based simulation frameworks. It is important to note that the scenario does not aim to replicate the real City of Sioux Falls, SD, and remains a fictitious test-case scenario. In this work, we use Multi-agent Transport Simulation (MATSim) in order to evaluate the stochastic user-equilibrium of the compiled supply and demand. The scenario data, as well as simulations input and output, can be obtained by following the instructions at www.matsim. org/scenario/sioux-falls.
Tectonic Relations Of Crustal Blocks In Relation To The Late Palaeozoic-Neogene Evolution Of Neotethyan Oceans In The Eastern Mediterranean Region (S Turkey, Cyprus, Syria)

Recent hydrocarbon-related and academic discoveries help the geological development of the easternmost Mediterranean basin to be better understood. Here, we focus on the northern margin of the Eastern Mediterranean basin and the area encompassing southern Turkey, Cyprus and northern Syria. Compared to the sub-sea geology of the Eastern Mediterranean basin, the Late Palaeozoic- Recent geology of the land areas to the north and east is relatively well known. Here, we draw on our own fieldbased research, coupled with much recently published information and use all of the available information to develop outline palaeotectonic maps of the region. These maps and the accompanying synthesis, hopefully will aid in the assessment of the hydrocarbon potential of the region as whole. We will focus on the Late Palaeozoic to Middle Miocene time period during which Neotethyan oceans opened and then largely closed. Although important, the submarine record of the pre-Neogene geology is sparse and still largely not in the public domain. For brevity we also exclude detailed consideration of the tectonic development of the Eurasian continental margin.
Recent ground thermo-hydrological changes in a southern Tibetan endorheic catchment and implications for lake level changes

Abstract. Climate change modifies the water and energy fluxes between the atmosphere and the surface in mountainous regions such as the Qinghai–Tibet Plateau (QTP), which has shown substantial hydrological changes over the last decades, including rapid lake level variations. The ground across the QTP hosts either permafrost or is seasonally frozen, and, in this environment, the ground thermal regime influences liquid water availability, evaporation and runoff. Consequently, climate-induced changes in the ground thermal regime may contribute to variations in lake levels, but the validity of this hypothesis has yet to be established. This study focuses on the cryo-hydrology of the catchment of Lake Paiku (southern Tibet) for the 1980–2019 period. We process ERA5 data with downscaling and clustering tools (TopoSCALE, TopoSUB) to account for the spatial variability of the climate in our forcing data (Fiddes and Gruber, 2012, 2014). We use a distributed setup of the CryoGrid community model (version 1.0) to quantify thermo-hydrological changes in the ground during this period. Forcing data and simulation outputs are validated with data from a weather station, surface temperature loggers and observations of lake level variations. Our lake budget reconstruction shows that the main water input to the lake is direct precipitation (310 mm yr−1), followed by glacier runoff (280 mm yr−1) and land runoff (180 mm yr−1). However, altogether these components do not offset evaporation (860 mm yr−1). Our results show that both seasonal frozen ground and permafrost have warmed (0.17 ∘C per decade 2 m deep), increasing the availability of liquid water in the ground and the duration of seasonal thaw. Correlations with annual values suggest that both phenomena promote evaporation and runoff. Yet, ground warming drives a strong increase in subsurface runoff so that the runoff/(evaporation + runoff) ratio increases over time. This increase likely contributed to stabilizing the lake level decrease after 2010. Summer evaporation is an important energy sink, and we find active-layer deepening only where evaporation is limited. The presence of permafrost is found to promote evaporation at the expense of runoff, consistently with recent studies suggesting that a shallow active layer maintains higher water contents close to the surface. However, this relationship seems to be climate dependent, and we show that a colder and wetter climate produces the opposite effect. Although the present study was performed at the catchment scale, we suggest that this ambivalent influence of permafrost may help to understand the contrasting lake level variations observed between the south and north of the QTP, opening new perspectives for future investigations.
OBJECT DETECTION AND LOCALISATION FOR BIM ENRICHMENT

Abstract. The use of Building Information Models (BIM) during the entire life cycle of a building or facility requires an up-to-date and detailed digital representation. Nowadays the BIM focus mostly lies on the design and construction phase of the building and is rarely used for the rest of the life cycle. For further use the BIM must be updated after construction and enriched with appliance objects such as safety equipment, heating elements to enhance its usability. In this work a new approach is presented to detect and locate appliance objects in a three dimensional environment using object detection in images created by indoor mobile mapping devices. By detecting and locating these appliance objects in the three dimensional world they can be included in the BIM model. This approach enables the detection and localization needed for the placement of placeholders or detailed geometric models of those appliances in the BIM model or other digital representations. Resulting in an increased level of detail and usability of the digital representation of the building or facility during its further life cycle. Overall, this work demonstrates and examines the accuracy of the detection and localization of appliance objects.
Spice plants as a biology learning resource based-education for sustainable development

Studying biology has research topics that are closely related to all the living things around the student and important for them to understand thoroughly. One of the local potentials in the environment around students that can be used as a source of learning biology is spice plants. This research is a qualitative descriptive study. The research aims to describe the spice plants in the Botanical Smartpark, which can be used as learning resources. The result of this research shows that there are 57 species and 27 families of spice plants found at the Botanical Smartpark, Yogyakarta, Indonesia. Spice plant biology objects can be used in biology learning by using project-based learning and socio-scientific issues-based learning models. In addition, this local potential can support education for sustainable development (ESD), through environmental conservation.
Contamination Of Poultry Carcasses With Staphylococcusspecies At Slaughterhouses Of Three Companies In Khartoum

This study was carried out to identify staphylococci bacteria which contaminate poultry carcasses which may cause food poisoning. Fresh poultry carcass samples were collected from slaughterhouses of three companies in Khartoum State. The total number of samples was 100 (30 intestine, 35 liver and 35 skin). They were cultured onto Baird Parker and manitol salt agar. After being purified, they were identified according to their morphological and biochemical properties. The highest frequency of isolation of staphylococci was from the liver, followed by skin and intestine. S. capitis subsp. ureolyticus, S. warneri were found in the three organs (liver, skin and intestine). While S. kloosi, S. epiderimidis, S. hyicus and S. capitis were only present in liver and skin. S. caseolyticus, S. pulveri and S. haemolyticus were present in the liver only and S. chromogen and S. lentus on the skin only.
Instance-Agnostic and Practical Clean Label Backdoor Attack Method for Deep Learning Based Face Recognition Models

Backdoor attacks, which induce a trained model to behave as intended by an adversary for specific inputs, have recently emerged as a serious security threat in deep learning-based classification models. In particular, because a backdoor attack is executed solely by incorporating a small quantity of malicious data into a dataset, it poses a significant threat to authentication models, such as facial cognition systems. Depending on whether the label of the poisoned samples has been changed, backdoor attacks on deep learning-based face recognition methods are categorized into one of the two architectures: 1) corrupted label attack; and 2) clean label attack. Clean label attack methods have been actively studied because they can be performed without access to training datasets or training processes. However, the performance of previous clean label attack methods is limited in their application to deep learning-based face recognition methods because they only consider digital triggers with instance-specific characteristics. In this study, we propose a novel clean label backdoor attack, that solves the limitations of the scalability of previous clean label attack methods for deep learning-based face recognition models. To generate poisoned samples that are instance agnostic while including physical triggers, the proposed method applies three core techniques: 1) accessory injection; 2) optimization-based feature transfer; and 3) $N$ :1 mapping for generalization. From the experimental results under various conditions, we demonstrate that the proposed attack method is effective for deep learning-based face recognition models in terms of the attack success rate on unseen samples. We also show that the proposed method not only outperforms the recent clean label attack methods, but also maintains a comparable level of classification accuracy when applied to benign data.
Analysis of Nuclear Dynamics in Nematode-Trapping Fungi Based on Fluorescent Protein Labeling

Nematophagous fungi constitute a category of fungi that exhibit parasitic behavior by capturing, colonizing, and poisoning nematodes, which are critical factors in controlling nematode populations in nature, and provide important research materials for biological control. Arthrobotrys oligospora serves as a model strain among nematophagous fungi, which begins its life as conidia, and then its hyphae produce traps to capture nematodes, completing its lifestyle switch from saprophytic to parasitic. There have been many descriptions of the morphological characteristics of A. oligospora lifestyle changes, but there have been no reports on the nuclear dynamics in this species. In this work, we constructed A. oligospora strains labeled with histone H2B–EGFP and observed the nuclear dynamics from conidia germination and hyphal extension to trap formation. We conducted real-time imaging observations on live cells of germinating and extending hyphae and found that the nucleus was located near the tip. It is interesting that the migration rate of this type of cell nucleus is very fast, and we speculate that this may be related to the morphological changes involved in the transformation to a predatory lifestyle. We suggest that alterations in nuclear shape and fixation imply the immediate disruption of the interaction with cytoskeletal mechanisms during nuclear migration. In conclusion, these findings suggest that the signal initiating nuclear migration into fungal traps is generated at the onset of nucleus entry into a trap cell. Our work provides a reference for analysis of the dynamics of nucleus distribution and a means to visualize protein localization and interactions in A. oligospora.
Upcycling of HDPE Milk Bottles into High-Stiffness, High-HDT Composites with Pineapple Leaf Waste Materials

In the pursuit of sustainability and reduced dependence on new plastic materials, this study explores the upcycling potential of high-density polyethylene (HDPE) milk bottles into high-stiffness, high-heat-distortion-temperature (HDT) composites. Recycled high-density polyethylene (rHDPE) sourced from used milk bottles serves as the composite matrix, while reinforcing fillers are derived from dried pineapple leaves, comprising fibers (PALF) and non-fibrous materials (NFM). A two-roll mixer is employed to prepare rHDPE/NFM and rHDPE/PALF mixtures, facilitating filler alignment in the resulting prepreg. The prepreg is subsequently stacked and pressed into composite sheets. The introduction of PALF as a reinforcing filler significantly enhances the flexural strength and modulus of the rHDPE composite. A 20 wt. % PALF content yields a remarkable 162% increase in flexural strength and a 204% increase in modulus compared to neat rHDPE. The rHDPE/NFM composite also shows improved mechanical properties, albeit to a lesser degree than fiber reinforcement. Both composites exhibit a slight reduction in impact resistance. Notably, the addition of NFM or PALF substantially elevates HDT, raising the HDT values of the composites to approximately 84 °C and 108 °C, respectively, in contrast to the 71 °C HDT of neat rHDPE. Furthermore, the overall properties of both the composites are further enhanced by improving their compatibility through maleic anhydride-modified polyethylene (MAPE) use. Impact fracture surfaces of both composites reveal higher compatibility and clear alignment of NFM and PALF fillers, underscoring the enhanced performance and environmental friendliness of composites produced from recycled plastics reinforced with pineapple leaf waste fillers.