Miracle-dz/UniFAR-FTUs huggingface dataset:
Combined depth-resolved cathodoluminescence spectroscopy and transmission electron microscopy on Al(Ga)N multi quantum well structures

A stack of five Al(Ga)N-based quantum wells is investigated by combined laterally and depth resolved cathodoluminescence (CL) spectroscopy in order to distinguish lateral and vertical inhomogeneities of these wells. Transmission electron microscopy (TEM) micrographs provide data for the real sample structure, which enters into the Monte-Carlo simulation of the depth-resolved CL measurements to refine the depth resolution. The comparison of these CL measurements to the results of electron energy loss spectra (EELS) allows to identify local thickness variations of the lower three quantum wells to be the origin of two different luminescence contributions to the overall spectrum. The differentiation of the two groups of quantum wells by depth-resolved CL is demonstrated.
Lower density of arthropod biomass in small high‐Andes
 Polylepis
 fragments affects habitat use in insectivorous birds

Polylepis forests are endemic to the high-Andes, with trees characterized by multi-layered, exfoliating bark-providing protection against harsh, high-elevation conditions, both for individual trees and the wide array of organisms dependent on them. However, Polylepis habitat has suffered severe human-induced land conversion and currently mainly occurs as fragmented remnants only. Here, we studied the effects of fragment size on local ambient temperature and on biomass of bark and its bark-dwelling arthropods. We did so by comparing multiple samples at the edge and interior of both large and small fragments, while also accounting for branch size, tree width, and tree structure. Because arthropod biomass is likely to impact higher trophic levels, we also studied abundance and foraging behavior of two bird species specialized on Polylepis forest. We show that arthropod biomass was relatively higher in wider, larger trees, which were preferred for foraging by both bird species. Moreover, we show that small forest fragments are not only environmentally less buffered but are also characterized by lower amounts of bark and lower densities of bark-dwelling arthropods than larger fragments. Our study highlights the conservation value of large trees. Also, we advise it is now timely to test to what degree restoration efforts to increase fragment size could mitigate the negative effects of reduced arthropod biomass for higher trophic levels of endemic specialist insectivores.
Effects of Mg, Ca, and Fe(II) Doping on the Kaolinite (001) Surface with H2O Adsorption

Kaolinite is often a cause of deformation in soft-rock tunnel engineering, leading to safety problems. The mechanism of the deformation is closely related to the interaction between kaolinite and water molecules. Because kaolinite has multiple defects, the effects of Mg, Ca, and Fe(II) doping on the atomic structure of the kaolinite (001) surface, and the subsequent adsorption and penetration of H2O into the interlayer, were studied systematically using density-functional theory. The results showed that for the Mg-, Ca-, and Fe(II)-doped kaolinites (001), the surface relaxation around the doping layer changed from contraction to expansion, due to the redistribution of electrons. The adsorption energies of the H2O monomer on Mg-, Ca-, and Fe(II)-doped kaolinites (001) were less than on undoped kaolinite (001). The results further revealed that the H2O molecule can also adsorb on the hollow site on the second-layer O surface of the Mg-, Ca-, and Fe(II)-doped kaolinites (001). For the undoped kaolinite, however, the H2O molecule adsorbs on the surface only. The energetic barriers for penetration of H2O from the adsorption site on the surface to the adsorption site on the O surface of Mg-, Ca-, and Fe(II)-doped kaolinites were also calculated: 1.18 eV, 1.07 eV, and 1.41 eV, respectively. The results imply that the influences of Mg, Ca, and Fe(II) doping on kaolinite allow the adsorbed water molecules to penetrate from the on-surface adsorption site to the O-surface site.
Public Health and Disability—The Importance of Keeping up the Good Work

Secondary and tertiary prevention strategies targeting people with disabilities to improve their health and wellbeing is important. In Sweden, >95% of all children with cerebral palsy (CP) participate in a follow-up program, where one of the goals is the prevention of hip dislocations. We reviewed the incidence of hip dislocations from 2010 to 2019 and the number of children who underwent different types of hip surgeries. The number of hip dislocations was reduced from 8.8% before introduction of the program to 0.3-0.4% up to 2015, followed by a gradual increase to 0.8% in 2019. The proportion of children who underwent adductor-psoas lengthening as their primary preventive surgery decreased from 50% in 2017 to 37% in 2019 with a corresponding increase of children undergoing femoral osteotomy, indicating more children underwent surgery at a later stage. Reasons for the increased number of children with hip dislocation may be that more children have moved to Sweden in recent years without corresponding compensation in health care resources and increased waiting times for surgery due to, among other things, a shortage of nurses. The results highlight the importance of constantly monitoring follow-up programs.
Humming Trains in Seismology: An Opportune Source for Probing the Shallow Crust

Seismologists are eagerly seeking new and preferably low-cost ways to map and track changes in the complex structure of the top few kilometers of the crust. By understanding it better, they can build on what is known regarding important, practical issues. These include telling us whether imminent earthquakes and volcanic eruptions are generating telltale underground signs of hazard, about mitigation of induced seismicity such as from deep injection of wastewater, how the Earth and its atmosphere couple, and where accessible natural resources are. Passive seismic imaging usually relies on blind correlations within extended recordings of Earth’s ceaseless “hum” or coda of well-mixed, small vibrations. In this article, we propose a complementary approach. It is seismic interferometry using opportune sources—specifically ones not stationary in time and moving in a well-understood configuration. Its interpretation relies on an accurate understanding of how these sources radiate seismic waves, precise timing, careful placement of pairs of listening stations, and seismic phase differentiation (surface and body waves). Massive freight trains were only recently recognized as such a persistent, powerful cultural (human activity-caused) seismic source. One train passage may generate a tremor with an energy output of a magnitude 1 earthquake and be detectable for up to 100 km from the track. We discuss the source mechanisms of train tremors and review the basic theory on sources. Finally, we present case studies of body- and surface-wave retrieval as an aid to mineral exploration in Canada and to monitoring of a southern California fault zone. We believe noise recovery from this new signal source, together with dense data acquisition technologies such as nodes or distributed acoustic sensing, will deeply transform our ability to monitor activity in the shallow crust at sharpened resolution in time and space.
Tocopherols: Chemical Structure, Bioactivity, and Variability in Croatian Virgin Olive Oils

Virgin olive oil (VOO) represents a rich source of natural antioxidants, with tocopherols as the most effective group of lipophilic, phenolic antioxidants. α-Tocopherol represents more than 95% of the total tocopherols in virgin olive oil, and it possesses the highest biological activity among members of the vitamin E family. Content and composition of the tocopherols of virgin olive oil depend on several agronomic factors, as well as olive processing and oil storage conditions. In this chapter, the tocopherol homologue activity in virgin olive oil and the biological importance are discussed. Research work is reported on the tocopherol content and composition variability in virgin olive oils of the most widespread Croatian cultivar “Oblica” and Italian cultivar “Leccino. ” Factors studied such as year, growing area and olive fruit ripening and their influence on the tocopherol content and composition of virgin olive oils are discussed. The effect of filtration of the oil and storage conditions on tocopherols are also examined. samples, factorial ANOVA was performed (Fisher’s F-test), followed by Tukey”s honest significant difference (HSD) test. A significance level of p ≤ 0.05 was applied. The correlation coefficients ( r ) determined by Pearson correlation matrix were used to define the influence of climatic conditions during the year on the VOOs tocopherol content. The obtained data were analyzed using Statistica software version 11.0 (StatSoft, Inc., USA, 2012).
HSPA2 Expression Predicts Early Postsurgical Relapse and Promotes Tumor Cell Migration and Invasion in Pancreatic Cancer

Background: Heat shock protein A2 (HSPA2) is known to relate to the pathogenesis and progress of cancer. This study aimed to investigate the connection between HSPA2 and early postsurgical relapse, and the influences of HSPA2 on cell biological behaviors in pancreatic cancer (PC). Methods: Expression of HSPA2 in cancerous and noncancerous samples was determined by bioinformatics and immunostaining methods. The significance of HSPA2 expression in predicting early postsurgical recurrence was assessed. The biological role and potential mechanisms of HSPA2 in PC progression were uncovered by enrichment analysis. HSPA2 expression in human PC cells was detected by immunoblotting. Silencing of HSPA2 in BxPC-3 cells and upregulation of HSPA2 in PANC-1 cells were achieved with siRNA and overexpression plasmid, respectively, and then the impacts of HSPA2 downregulation and upregulation on cancer cell biological behaviors were estimated.Results: HSPA2 expression in tumor specimens was markedly elevated compared with nontumor specimens. HSPA2 overexpression could independently predict early postsurgical recurrence, and combined with malignant clinicopathological characteristics had greater predictive power and potential application value. Enrichment analysis revealed that HSPA2 expression was closely associated with PC progression. HSPA2 was expressed in BxPC-3, PANC-1 and SW1990 cells, with the highest and lowest levels in BxPC-3 and PANC-1 cells, respectively. Cell migration and invasion abilities were remarkably restrained in HSPA2-silenced BxPC-3 cells and significantly enhanced in HSPA2-overexpressed PANC-1 cells.Conclusion: HSPA2 expression predicts early postoperative recurrence and promotes cell migration and invasion, and is expected to become a useful molecular target of antitumor treatment in PC.
A Comparison of Estimation Methods for the Rasch Model

The Rasch model is one of the most prominent item response models. In this article, different item parameter estimation methods for the Rasch model are compared through a simulation study. The type of ability distribution, the number of items, and sample sizes were varied. It is shown that variants of joint maximum likelihood estimation and conditional likelihood estimation are competitive to marginal maximum likelihood estimation. However, efficiency losses of limited-information estimation methods are only modest. It can be concluded that in empirical studies using the Rasch model, the impact of the choice of an estimation method with respect to item parameters is almost negligible for most estimation methods. Interestingly, this sheds a somewhat more positive light on old-fashioned joint maximum likelihood and limited information estimation methods.
How prevalent is overfitting of regression models? A survey of recent articles in three psychology journals

Since 2011, there has been much discussion and concern about a "replication crisis" in psychology. An inability to reproduce findings in new samples can undermine even basic tenets of psychology. Much attention has been paid to the following practices, which Bishop (2019) described as "the four horsemen of the reproducibility apocalypse": Publication bias, low statistical power, phacking (Simmons et al., 2011) and HARKing (i.e., hypothesizing after the results are known; Kerr, 1998). Another practice that has received less attention is overfitting of regression models. Babyak (2004) described overfitting as "capitalizing on the idiosyncratic characteristics of the sample at hand", and argued that it results in findings that "don’t really exist in the population and hence will not replicate. " The following common data-analytic practices increase the likelihood of model overfitting: Having too few observations (or events) per explanatory variable (OPV/EPV); automated algorithmic selection of variables; univariable pretesting of candidate predictor variables; categorization of quantitative variables; and sequential testing of multiple confounders. We reviewed 170 recent articles from three major psychology journals and found that 96 of them included at least one of the types of regression models Babyak (2004) discussed. We reviewed more fully those 96 articles and found that they reported 286 regression models. Regarding OPV/EPV, Babyak recommended 10 -15 as the minimum number needed to reduce the likelihood of overfitting. When we used the 10 OPV/EPV cut-off, 97 of the 286 models (33.9%) used at least one practice that leads to overfitting; and when we used 15 OPV/EPV as the cut-off, that number rose to 109 models (38.1%). The most frequently occurring practice that yields overfitted models was univariable pretesting of candidate predictor variables: It was found in 61 of the 286 models (21.3%). These findings suggest that overfitting of regression models remains a problem in psychology research, and that we must increase our efforts to educate researchers and students about this important issue.
Sustainable and regional gastronomy: cassava leaves as a potential ingredient for gluten-free biscuits

The addition of roots derivatives to bakery products may be a promising alternative to add value to these products. This study aimed to characterize and evaluate the effect of cassava leaves on the properties of gluten-free biscuits (GFB). The ingredients used were cassava flour, rice flour, cui, tapioca flour, and 0 (F0), 3.69% (F1), 5.34% (F2), and 7.38% (F3) of cassava leaves (CCL). The results were evaluated by analysis of variance, followed by Scott-Knott test (p-value<0.05). The CCL presented 89.9% moisture, water activity of 0.98, and 2.75% protein; tryptophan was the limiting amino acid. No significant differences were observed between the F0-control and those made with the addition of CCL, which presented moisture and Aw below 3% and 0.30, and hardness between 45 to 60 N. The sensory acceptance scores were greater than 6, which indicates that it is possible to increase the added value of CCL in bakery products. The use of cassava leaves in biscuits showed good technological and sensory characteristics, making it possible to be an ingredient from regional by-products that can favor sustainable development, respect the concept of regionalization, and add income and employment.
Arctic ocean–sea ice reanalysis for the period 2007–2016 using the adjoint method

We present an Arctic ocean–sea ice reanalysis covering the period 2007–2016 based on the adjoint approach of the Estimating the Circulation and Climate of the Ocean (ECCO) consortium. The spatiotemporal variation of Arctic sea surface temperature (SST), sea ice concentration (SIC), and sea ice thickness (SIT) is substantially improved after the assimilation of ocean and sea ice observations. By assimilating additional World Ocean Atlas 2018 (WOA18) hydrographic data, the freshwater content of the Canadian Basin becomes closer to the observations and translates into changes of the ocean circulation and of transports through the Fram and Davis straits. This new reanalysis compares well with previous filter‐based (TOPAZ4) and nudging‐based (PIOMAS) reanalyses regarding SIC and SST. Benefiting from using the adjoint of the sea ice model, our reanalysis is superior to the ECCOv4r4 product considering sea ice parameters. However, the mean state and variability of the freshwater content and the transport properties of our reanalysis remain different from TOPAZ4 and ECCOv4r4, likely because of a lack of hydrographic observations.
Fixed point theorems under Rhoades and Reich contractive conditions in complete cone metric spaces

One of the extended metric space concepts is a cone metric space. The cone metric space was first proposed by Guang and Xian in 2007. In their research, they introduced Banach fixed point theorems in complete cone metric space, namely by analogizing the fixed point theorems in complete metric space. They add normal properties to the cone set. However, Rezapour in 2008 refuted Banach fixed point theorems in cone metric space by eliminating normal properties of the cone set. For this reason, we will investigate the existence and uniqueness of Rhoades and Reich contractive mappings in cone metric space by referring to the research of Guang and Rezapour.
Probabilistic trajectory prediction of heterogeneous traffic agents based on layered spatio-temporal graph

In order to safely and comfortably navigate in the complex urban traffic, it is necessary to make multi-modal predictions of autonomous vehicles for the next trajectory of various traffic participants, with the continuous movement trend and inertia of the surrounding traffic agents taken into account. At present, most trajectory prediction methods focus on prediction on future behavior of traffic agents but with limited, consideration of the response of traffic agents to the future behavior of the ego-agent. Moreover, it can only predict the trajectory of single-type agents, which make it impossible to learn interaction in a complex environment between traffic agents. In this paper, we proposed a graph-based heterogeneous traffic agents trajectory prediction model LSTGHP, which consists of the following three parts: (1) layered spatio-temporal graph module; (2) ego-agent motion module; (3) trajectory prediction module, which can realize multi-modal prediction of future trajectories of traffic agents with different semantic categories in the scene. To evaluate its performance, we collected trajectory datasets of heterogeneous traffic agents in a time-varying, highly dynamic urban intersection environment, where vehicles, bicycles, and pedestrians interacted with each other in the scene. It can be drawn from experimental results that our model can improve its prediction accuracy while interacting at a close range. Compared with the previous prediction methods, the model has less prediction error in the trajectory prediction of heterogeneous traffic agents.
Metabolic imaging and secondary ion mass spectrometry analysis to investigate liver structure and function during regeneration

We analyzed the structural and functional state of liver tissue in normal state and during regeneration using multiphoton microscopy in combination with the time-of-flight secondary ions mass spectrometry (TOF-SIMS). The induction of regeneration process was performed on 30% and 70% hepatectomy models of rats. The FLIM method has shown an increase in the contribution of the bound form of NADH, as well as the contribution of NADPH in hepatocytes, which indicates a growth in the contribution of oxidative phosphorylation and biosynetic processes during liver regeneration. Using the TOF-SIMS method, it has been shown that the signal from fragments of fats, fatty acids, phosphotidylcholine, and sphingomyelin is increased, combined with a decline in the signal from amino acid’s fragments in the regenerating liver. The results will make it possible to identify criteria for assessing the regenerative potential of the liver during resection in order to reduce the risk of developing of the postoperative liver failure.
Health Literacy and Health-Related Quality of Life in Older Adults with Type 2 Diabetes: The Mediating Role of Treatment Regimen Adherence

Background and objective: It is unclear how health literacy is associated with health-related quality of life. The aim of this study was to examine the mediating role of treatment regimen adherence between health literacy and health-related quality of life (HRQoL) in older adults with type 2 diabetes mellitus (T2DM). Material and methods: In this cross-sectional study, a multi-stage cluster sampling method was used to recruit 300 diabetic patients aged 60 years and over with diabetes. The abbreviated version of the Test of Functional Health Literacy in Adults (S-TOFHLA) and the Swedish Health-related Quality of Life (SWED-QUAL) instrument were used to measure health literacy and HRQoL, respectively. In addition, the Morisky Medication Adherence Scale (MMAS), the diet and exercise adherence questionnaire, were used to assess treatment regimen adherence. The four steps of Baron and Kenny’s procedure were implemented to test the mediation hypotheses. Results: The mean age of the respondents was 64.92 years. In addition, the mean of the respondents’ health literacy score was 52.82. The prevalence rates of the inadequate, marginal, and adequate health literacy of the respondents were 70%, 14.7%, and 15.3%, respectively. Two items of treatment regimen adherence (medication adherence and diet and exercise adherence) had a partial mediating role between health literacy and quality of life in elderly diabetes patients. The result of Baron and Kenny’s procedure and Sobel’s test showed a significant mediation role in medication adherence (p = 0.00, Sobel’s Z = 2.77) and diet and exercise adherence (p = 0.00, Sobel’s Z = 6.26) between health literacy and HRQoL. Conclusion: Medication adherence, diet adherence, and exercise adherence are mediating factors in relationship between health literacy and HRQoL that increase the health literacy and quality of life in older adults with T2DM.
Trust Management Approach for Detection of Malicious Devices in SIoT

Internet of Things (IoT) is an innovative era of interrelated devices to provide services to other devices or users. In Social Internet of Thing (SIoT), social networking aspect is used for building relationships between devices. For providing or utilizing services, devices need to trust each other in complex and heterogeneous environments. Separating benign and malicious devices in SIoT is a prime security objective. In literature, several works proposed trust computation models based on trust features. But these models fail to identify malicious devices. This paper focuses on detection of malicious devices. In this paper, basic fundamentals, properties, models and attacks of trust in SIoT are discussed. Up-to-date research distributions on trust management and trust attacks are reviewed and idea of Trust Management using Machine Learning Algorithm (TM-MLA) is proposed for identification of malicious devices.
Wavelet transform analysis of composite signal under multi-source excitation

In practical engineering application, the response of mechanical structure may be the superposition effect of vibration source interaction, while the traditional detection method only considers the main vibration source, ignoring other vibration sources will cause analysis error. Therefore, it is of practical engineering significance to study the detection method of compound excitation in mechanical testing. This paper aims to present an extraction method of composite modulation signal under multi-source excitation by wavelet transform. The modulated signal is analyzed by short-time Fourier transform and wavelet transform. The time-frequency analysis results show that the resolution of wavelet can be automatically adjusted at high frequency, and the effect of wavelet is better at high frequency. The key contribution is to establish a method for extracting multi-source excitation signals and to provide certain technical support for the modulated signal under multi-source excitation.