Miracle-dz/UniFAR-FTUs huggingface dataset:
Wheat grain and straw yield, grain quality, and disease benefits associated with increased management intensity

Winter wheat is a very important crop in the U.S. where an average of 53 million acres have been planted since 2000 (McMullen et al., 2012; USDA NASS, 2020). During the Green Revolution from the 1960’s through 1980’s, many advances in wheat genetics and new varieties led to significant advances in wheat production (Bell et al., 1995; Brancourt-Hulmel et al., 2003), Since then, yield gains have plateaued in many wheatproducing regions, including in the U.S. (Lollato et al. 2019).
Impacts of Interview as Research Instrument of Data Collection in Social Sciences

This paper examined the implications of using interviews as method of data collection in social sciences with reference to researcher’s experience during fieldwork. The paper is purely qualitative and documentary sources were source of data collection. The paper argued that interview as an instrument of data collection when compared to other data collection techniques like questionnaire is more powerful in eliciting narrative data that allow researchers to investigate people's views in greater depth. The paper indicated that interview as a tool for social science data collection research helps to facilitate in obtaining direct explanation for human actions through a comprehensive speech interaction. The paper concluded that although interviewing is a powerful way of getting insights into interviewee's perceptions, it could go hand in hand with other methods providing in-depth information about participants' inner values and beliefs. For instance, using personal observation as a supplement to interviews would allow researchers investigate participants' external behaviors and internal beliefs. Therefore, the paper stressed that using more than one data collection instrument (although it depends on the research questions) would help obtaining richer data and validating the research findings.
On First-Passage Times and Sojourn Times in Finite QBD Processes and Their Applications in Epidemics

In this paper, we revisit level-dependent quasi-birth-death processes with finitely many possible values of the level and phase variables by complementing the work of Gaver, Jacobs, and Latouche (Adv. Appl. Probab. 1984), where the emphasis is upon obtaining numerical methods for evaluating stationary probabilities and moments of first-passage times to higher and lower levels. We provide a matrix-analytic scheme for numerically computing hitting probabilities, the number of upcrossings, sojourn time analysis, and the random area under the level trajectory. Our algorithmic solution is inspired from Gaussian elimination, which is applicable in all our descriptors since the underlying rate matrices have a block-structured form. Using the results obtained, numerical examples are given in the context of varicella-zoster virus infections.
Determination of the composition of multilayer plastic packaging with NIR spectroscopy

In food and medical packaging, multiple layers of different polymers are combined in order to achieve optimal functional properties for various applications. Flexible multilayer plastic packaging achieves a reduction in weight compared to other packaging products with the same function, saving material and in transportation costs. Recycling of post-industrial multilayer packaging was achieved by some companies, but the available technologies are limited to specific polymer types. For post-consumer waste, recycling of multilayer packaging has not been achieved yet. One of the main challenges in plastic sorting is that the detection and separation of multilayer packaging from other materials is not possible yet. In this study, the possibility to detect and sort flexible multilayer plastic packaging was investigated with near-infrared spectroscopy, which is the state-of-the-art technology for plastic sorting. The results show that from a detection and classification point of view, sorting of monolayer, two- and three-layers samples under laboratory conditions is possible. According to the captured data, the sequence of layers has little influence on the spectra. In case of glossy samples, the spectra are influenced by printed surfaces. With an increase in thickness, the spectra get more characteristic, which makes the classification easier. Our results indicate that the sorting of post-consumer multilayer plastic packaging by main composition is theoretically achievable.
An Alternative to Dark Matter and Dark Energy: Scale-Dependent Gravity in Superfluid Vacuum Theory

We derive an effective gravitational potential, induced by the quantum wavefunction of a physical vacuum of a self-gravitating configuration, while the vacuum itself is viewed as the superfluid described by the logarithmic quantum wave equation. We determine that gravity has a multiple-scale pattern, to such an extent that one can distinguish sub-Newtonian, Newtonian, galactic, extragalactic and cosmological terms. The last of these dominates at the largest length scale of the model, where superfluid vacuum induces an asymptotically Friedmann–Lemaître–Robertson–Walker-type spacetime, which provides an explanation for the accelerating expansion of the Universe. The model describes different types of expansion mechanisms, which could explain the discrepancy between measurements of the Hubble constant using different methods. On a galactic scale, our model explains the non-Keplerian behaviour of galactic rotation curves, and also why their profiles can vary depending on the galaxy. It also makes a number of predictions about the behaviour of gravity at larger galactic and extragalactic scales. We demonstrate how the behaviour of rotation curves varies with distance from a gravitating center, growing from an inner galactic scale towards a metagalactic scale: A squared orbital velocity’s profile crosses over from Keplerian to flat, and then to non-flat. The asymptotic non-flat regime is thus expected to be seen in the outer regions of large spiral galaxies.
Deep learning of quality control for stereotaxic registration of human brain MRI

Linear registration to stereotaxic space is a common first step in many automated image-processing tools for analysis of human brain MRI scans. This step is crucial for the success of the following image-processing steps. Several well-established algorithms are commonly used in the field of neuroimaging for this task, but none of them has a 100% success rate. Manual assessment of the registration is commonly used as part of quality control. We propose a completely automatic quality control method based on deep learning that replaces human rater and accurately performs quality control assessment for stereotaxic registration of T1w brain scans. In a recently published study from our group comparing linear registration methods, we used a database of 9693 MRI scans from several publically available datasets and applied five linear registration tools. In this study, the resulting images that were assessed and labeled by a human rater are used to train a deep neural network to detect cases when registration failed. Our method was able to achieve 88% accuracy and 11% false positive rate in detecting scans that should pass quality control, better than a manual QC rater.
Anatomical Features of the Tubercle and Young Sporophyte of the Annual Fern Anogramma chaerophylla Growing in the Punta Lara Natural Reserve (Buenos Aires, Argentina)

Abstract The fern genus Anogramma is characterized by the presence of annual sporophytes and tubercles that persist through dry periods. Tubercles may host embryos that develop when climatic conditions are more favorable. As information on the structure of the tubercle and sporophyte of Anogramma chaerophylla is incomplete, the objective of this work was to analyze anatomical characteristics during development and deepen knowledge of the adaptive strategies of this species. Spores were grown in-vitro and different stages of tubercle development and embryonic sporophytes were fixed in FAA, embedded in Paraplast and analyzed using light microscopy. Initially, the green gametophyte developed antheridia and archegonia in its thickened portion, where later bisexual tubercles differentiated. Embryos developed only from the archegonia located in the tubercles, with one embryo developing per tubercule. During sporophyte growth the reserves accumulated in the tubercle were consumed. Oversized cells were observed at the junction between the green gametophyte and the tubercle, suggesting a possible role in translocation of substances. The young sporophyte consisted of a short shoot and a prominent foot. The placenta comprised the foot cells and the adjacent tubercle cells. The first leaves protruded soon and developed early as photosynthetic organs. Sporophytes remained attached to the tubercles until advanced stages of development. Vegetative propagation was documented in smaller tubercles that did not develop gametangia. Because few sporophytes were observed in vivo, it is likely that natural populations are maintained through vegetative propagation of the gametophyte until favorable conditions encourage development of sporophytes.
Demarcating the anatomical structure of the claustrum: piecing together a new functional puddle

Background: A major obstacle in the understanding of the functional anatomy of the claustrum has been, and continues to be, the contradiction surrounding its anatomical boundary and, in particular, its rostral (i.e. anterior to striatum), extent. In a recent review we highlighted gene expression-based evidence from the mouse brain which lends weight to the idea that the anatomical boundary of the claustrum does in fact extend rostral to the anterior apex of the striatum. In light of this evidence, in the present study, we have examined the expression of two genes that have previously been identified as having differential expression in the mouse claustrum, with the aim of: 1, establishing the true neuroanatomical boundaries of the rat claustrum; and 2, determining the efficacy of claustral marker expression in the histological verification of claustral electrode placement following electrophysiological recordings in awake behaving rats. Methods: The expression profiles of two genes, crystallin mu (Crym) and guanine nucleotide binding protein (G protein), gamma 2 (Gng2) were assessed immunohistochemically in five male rats (one Wistar Kyoto (WK) and four Lister hooded (LH)). Prior to histological analysis, two of the rats had undergone surgical implantation of tetrodes targeting the putative rostral claustrum. Results: In results that are consistent with those we have previously described in the mouse brain, expression of Crym in the rat brain was highly attenuated, or absent, in the claustrum, demarcating a nuclear boundary that extended considerably beyond the anterior apex of the striatum. In concordance, enriched expression of Gng2 was found in the claustrum, again extending equivalently rostral to the anterior apex of the striatum. The expression of claustral marker genes is a highly effective tool in the verification of electrophysiological electrode placement. Electrophysiological recordings from within this Gng2 and Crym-defined boundary of the rostral claustrum support previous reports of a spatial map in the rostral claustrum. Conclusions: It is now clear that the anatomical boundary of the rat claustrum does in fact extend into more frontal regions of the brain than has previously been asserted. The importance of these findings are considered in the context of the regional specificity of claustral function, anatomical connectivity and electrophysiological properties.
Real-time observation of ion migration in halide perovskite by photoluminescence imaging microscopy

The stability issue of organometal halide perovskite optoelectronic devices, e.g. the current–voltage –hysteresis effect and the degradation of the device performance under external light/electric field, are closely related to the ionic movement inside perovskite materials. However, our understanding of ionic properties is still at a relatively preliminary stage, and the detailed dynamic process of ionic movement in perovskite materials is controversial. Photoluminescence (PL) imaging microscopy, as a versatile real-time observation and characterization method, has become a powerful tool to explore the ionic movement in different material systems. This review firstly summarizes the development of PL imaging microscopy for ion migration characterization in perovskite materials. Secondly, combined with the wide-field PL imaging microscope, the dynamic process of ion migration in halide perovskite materials is further discussed. Thirdly, the observations of the degradation process and the ion migration suppression in different perovskite optoelectronic devices characterized by PL imaging microscopy are also introduced. This methodology is of significance for the deep understanding of the interaction between carriers/defect ions in perovskite materials, and provides guidance to further improve the stability and efficiency of perovskite optoelectronic devices.
Linguistic Analysis of Self-Narratives of Patients With Gambling Disorder

Aim of the present study was to investigate affective and cognitive processes underlying self-narratives of patients with gambling disorder through a verbal language analysis. A semistructured interview was administered to 30 patients with gambling disorder (GD) (24 males and 6 females; mean age: 46.63±9.08) concerning the various thematic areas of their condition: definition of addiction, onset and maintenance of the addiction, relapses, desire, loss of control, control strategies, and treatment. Word usage in the self-narratives was categorized using James Pennebaker’s Linguistic Inquiry and Word Count (LIWC) text-analysis software. Specifically, variables analyzed were emotion-related words, the use of pronoun-related words, and tense-related words. The findings showed a higher percentage of negative emotion-related words in the thematic areas of the definition of addiction, maintenance, and loss of control compared with other areas, which may suggest an emotional dysregulation; a higher percentage of first person singular-related words than other person-related words which decreases in the thematic areas of the desire, relapse, and loss of control, which may suggest dissociative phenomena; lastly, a high percentage of present tense-related words, which suggested a static and rigid representation of one’s dependency condition in GD patients and a difficulty to self-project into the future. Overall, the linguistic analysis revealed critical issues in affective and cognitive processes in specific phases of addiction in GD patients which could help guide treatment.
Unaltered soil microbial community composition, but decreased metabolic activity in a semiarid grassland after two years of passive experimental warming

Abstract Soil microbial communities regulate soil carbon feedbacks to climate warming through microbial respiration (i.e., metabolic rate). A thorough understanding of the responses of composition, biomass, and metabolic rate of soil microbial community to warming is crucial to predict soil carbon stocks in a future warmer climate. Therefore, we conducted a field manipulative experiment in a semiarid grassland on the Loess Plateau of China to evaluate the responses of the soil microbial community to increased temperature from April 2015 to December 2017. Soil temperature was 2.0°C higher relative to the ambient when open‐top chambers (OTCs) were used. Warming did not affect microbial biomass or the composition of microbial functional groups. However, warming significantly decreased microbial respiration, directly resulting from soil pH decrease driven by the comediation of aboveground biomass increase, inorganic nitrogen increase, and moisture decrease. These findings highlight that the soil microbial community structure of semiarid grasslands resisted the short‐term warming by 2°C, although its metabolic rate declined.
Evaluation of porcine epidemic diarrhea virus in feed manufacturing

Biological hazards in animal feed are a growing concern for the feed industry. Porcine epidemic diarrhea virus (PEDV) is the first viral pathogen confirmed to be transmissible in swine feed and feed ingredients. This led to investigations identifying the magnitude of transmissible risk PEDV imposes and strategies to mitigate infectivity in contaminated diets. The objective of the first experiment was to evaluate the minimum infectious dose of PEDV in virus-inoculated feed. Pigs became infected when PEDV concentrations at or above 5.6 × 10 50% tissue culture infectious dose/g (TCID50/g); corresponding feed cycle threshold (Ct) of 37 or below was utilized. Evaluation of a mitigation strategy for PEDV contaminated diets is also important since cross-contamination during feed manufacturing is possible. Therefore, the objective of the second experiment was to determine the effectiveness of feed batch sequencing as a method to minimize the risk of PEDV cross-contamination. This method was effective to reduce but not eliminate infectious PEDV carryover risk. Furthermore, feed that lacked detectible PEDV RNA as analyzed by quantitative real-time reverse transcription PCR assay (qPCR) was infectious. The third study was an observational study complementary to the previous experiment where the magnitude of virus contamination in the feed manufacturing facility was characterized during feed batch sequencing. Widespread contamination of the facility occurred and surfaces remained contaminated until chemically cleaned. The final experiment was conducted to assess PEDV RNA detection in feed and spray dried porcine plasma (SDPP) when analyzed by qPCR across 5 diagnostic laboratories. Overall, it appears qPCR PEDV RNA detection in feed and SDPP was precise as quantified by low coefficient of variation across laboratories, with the exception of one %CV from SDPP inoculated with low virus load from one laboratory. Although the magnitude of the Ct value difference was large in only 1 of 5 laboratories, comparisons of Ct values across laboratories should be interpreted cautiously. Finally, qPCR can be a useful surveillance tool for detection of PEDV RNA in non-clinical samples such as feed and SDPP.
Procedure for collecting milk sample and the number of milkings in relation to chemical composition and somatic cells of the fresh milk

This study was carried out to determine which system of milkings and sampling methodology presenting chemical composition results safer and lower variation of the results. In Properties I and II, the fresh milk samples were collected in 40 ml flasks containing bronopol in order to compare the chemical composition of the milk, as adopting two sample collection methods, that is two and three milkings. In order to compare the chemical composition of milk and SCC, between two sampling methodologies, in two daily milkings (Property I) and three daily milkings (Property II), fresh milk samples were collected randomly totaling 300 samples on the property I and 312 samples on the property II. The milk chemical components were determined through analytical principle that is based on differential absorption of infrared waves by components of the milk. By analyzing the treatments, experimental design was used entirely randomized and averages were compared by Tukey test using the statistical program SISVAR (statistical analysis system). When evaluating the data obtained through variation coefficient (VC), the occurrence of experimental was observed, since most results showed low variation. However the distinct procedures for sampling of the fresh milk may present varied levels of the chemical composition and SCC, therefore overestimating or underestimating the values of the milk composition, when samples are collected at different times of the day and different number of milkings. Key words: Cows of high production, isolates samples, period, pool, sampling methodology.
Internal acoustic structuring in pied babbler recruitment cries specifies the form of recruitment

Language is inherently combinatorial, and parallels of this combinatorial capacity are found in nonhuman systems, with animals combining sounds and calls into larger meaningful structures. However, further analogue examples are central in unveiling the diversity, distribution, and evolutionary drivers of combinatoriality. Here, we provide evidence for internal “meaning-refining” acoustic variation within a larger stereotyped signal in pied babblers (Turdoides bicolor). Using acoustic analyses, we demonstrate that males produce 2 long, raucous, “cry-like” structures, both starting with a wind-up segment grading into repetitions of A/single-note or AB/double-note motifs. Behavioral observations indicated that, consistent with similarities in their larger stereotyped structure, both variants function overall in recruiting group members during locomotion, but the internal A or AB substructure specifies the “precise” form of recruitment, from approaching the caller’s announced location to following it over longer distances. Playing back cries from a stationary loudspeaker further supported that the 2 variants elicit different responses, with more individuals approaching the loudspeaker in response to single-note compared with double-note cries. Additionally, despite similarities in overall distance travelled, group movement was only directional for single-note, but undefined for double-note cries. We suggest that the overall structure of the 2 cry variants conveys the same general meaning, with embedded variation refining this meaning. These results further illustrate the variability of generative mechanisms outside of human language and lend support to the hypothesis that combinatorial structuring may have emerged in species with limited or fixed vocal repertoires in order to enhance communicative output.
Applications of Computational Methods in Biomedical Breast Cancer Imaging Diagnostics: A Review

With the exponential increase in new cases coupled with an increased mortality rate, cancer has ranked as the second most prevalent cause of death in the world. Early detection is paramount for suitable diagnosis and effective treatment of different kinds of cancers, but this is limited to the accuracy and sensitivity of available diagnostic imaging methods. Breast cancer is the most widely diagnosed cancer among women across the globe with a high percentage of total cancer deaths requiring an intensive, accurate, and sensitive imaging approach. Indeed, it is treatable when detected at an early stage. Hence, the use of state of the art computational approaches has been proposed as a potential alternative approach for the design and development of novel diagnostic imaging methods for breast cancer. Thus, this review provides a concise overview of past and present conventional diagnostics approaches in breast cancer detection. Further, we gave an account of several computational models (machine learning, deep learning, and robotics), which have been developed and can serve as alternative techniques for breast cancer diagnostics imaging. This review will be helpful to academia, medical practitioners, and others for further study in this area to improve the biomedical breast cancer imaging diagnosis.