bluuebunny/crossref_metadata_2025 huggingface dataset:
Influence of thermal pretreatments on dimensional change and humidity sensitivity of densified spruce and poplar wood
Authors: Pelit Huseyin , Yorulmaz Ramazan
Published: October 2023

The effect of thermal pretreatments on the dimensional change and humidity sensitivity of densified spruce (Picea orientalis) and poplar (Populus nigra) wood were investigated. A thermal pretreatment was applied on the wood specimens at 140 °C, 160 °C, 180 °C, and 200 °C for 7 h and 9 h. Wood specimens were then compressed at ratios of 20 % and 40 % at a temperature of 150 °C. The results showed that spring-back and thickness swelling increased in all specimens (thermally pre-treated and untreated) depending on the increase in compression ratio. However, set-recovery was determined higher at 20 % compression ratio. The equilibrium moisture content values ​​of untreated specimens and thermally pre-treated specimens at low temperatures (140 ºC and 160 ºC) were found lower than uncompressed specimens. The impact of compression ratio on equilibrium moisture content was not clear. Thermal pretreatments significantly affected the dimensional stability and hygroscopicity of densified specimens (especially poplar wood). Depending on the increase in thermal pretreatment temperature and duration, spring-back, set-recovery and thickness swelling in wood specimens decreased up to 31 %, 67 % and 62 %, respectively. In addition, equilibrium moisture content and water absorption decreased with the increase in thermal pretreatment temperature and duration. Moreover, the thermal treatment temperature was more important than duration on the investigated properties.
A aprendizagem na área de Nutrição Materno-Infantil por meio de casos clínicos como alternativa às aulas práticas
Authors: CAMATARI F. O. S. , VILAS BOAS Anderson Camatari , ARRUDA S. M.
Published: October 2023

The use of active learning methods combined with the early insertion of students in the activities of professional daylife, becomes a potential alternative to reduce the dichotomy between theory and practice. In the Maternal-Child Nutrition course of a Nutrition graduation, due to the impossibility of practical classes and the contact with the public / patient due to the social distance necessary to fight the pandemic of COVID-19, an alternative found was making an activity, in remote format, to simulate a clinical case. With the objective of identifying which Strands of Scientific Learning (FAC) were present in the speeches of the students during this activity, this research found the following FAC: interest, understanding of knowledge, scientific thinking, self identification as a professional; which shows that the use of clinical cases can be made to bring students closer to the public/patients, being an alternative that minimizes the insecurity of students, in face-to-face care in the future.
Avaliação da Transformação da Percepção Ambiental sobre os Impactos Ambientais utilizando a Ferramenta Pegada Ecológica
Authors: BECKMANN Lilian Janine de Barros , DUTRA C. M.
Published: October 2023

The environmental theme has been discussed at different levels of education, often decontextualized from the reality in which students live and end up becoming inefficient. This article aims to assess the change in environmental perception after the Ecological Footprint activity was carried out by undergraduate students in the Natural Sciences Course of a university in southern Brazil. The same questionnaire was applied before and after the intervention, consisting of questions that aim to assess the impact perceived by students in relation to daily lifestyle and consumption activities. The collected data were analyzed through content analysis and statistical analysis. Word cloud was used to facilitate the feedback of the results to the participants. For the discursive questions, there was an increase in the answers and we obtained new codes. Regarding objective questions, there was an increasing trend observed in all questions in the post-intervention period. These results indicate that the ecological footprint constitutes a pedagogical tool with an environmental approach capable of modifying the environmental perception of the participants.
Os estudos sobre Alfabetização Científica, com um olhar sobre a temática meio ambiente, nos anos iniciais do Brasil: uma revisão sistemática
Authors: OLIVEIRA F. D. , BAGESTERO P. S. P. , PUNTEL R. L. , ROOS Daniel Henrique
Published: October 2023

The present study consists of a systematic review and aimed to investigate, in the national academic production, how scientific literacy is portrayed in the early years, as well as to verify the forms of articulation between CA and the environment theme. The CAPES/MEC Journal Portal database was used as a source of information. The search was performed following the guidelines set out in the Cochrane Collaboration Manual (2011). As a result, we found 127 articles and after applying the exclusion and inclusion criteria, 20 works were selected, related to the descriptors “Scientific Literacy”, “Initial Years” and “Science Teaching”. Bardin's (2016) content analysis was used, from which categories emerged focusing on teachers, students and guiding documents. It was found that research focused on CA still lacks studies focused on the early years. In addition, most studies had students as the focus of the study, with a predominance of practical interventions. When the focus of the work was on the teachers, most of the articles addressed the conceptions that they have of CA. On the other hand, studies on how AC/Environment is addressed in the guiding documents pointed out the gaps and inconsistencies of public policies. Due to the number of mentions (70% of the articles evaluated), it was possible to link the environment theme to CA, since environmental topics act as facilitators of the students' scientific literacy process.
Antioxidant Activities, Phenolic Compounds and Organic Acids of Raw and Boiled Berries of Solanum Torvum Swartz From Eastern Côte d’Ivoire
Authors: Kouadio Eugène Jean Parfait , Kouadio Kouakou , Adingra Kouassi Martial-Didier , Kouadio Martin
Published: October 2023

Berries of solanum torvum, referred to as wild eggplant, are widely consumed in eastern Côte d'Ivoire in boiled form in sauces or soups. This study aimed to evaluate the antioxidant potential of these fruits through the estimation of antioxidant capacities of the extracts, identification and quantification of phenolic compounds and organic acids of raw berries and boiled berries to gauge the influence of this cooking. Results showed that boiling caused a considerable decrease in the antioxidant capacity of S. torvum berry extracts. By DPPH scavenging, the effective concentration (EC50) value of extract increased from 20.00 to 42.20 µg/mL, respectively for raw and boiled berries. Regarding EC50 values for antioxidant activities via FRAP, the values of 75.10 and 87.20 µg/mL were obtained, respectively for raw and boiled berries extract. In terms of phenolic compounds, the most predominant were catechin and gallic acid with respective contents of 1.06 and 0.86 mg/kg in the raw berries; 0.86 and 0.71 mg/kg in boiled berries, demonstrating the decrease in levels of these compounds by boiling. Organic acids showed the same decreasing trend during boiling. However, using cooking water when preparing soups or sauces could minimize these losses. In addition to this, one could consider other cooking methods such as steaming to better ensure nutrient retention
Variation of Pectin and Sugar Concentration on The Characteristic of Passion Fruit Gummy Candy
Authors: Anjliany Meysin , Nabilah Tri Adelti , Syafutri Merynda Indriyani
Published: October 2023

Gummy candy is a type of soft candy who made from juice and gel-forming materials. The objective of this research was to determine the effect of variation of pectin and sugar concentration on physical and chemical characteristics of passion fruit (Passiflora edulis) gummy candies. The research using factorial completely randomized design with two factors, namely concentration variation of pectin (1%, 1,5%, 2%) and concentration variation of sugar (30%, 40%, 50%). The observed parameters included physical characteristics (color, elasticity) and chemical characteristics (water content, ash content, pH, vitamin C, reducing sugar content, total acid). The result showed that concentration of pectin significantly affected on color (lightness, redness, yellowness), elasticity, water, ash, vitamin C, reducing sugar content, and total acid content, where as concentration of sugar significantly affected on color (lightness, yellowness), elasticity, water, ash, pH, vitamin C, reducing sugar content, and total acid content. The interaction affected significantly on elasticity, water, reducing sugar content, and total acid content. A3B2 treatment (pectin concentration 2% and sugar concentration 40%) was the best treatment based on parameters of water content (17.41%), ash content (1.06%), and reducing sugar content (8.28%).
Continuity of Care: A Primer for Family Medicine Residencies
Authors: Garrison Gregory M. , Meunier Matthew R. , Boswell Christopher L. , Greenwood Jason D. , Nordin Terri , Angstman Kurt B.
Published: October 2023

Continuity of care has been an identifying characteristic of family medicine since its inception and is an essential ingredient for high-functioning health care teams. Many benefits, including the quadruple aim of enhancing patient experience, improving population health, reducing costs, and improving care team well-being, are ascribed to continuity of care. In 2023, the Accreditation Council for Graduate Medical Education (ACGME) added two new continuity requirements—annual patient-sided continuity and annual resident-sided continuity—in family medicine training programs.
This article reviews continuity of care as it applies to family medicine training programs. We discuss the various types of continuity and issues surrounding the measurement of continuity. A generally agreed upon definition of patient-sided and resident-sided continuity is presented to allow programs to begin to collect the necessary data. Especially within resident training programs, intricacies associated with maintaining continuity of care, such as empanelment, resident turnover, and scheduling, are discussed. The importance of right-sizing resident panels is highlighted, and a mechanism for accomplishing this is presented.
The recent ACGME requirements represent a cultural shift from measuring resident experience based on volume to measuring resident continuity. This cultural shift forces family medicine training programs to adapt their various systems, policies, and procedures to emphasize continuity. We hope this manuscript’s review of several facets of contuinuity, some unique to training programs, helps programs ensure compliance with the ACGME requirements.
Enantiomeric and Monoaminergic Contributions to Methamphetamine's Bidirectional Effects on Fentanyl-Depressed Respiration in Mice
Authors: Elder Harrison , Walentiny David , Beardsley Patrick
Published: October 2023

Rationale: Fentanyl remains the primary cause of fatal overdoses, and
its co-use with methamphetamine (METH) is a growing concern. The optical
isomers of METH, dextromethamphetamine (d-METH) and levomethamphetamine
(l-METH), differ substantially in dose expression and thus may
differentially contribute to the racemate’s bidirectional effects.
Furthermore, it is unknown which of METH’s monoamine (MA) receptor
mechanisms mediate these respiratory effects. Thus, systematic
evaluation of monoamine receptor selective agents may identify treatment
targets for OIRD. Methods: The two optical isomers of METH, d-METH and
l-METH, were tested in adult male mice to determine their effects on
basal and fentanyl-depressed minute volume (MVb; i.e., respiratory
frequency x tidal volum) using whole-body plethysmography. Next, six
selective agonists at MA receptors involved in METH’s activity
[phenylephrine (PNE; α1), clonidine (CLON; α2), SKF-82958 (SKF; D1),
quinpirole (QPR; D2), 8-OH-DPAT (8-OH; 5HT1A), and DOI (5HT2)] were
singly tested on basal MVb, and then in combination with fentanyl.
Results: d-METH elevated MVb and l-METH decreased MVb. Under
fentanyl-depressed conditions, the bidirectional effects of racemic METH
were recreated by d-METH while l-METH significantly exacerbated OIRD at
1.0 and 3.0 mg/kg. MVb was dose-dependently increased by PNE and SKF and
decreased by CLON and QPR. Neither 8-OH nor DOI altered basal MVb. Under
fentanyl-depressed conditions, SKF transiently elevated MVb, while PNE
more persistently increased it, while DOI transiently increased MVb, and
8-OH decreased MVb. Conclusions: d-METH and l-METH differentially
contribute to the bidirectional respiratory modulation observed with the
racemate and selective activation of MA receptors altered basal
respiration and OIRD.
Antarctica’s Hidden Mycoviral Treasures in Fungi Isolated from Mosses: A First Genomic Approach
Authors: Victória Filipe de Carvalho , Nobre Steffany Virgolino Araújo , Andrade Guilherme Afonso Kessler de , Metz Geferson Fernando , Lucini Fabíola , Albuquerque Margéli Pereira de
Published: October 2023

This study investigates the presence of mycoviruses in Antarctic fungi
and elucidates their evolutionary relationships. To achieve this, we
aligned mycoviral gene sequences with genomes of previously sequenced
Antarctic endophytic fungi, made available by our research group and
accessible via JGI. Our findings reveal that the most prevalent genetic
regions in all endophytic fungi are homologous to Partitiviruses. These
regions display evidence of positive selection pressure, suggesting
genetic diversity and the accumulation of non-synonymous mutations. This
phenomenon implies a crucial role for these regions in the adaptation
and survival of these fungi in the challenging Antarctic ecosystems. The
presence of mycoviruses in Antarctic endophytic fungi may indicate
shared survival strategies between the virus and its host, shedding
light on their evolutionary dynamics. This study underscores the
significance of exploring mycoviruses within endophytic fungi and their
contributions to genetic diversity. Future research avenues could delve
into the functional implications of these conserved mycoviral genetic
regions in Antarctic endophytic fungi, providing a comprehensive
understanding of this intriguing symbiotic association.
The impact of ultrasound-guided high-intensity focused ultrasound for uterine fibroid on ovarian reserve and quality of life: A prospective cohort study
Authors: Gu Wei , Yuan Jiangjing , Zhou Yun , Li Yuhong , Wang Yudong
Published: October 2023

Objective: To evaluate variation of anti-Müllerian hormone
(AMH) levels and quality of life in women with uterine fibroids after
the treatment of ultrasound-guided high-intensity focused ultrasound
(USgHIFU). Design: Prospective cohort study. Setting:
International Peace Maternity and Child Health Hospital, Shanghai,
China. Population: A total of 69 patients with uterine fibroids
from October 2018 to November 2021. Methods: AMH levels, score
of uterine fibroid symptom and quality of life (UFS-QOL) and fibroid
volume before and 1-, 3-, 6-month after the USgHIFU treatment were
analyzed. Correlations between AMH levels and age, fibroid types,
fibroid location were assessed. Main outcome measures:
Anti-Müllerian hormone levels and score of UFS-QOL. Results: Of
all the 69 patients enrolled in this study, 54 patients were finally
analyzed. UFS-QOL scores at baseline, 1-month and 6-month after
treatment were 70 (50.75-87.50), 57(44.75-80.00), and 52(40.75-69.00),
respectively ( p < 0.001). Reduction of fibroids volume
rate increased significantly at 3-month compared to 1-month follow-up (
p < 0.001) and no significant change was observed
between the 3-month and 6-month follow-up ( p >
0.99). The median AMH levels (ng/ml) before and at 1-, 3- and 6-month
after treatment were 1.22 (0.16-3.28), 1.12 (0.18-2.52), 1.15
(0.19-2.08) and 1.18 (0.36-2.43), respectively，there was no significant
difference in AMH levels among the groups ( p = 0.2), and no
significant difference in subsequent subgroup analysis stratified by age
( p > 0.05). Multivariate linear regression analyses
showed that women age was significantly and independently associated
with AMH levels in related influencing factors. Conclusions:
The short-term and long-term follow-up of USgHIFU in the treatment of
Uterine fibroid shows that the treatment can significantly improve the
quality of life without adverse effects on ovarian function.
Atroposelective synthesis of 2-arylindoles via chiral phosphoric acid-catalyzed direct amination of indoles
Authors: Bao Wen , Chen Ye-Hui , Liu Yu-Wei , Xiang Shao-Hua , Tan Bin
Published: October 2023

Indole-based atropisomers are a very important class of axially chiral
compounds. However, the atroposelective synthesis of axially chiral
2-arylindole remains largely unexplored. In this study, we report the
successful synthesis of atropisomeric 2-arylindoles using direct
amination of indoles with p-quinonediimines in the presence of chiral
phosphoric acid as a catalyst. Quinonediimine acts as an aminating
reagent through formal polarity inversion of imine. The malonate group
on the 2-aryl of 2-indoles was found to be essential for high
enantioselectivity of the products. This could be due to the additional
interaction between the ester group and the catalyst, as well as the
intramolecular hydrogen bonding. Our findings provide a new strategy for
the asymmetric construction of 2-arylindole atropisomers.
SaveBirds.app: A web tool for analyzing the North American Breeding Bird Survey data to enhance conservation in protected areas
Authors: Green Robert , Rezaee Mostafa M. , Shojaei Hamid , Gregory Andrew
Published: October 2023

Initiated in 1966, the Breeding Bird Survey (BBS) has gathered a large
collection of data on 800 avian species from 300,000 sites across North
America. Managed collaboratively by the United States Geological Survey
(USGS) and the Geological Survey of Canada (GSC), this dataset helps in
the ecological assessment of 40,000 protected areas (PAs) in the region.
To unlock this data’s full potential, we present the SaveBirds.app—a
specialized web application designed to explore the extensive BBS
dataset. The platform empowers various stakeholders, including
ecologists, wildlife managers, and policymakers, by providing them with
custom analytical tools to address critical conservation questions.
SaveBirds.app offers three core functionalities: 1) Metrics, for
calculating species-specific Rarity Scores and route-based Species
Richness (SR), Rarity-Weighted Richness (RWR), and Shannon diversity ( H
′ ) based on customizable parameters; 2) Presence/Absence Data, for
mapping the spatio-temporal distribution of selected bird species; and
3) Bird Atlas Generator, the first publicly available tool equipped with
a pre-built ArcGIS model, enabling users to create customized bird
atlases. SaveBirds.app represents a pivotal advancement in using
long-term ecological datasets, providing strong analytics to inform and
prioritize conservation initiatives in North America.
A review of the biomarkers with the potential to predict poor prognosis of neuroblastoma
Authors: Li Le , Lin Minhua , Lv Ziyin , Lin Ting , Liao Cailing , Ye Chenle , Huang Yunxia , Yan Mi
Published: October 2023

Neuroblastoma is the most common extracranial tumor in children, and
some children have already metastasized throughout the body when
diagnosed, rapidly progressing to death. This article summarizes
existing research findings and indicators for predicting poor prognosis,
aiming to provide reference for clinical treatment and promote the
research development.
QSAR, Molecular Docking, and Molecular Dynamic Simulation Studies of ACE2 Inhibitors for the Development of Drugs Against SARS-CoV-2
Authors: Basmenj Esmaeil Roohparvar , Arastonejad Mahshid , Ghiabi Shamim , Zare Somayeh , Omidvar Behnoosh , KhalatbariLimaki Mahdi
Published: October 2023

The global pandemic of coronavirus disease is attributable to a newly
emerged coronavirus targeting the respiratory system. A pivotal approach
in addressing this pandemic involves the search for pharmaceutical
compounds capable of impeding the essential viral proteins necessary for
viral replication and infection. Since ACE2 enzyme acts as the primary
cellular entry point for certain coronaviruses, inhibiting it can play a
crucial role in our efforts to combat these viruses. In this study, we
employed a range of ACE2 inhibitors to conduct quantitative
structure-activity relationship (QSAR) analyses, molecular docking
analysis, and molecular dynamics simulations. The QSAR investigation,
which relies on the Stepwise-MLR model developed in this study, provides
a conceptual framework for improving the effectiveness of ACE2 inhibitor
compounds. The molecular docking analysis revealed possible binding
locations of the compounds within the ACE2 (PDB ID=6m0j). A 150-ns
molecular dynamics simulation was conducted to validate the
conformational stability of the top three promising compounds when bound
to SARS-CoV-2-ACE2 complex. The findings indicated that all three
compounds consistently occupied the specific binding pocket of the
target and established numerous hydrogen bonds throughout the
simulation, aligning with the results of the molecular docking studies.
This research could help identify new leads for the development of novel
anti-viral drugs against SARS-CoV-2.
Effect of 24-h and 36-h Acute Total Sleep Deprivation on Human Attention: An Activation Likelihood Estimation Meta-analysis
Authors: Chen Jie , Song Tao , Peng Ziyi , Zhong Xiao , Lian Jie , Xu Lin , Shao Yongcong
Published: October 2023

Abstract Background: Currently, there is no consensus on the effect of
24-h and 36-h acute total sleep deprivation (ATSD) on human attention.
This activation likelihood estimation (ALE) meta-analysis aimed to
compare the different patterns of functional magnetic resonance imaging
(fMRI activation) between 24-h and 36-h ATSD across attention tasks.
Methods: We used GingerALE 2.3.6 software to conduct coordinate-based
ALE meta-analysis. The literature related to sleep deprivation,
attention, and neuroimaging was searched in four databases: CNKI,
PubMed, Web of Science, and PsycINFO from November 1980 to March 2023.
Results: We included 16 fMRI-related articles, with 383 participants and
95 foci. The findings revealed that 24-h ATSD and 36-h ATSD may impair
different brain areas. After 24-h ATSD, there was significantly reduced
brain activation in the parietal-occipital attention lobes and the
salience network, including the bilateral superior parietal lobule,
right inferior occipital gyrus, and left insula. Increased activation
was observed in the sub-lobar regions, including the bilateral thalamus.
After 36-h ATSD, there was significantly reduced activation in the
frontoparietal attention network, including the left middle frontal
gyrus and the right inferior frontal gyrus. Conclusions: This ALE
meta-analysis revealed that prolonged ATSD leads to more severe
temporary brain damage and a cumulative decrease in the external stimuli
captured by humans. This primarily affects the
frontal-parietal-occipital attention network and the salience network.
Thalamic activation may compensate for dysfunction in the
parietal-occipital attention network after 24-h ATSD. Sleep deprivation
duration plays a crucial role in the extent of attention impairment.
An existence result for implicit functional equations
Authors: Golshan Hamid Mottaghi
Published: October 2023

In this article, we attempt to provide a more general method based on
Petryshyn’s fixed-point theorem to ensure the existence of solutions to
implicit functional equations. These implicit functional equations
include fractional, non-fractional, (fractional) stochastic integral
equations, etc., and any combination of them in C( I).
Some results regarding the existence of fixed points in implicit
functional integral equations will be reviewed in the literature. We
show that this general result unifies and improves many of the main
results in the literature. To illustrate that our approach is more
general than other methods, we present some concrete examples. Also, we
apply our method to create new functional equations in practice and
check the existence of solutions.
An experimental approach to examine behavior and brain activity during decision-making under risk as compared to ambiguity
Authors: Albrecht Benjamin , Hewig Johannes , Mussel Patrick , Welpe Isabell , Stanton Angela , Miltner Wolfgang
Published: October 2023

Neural correlates of decisions under risk and under ambiguity have been
examined for several decades. In the current study, we focus on a
neglected aspect that is a potential confounding of the average risk of
alternatives in a trial, the average magnitude of the outcomes, and the
difference in risk between the two alternatives. We present an
experimental approach to solve this problem here and explicitly separate
risk and ambiguity. In the present fMRI-study with 20 participants, we
created different levels of risk and ambiguity to investigate their
effects on behavior and brain activation. In a first experimental block,
decisions with mixed-risk options (one high-risk option paired with one
low-risk option) were compared to decisions with two high-risk or two
low-risk options in terms of the effects on decision-making and neural
activity. The second block consisted of the same risk levels crossed
with high and low ambiguity by withholding information about the
probabilities of the outcomes. During mixed-risk trials participants
made cautious decision significantly more often. This effect was
strongest during mixed trials with high ambiguity in the second block.
In addition, risk behavior of subjects was correlated with the
subjective importance of the amount of potential monetary losses or wins
and the related probabilities. The fMRI results revealed activation of
the dorsal anterior cingulate cortex (dACC), the insula, and the
orbitofrontal cortex (OFC) during mixed risk trials without ambiguity.
In contrast, activation of the amygdala was specifically present during
mixed-risk trials with high ambiguity.
pcvr: An R package and tutorials for guided statistical analysis of plant phenotyping data
Authors: Sumner Josh , Fahlgren Noah , Murphy Katherine M
Published: October 2023

PlantCV is a Python-based image analysis tool that lowers the barrier to entry for complex image analysis workflows in plant phenotyping. To provide support for subsequent analysis steps of measured trait data we have developed pcvr, an R package to assist in common plant phenotyping analyses. The goal of pcvr is to make common statistical analyses both easier and more consistent and to lower the barrier to entry for useful Bayesian methods. Here we demonstrate three pieces of a possible analysis covering single value trait analysis, longitudinal modeling, and multi-value trait analysis.
Strong El Niño events lead to robust multi-year ENSO predictability
Authors: Lenssen Nathan , DiNezio Pedro , Goddard Lisa , Deser Clara , Kushnir Yochanan , Mason Simon , Newman Matthew , Okumura Yuko M
Published: October 2023

The El Niño-Southern Oscillation (ENSO) phenomenon – the dominant
source of climate variability on seasonal to multi-year timescales – is
predictable a few seasons in advance. Forecast skill at longer
multi-year timescales has been found in a few models and forecast
systems, but the robustness of this predictability across models has not
been firmly established owing to the cost of running dynamical model
predictions at longer lead times. In this study, we use a massive
collection of multi-model hindcasts performed using model analogs to
show that multi-year ENSO predictability is robust across models and
arises predominantly due to skillful prediction of multi-year La Niña
events following strong El Niño events.
Portable High-Throughput Digital Confocal Microscope for Early Disease Detection
Authors: Zhao Tianzhang , Goodnight Morgan , Telenko Darcy , Jin Jian
Published: October 2023

Northern corn leaf blight (NCLB), caused by the fungus
Setosphaeira turcica, is one of the most devastating corn
diseases in the U.S. and has reduced Indiana yields for the last decade.
NCLB can cause significant yield loss if conditions are favorable for
early disease onset near tassel/silk (VT/R1) growth stages. Therefore,
early detection and timely disease management are essential to mitigate
yield loss and optimize fungicide applications. Remote sensing
technologies have broad applications in plant phenotyping areas, but
they present specific challenges in the early detection of diseases,
particularly for diseases where lesions first appear in the lower crop
canopy. While laboratories can provide more accurate results than remote
sensing, their throughput is limited. To achieve higher throughput and
more precise measurements for improved early disease detection, a
portable digital microscope prototype has been developed. Distinct from
other portable microscopes, this device can detect pathogens and
directly monitor their growth on live plant tissue due to its 1 nm
spatial resolution. Moreover, it is built with a confocal configuration
to capture high-resolution reflective images, thereby outperforming
traditional microscopes in throughput. This feature also permits
repetitive non-destructible measurements on a single leaf and
accommodates leaves of varying thicknesses. By analyzing time-series
images of infected leaves, this portable digital microscope has proven
its ability to detect spores and germ tubes of the pathogen before
symptoms are visibly apparent. It has the potential to effectively
bridge the gap between precision and throughput, providing critical
insights into disease management.
3D Root Structure Modeling and Analysis Using Close-Range Photo Scanning
Authors: Carpenter Joshua , Bogati Sujata , Jung Jinha , Wang Diane
Published: October 2023

This work presents a methodology for creating digital twins of root
system architecture (RSA) that can be used for studying the phenotypic
variation in RSA. Growing populations demand increased global food
production. To sustainably support this increase, crops must be
developed to flourish in nutrient-depleted soils. Since the
effectiveness of nutrient uptake is determined by plant rooting system
dynamics, much focus has been placed on studying RSA across species and
varieties. A particularly effective tool for studying RSA in 3D has been
X-ray computer tomography (CT). However, this technology is cost
prohibitive and cannot model field-grown samples. A far more
cost-effective technology is close-range photogrammetric scanning, which
uses multiple 2D images to reconstruct 3D point clouds of RSA. This
project develops a point cloud processing pipeline that takes
high-density point clouds of soybean rooting structures and generates 3D
RSA models. These digital twins are then used as the basis for analyzing
the phenotypic variation of the geometric and biometric features of the
RSA. We believe this digital twin construction and analysis pipeline
will increase the impact of RSA research in support of sustainable food
production in nutrient-depleted areas of the world.
Detecting Invasive Shrub Species by Utilizing High-Density Airborne LiDAR Data and Spectral Image
Authors: Choi Dennis Heejoon , Morton Isaac S. , Darling Lindsay E. , Wang Jianmin , Thapa Bina , Fei Songlin , Hardiman Brady S.
Published: October 2023

In the Chicago region, common buckthorn and bush honeysuckle stand out
as dominant invasive species, accounting for over 40% of the regional
forest coverage. Their proliferation leads to the formation of dense
thickets that hinder sunlight penetration, resulting in diminished
native plant diversity in the understory. Accurate detection of these
species across this region is essential for the effective management of
these invasives. Airborne LiDAR datasets show strong potential in
detecting the distinctive structural patterns created by these thickets.
Previous studies have utilized multi-temporal spectral imagery to track
the phenological shifts of invasive species. However, in the Chicago
region, it is difficult to employ multi-temporal spectral imagery due to
substantial cloud cover during early spring and late autumn.
Consequently, our research adopted the use of dense airborne LiDAR
datasets specific to the Chicago area. Preliminary results indicate that
invaded plots manifest less complex vertical structure, higher
vegetation area index in the subcanopy, and lower NDVI values compared
to their non-invaded plots. Notably, LiDAR-derived metrics surpass
NDVI-based ones in estimation. Using binomial logistic regression (with
an AUC of 0.97), we assessed the presence and absence of these invasive
species across Chicago’s forests, achieving an accuracy rate of 0.92.
Alarmingly, our findings suggest that these invasive species have
affected over 75% of the forest patches in Chicago. In summary, our
research highlights the important role of LiDAR datasets in
regional-scale invasive species detection.
Nondestructive high-throughput screening of wheat spike and grain
Authors: Hufnagel Eva , Weule Mareike , Claussen Joelle , Gerth Stefan
Published: October 2023

Given the changing environmental conditions, understanding internal
mechanisms of crops and their interaction with the environment in
abiotic stress conditions is very important. To estimate the yield of
e.g. wheat, spike and grain traits are used for the selection of
resilient genotypes for further breeding programs. Typically, the
extraction of these traits is laborious and destructive. With automated
X-ray technology a non-destructive screening of spikes can be conducted
faster and more accurate. Furthermore, the technology allows extracting
additional traits such as center of mass and aspect ratio of each grain,
together with the position of the grain within the spike.

We present the analysis of 203 wheat accessions carried out using a
portable computed-tomography system (CT). The wheat plants were exposed
to either drought or combined drought and heat stress. With the EarS
algorithm, spike traits were analyzed with an accuracy of 95-99%. The
system scanned 4 spikes simultaneously, which resulted in a
scanning-time of 7 minutes per spike. To enable a high-throughput
acquisition and comparison of wheat traits, we present the required
steps for automation. Thus, together with PhenoKey, we developed an
automated CT-system with integrated conveyor belt for The Plant
Accelerator®, University of Adelaide. This system examines spikes and
grains with high throughput. The system has space for 35 spike holders,
each of which can carry 30 spikes. This allows a scanning time of 13
seconds per spike. Combined with an automatic data post processing each
grain can be identified and linked to the corresponding genotype.
Modeling the Impact of Drought and Heat Stress on Maize Anthesis-Silking Interval
Authors: Nolta Bethany , Wheeler Carolina , Kirkole Atharva , Thompson Addie
Published: October 2023

Understanding and enhancing plant resilience traits in maize is critical
for ensuring consistent yields in the face of challenging conditions
such as drought, disease, and insect pressure. The adoption of
drought-resistant and insect-resistant maize varieties has already
proven highly beneficial to growers, sparking further interest in
uncovering the precise genetic and phenomic factors associated with
increased resilience. This study utilized genetic, phenomic, and
environmental data collected by Genomes to Fields teams across diverse
regions of the United States. These regions exhibited a wide range of
climatic conditions, from optimal to stressful, including drought and
heat challenges. Leveraging advanced Machine Learning techniques, the
study aimed to predict the impact of drought and heat stress on the
anthesis-silking interval, a crucial trait influencing yield, and to
identify the most effective combination of phenotypes for enhancing
drought resilience in maize.
The Relationship of Chlorophyll Concentration and Canopy Greenness with Maize Yield
Authors: Singh Iha , Sepanak Isabella , Thompson Addie
Published: October 2023

Maximizing crop yield is a central goal in agriculture and plant
breeding. Several phenotypic traits, including leaf chlorophyll content
and canopy greenness, can help predict yield across different varieties.
In this study, we aimed to quantify the relationship between leaf
chlorophyll concentration, canopy greenness, and crop yield within the
Genomes to Fields trials. Our goal was to assess the correlation and
enhance predictive modeling between these factors, evaluating the
effectiveness of canopy cover and spectral reflectance in predicting
yield. We accomplished this by collecting chlorophyll data from multiple
leaves within each field plot and utilizing imagery captured by
unoccupied aerial systems. This image data provided RGB and
multispectral reflectance information on a per-plot basis throughout the
growing season, allowing us to model patterns linking chlorophyll
concentration and yield for each plot. We integrated data from these two
methods with genotypic data from the same maize varieties to explore the
fundamental relationships between chlorophyll levels, canopy greenness,
and crop yield.
Combining Solar-Induced Chlorophyll Fluorescence (SIF) with Functional Phenotyping Systems: Assessing Limitations in Estimating Photosynthesis Under Stress
Authors: Mayo Amir , Moshelion Menachem , Liran Oded
Published: October 2023

High-throughput measurements of photosynthesis across various
cultivars/genomes and environmental conditions are crucial for
understanding plant photosynthetic adaptability. Advanced remote sensing
techniques, such as solar-induced chlorophyll fluorescence (SIF),
facilitate field-based, high-throughput photosynthesis assessments. Our
research explored whether combining SIF measurements with whole-plant
water relation data during standardized drought experiments could
effectively quantify photosynthetic activity and early-stage water
stress detection. We employed the functional-phenotyping PlantArray
system for controlled drought treatment and simultaneous monitoring of
growth and water balance in 72 tomato plants from four different
introgression lines (ILs).

We introduced a SIF-derived index, electron transport rate (RS-ETRi),
and found it negatively correlated with whole-plant stomatal conductance
(Gsc) under normal conditions, and positively during drought.
Surprisingly, no substantial links were found between SIF and either
plant biomass or Gsc. Among various vegetation indices (VIs), SIF 687
was the earliest drought indicator but presented detection challenges
due to its weak signal. Interestingly, while SIF parameters failed to
differentiate between ILs, significant differences were observed through
gravimetric water-relation measurements.

Our findings suggest that while SIF is a valuable tool in photosynthesis
studies, its correlation with photosynthetic activity is complex. Thus,
using SIF alone to quantify photosynthetic activity might be an
oversimplification. We concluded that SIF does not offer advantages over
traditional methods in detecting physiological variations among ILs,
highlighting the complexity and limitations of SIF in plant
physiological research.
PyBrOpS -Python Breeding Optimizer and Simulator
Authors: Shrote Robert Z , Thompson Addie M
Published: October 2023

Choosing a suitable breeding strategy is essential to the success of a plant breeding program. Simulations are an important tool that allow plant breeders to propose and assess the merits of alternative breeding strategies. The Python package PyBrOpS provides a highly flexible and modular framework to make optimized breeding selection decisions and perform stochastic simulations of plant breeding programs. PyBrOpS utilizes a customizable scripting-based approach to constructing breeding simulations and optimizations. Through the use of software interfaces that allow for extensibility, the user may implement custom PyBrOpS modules that provide additional functionality. PyBrOpS offers pre-built subroutines for selection strategies such as conventional genomic selection, weighted genomic selection, optimal contribution selection, optimal population value selection, and optimal haploid value selection. Additionally, PyBrOpS is capable of both single-and multi-trait selection. For multi-trait selection scenarios, PyBrOpS offers the novel capability of mapping trade-off frontiers through the use of multi-objective evolutionary algorithms. Here, we describe the main features of PyBrOpS and provide example use cases for breeding program simulation and optimization.
Digital Twins Models for Crop Phenotyping, Management and Yield Forecasting
Authors: Landivar-Bowles Juan , Pal Pankaj , Bhandari Mahendra , Landivar-Scott Jose Luis
Published: October 2023

Phenotype characterization is an exciting new field that links
agriculture and data science. Thanks to advances in remote sensing and
artificial intelligence, we can now accurately quantify field-scale
phenotypic information and integrate this big data into predictive and
prescriptive management tools.

Our past work has shown that phenotypic information measured from UAS is
more precise and reliable than manual field measurements. In addition,
we have shown that the vast size of this data can outweigh the
complexity of the problem, to the point where even a simpler algorithm
can outperform a sophisticated algorithm when big enough training data
are available. This is because the big data captures even very
infrequent aspects of the problem of interest, which can be modeled with
simple logics.

The availability of UAS data makes it possible to develop digital twin
models to forecast future plant growth and develop in-season management
plans. A digital twin model is a virtual representation of real-world
entities and processes. These models use early growth patterns of a crop
as input to artificial intelligence algorithms so that the algorithms
can predict crop performance during the next 10, 20, or 30 days ahead of
the last data point collected by the UAS. Crop growth features
forecasting results can be useful for the management of irrigation,
growth regulators, maturity of the crops, and to obtain early-season
yield estimation.
Root Phenotyping Using Pose Estimation
Authors: Berrigan Elizabeth Marie , Wang Lin , Carrillo Hannah , Echegoyen Kimberly , Kappes Mikayla , Torres Jorge , Ai-Perreira Angel , McCoy Erica , Shane Emily , Copeland Charles , Ragel Lauren , Georgousakis Charidimos , Lee Sanghwa , Reynolds Dawn , Talgo Avery , Gonzalez Juan , Zhang Ling , Rajurkar Ashish , Ruiz Michel , Daniels Erin , Maree Liezl , Pariyar Shree , Busch Wolfgang , Pereira Talmo D.
Published: October 2023

Image segmentation is commonly used to estimate the location and shape
of plants and their external structures. Segmentation masks are then
used to localize landmarks of interest and compute other geometric
features that correspond to the plant’s phenotype. Despite its
prevalence, segmentation-based approaches are laborious (requiring
extensive annotation to train), and error-prone (derived geometric
features are sensitive to instance mask integrity). Here we present a
segmentation-free approach which leverages deep learning-based landmark
detection and grouping, also known as pose estimation. We use a tool
originally developed for animal motion capture called SLEAP (Social LEAP
Estimates Animal Poses) to automate the detection of distinct
morphological landmarks on plant roots. Using high-throughput
phenotyping method Root Architecture 3-D Imaging Cylinder (RADICYL)
across multiple species, we show that our approach can reliably and
efficiently recover root system topology at greater accuracy, faster
speed, and with fewer annotated samples than segmentation-based
approaches. In order to make use of this landmark-based representation
for root phenotyping, we developed a Python library (sleap-roots
) for trait extraction directly comparable to existing
segmentation-based analysis software. We show that landmark-derived root
traits are highly accurate and can be used for common downstream tasks
including genotype classification and unsupervised trait mapping.
Altogether, this work establishes the validity and advantages of pose
estimation-based plant phenotyping. To facilitate adoption of this
easy-to-use tool and to encourage further development, we
make sleap-roots ,  all training data, models, and trait
extraction code available
at: https://github.com/talmolab/sleap-roots.
Smartphone-Based Tree Diameter Measurement Using Single Snapshot
Authors: Xiang Wang , Zhang Song , Fei Songlin
Published: October 2023

This paper presents an inventive and precise methodology for measuring
tree diameters at specific heights, leveraging iPhones equipped with
light detection and ranging (LiDAR) and red, green, and blue (RGB)
sensors. Initially, a single snapshot of the tree is captured,
incorporating depth and RGB images. Sparse LiDAR data is processed to
generate a dense 3D point cloud for each RGB pixel, allowing accurate
estimation of the tree trunk’s orientation. This raw 3D point cloud is
then standardized, ensuring consistency irrespective of the capture
angle. A specific band of transformed 3D points around the target height
is selected to estimate the initial diameter and the average distance
from the tree to the smartphone camera. To enhance accuracy, a
precomputed lookup table is utilized. Experimental results showcase the
method’s efficacy, achieving a measurement accuracy of approximately
1.12 cm in mean absolute error and 0.77 cm in root mean square error for
218 trees within a depth range of 0.2 m to 5 m, using an iPhone 13 Pro.
This proposed diameter estimation technique proves invaluable for
practical forest inventory applications, given its unmatched reliability
and precision. Forestry experts and researchers can significantly
benefit from this approach, revolutionizing the way tree measurements
are conducted in the field. The integration of smartphone technology
with advanced sensors marks a pivotal advancement in the realm of forest
assessment, paving the way for more accurate and efficient ecological
studies and resource management initiatives.
Health Spending Efficiency in Developing Asia
Authors: Bajaro Donna Faye , Jinjarak Yothin , Myoda Yuho , Park Donghyun , Quising Pilipinas
Published: October 2023

This study analyzes health spending efficiency in developing Asia. The result shows universal health coverage service coverage index and population density as key determinants of health spending efficiency. While East Asia has the highest average technical efficiency score, Caucasus and Central Asia has the highest average allocative efficiency score. Overall, there is significant potential for improving both technical and allocative efficiency in health-care expenditures across developing Asia.
SCOPE AND FINANCIAL IMPLICATIONS OF THE INTRODUCTION OF IFRS 9 USING THE EXAMPLE OF A COMMERCIAL BANK
Authors: Juszczyk Sławomir , Bartosiak Wioleta , Juszczyk Juliusz , Konieczny Robert , Palimonka Bartosz
Published: October 2023

The aim of the research was to identify the financial consequences of introducing IFRS 9 in a leading commercial bank in Poland. The research period was six years and covered the years 2015-2020. It was established, inter alia, that IFRS 9, compared to the previously applicable IAS 39, changed the method of measuring financial assets and thus led to changes in the balance sheet and financial results. The introduction of IFRS 9 also increased financial provisions for loans to be repaid in the bank's portfolio,