bluuebunny/crossref_metadata_2025 huggingface dataset:
Factor structure of Pre‐Loss Grief‐12 in caregivers of people living with dementia
Authors: Park Juyoung , Levine Hannah , Galvin James E.
Published: July 2022

Introduction

The objective was to develop and refine a version of the Prolonged‐Loss Grief‐12 (PG‐12) specific to caregivers of people living with dementia. Confirmatory factor analysis (CFA) was performed to test the fit of the data from the caregivers and to assess the factor structure of the PG‐12 in order to evaluate pre‐loss grief accurately by identifying relevant items and eliminating items that are not appropriate for caregivers of persons with dementia.

Methods

A total of 699 eligible caregivers of persons living with dementia (PLWDs) were recruited through relevant dementia associations and organizations. The e‐mail for recruitment provided potential participants with information about the study and detailed instructions on how to participate by following a link to the online survey. Secondary analysis was based on the survey data. CFA was conducted via the Full Information Maximum Likelihood estimation method to test the unidimensional model of PG‐12 in the study population. Standard procedures were used to establish the parameters in the factor loading, factor variance‐covariance, and uniqueness matrices.

Results

The initial model was modified to develop a better fitting model and to detect misfitting parameters in the PG‐12 by deleting irrelevant items for the PLWD's caregiver. The adjusted dementia‐specific 10‐item version (PG‐10‐D) had significantly improved fit indices. An overall assessment of fit indicated that the model adequately approximated the data. Factor loadings ranged from 0.53 to 0.85.

Discussion

We found that the dementia‐specific, unidimensional PG‐10‐D, modifying the original PG‐12, may be useful and parsimonious in assessing and quantifying pre‐loss grief in dementia caregivers. Future studies are needed to further test its validity and reliability.

Highlights

First study to evaluate a dementia‐specific 10‐item version (PG‐10‐D) of the Prolonged‐Loss Grief‐12 (PG‐12).

PG‐10‐D is useful in assessing and quantifying pre‐loss grief in caregivers.

PG‐10‐D could be an early identifier of caregivers at risk for pre‐loss grief.

PG‐10‐D could be the standard measure for effective intervention for caregivers.
Measurement of neurodegeneration using a multivariate early frame amyloid PET classifier
Authors: Matthews Dawn C. , Lukic Ana S. , Andrews Randolph D. , Wernick Miles N. , Strother Stephen C. , Schmidt Mark E. ,   for the Alzheimer's Disease Neuroimaging Initiative
Published: July 2022

Introduction

Amyloid measurement provides important confirmation of pathology for Alzheimer's disease (AD) clinical trials. However, many amyloid positive (Am+) early‐stage subjects do not worsen clinically during a clinical trial, and a neurodegenerative measure predictive of decline could provide critical information. Studies have shown correspondence between perfusion measured by early amyloid frames post‐tracer injection and fluorodeoxyglucose (FDG) positron emission tomography (PET), but with limitations in sensitivity. Multivariate machine learning approaches may offer a more sensitive means for detection of disease related changes as we have demonstrated with FDG.

Methods

Using summed dynamic florbetapir image frames acquired during the first 6 minutes post‐injection for 107 Alzheimer's Disease Neuroimaging Initiative subjects, we applied optimized machine learning to develop and test image classifiers aimed at measuring AD progression. Early frame amyloid (EFA) classification was compared to that of an independently developed FDG PET AD progression classifier by scoring the FDG scans of the same subjects at the same time point. Score distributions and correlation with clinical endpoints were compared to those obtained from FDG. Region of interest measures were compared between EFA and FDG to further understand discrimination performance.

Results

The EFA classifier produced a primary pattern similar to that of the FDG classifier whose expression correlated highly with the FDG pattern (R‐squared 0.71), discriminated cognitively normal (NL) amyloid negative (Am–) subjects from all Am+ groups, and that correlated in Am+ subjects with Mini‐Mental State Examination, Clinical Dementia Rating Sum of Boxes, and Alzheimer's Disease Assessment Scale–13‐item Cognitive subscale (R = 0.59, 0.63, 0.73) and with subsequent 24‐month changes in these measures (R = 0.67, 0.73, 0.50).

Discussion

Our results support the ability to use EFA with a multivariate machine learning–derived classifier to obtain a sensitive measure of AD‐related loss in neuronal function that correlates with FDG PET in preclinical and early prodromal stages as well as in late mild cognitive impairment and dementia.

Highlights

The summed initial post‐injection minutes of florbetapir positron emission tomography  correlate with fluorodeoxyglucose.

A machine learning classifier enabled sensitive detection of early prodromal Alzheimer's disease.

Early frame amyloid (EFA) classifier scores correlate with subsequent change in Mini‐Mental State Examination, Clinical Dementia Rating Sum of Boxes, and Alzheimer's Disease Assessment Scale–13‐item Cognitive subscale.

EFA classifier effect sizes and clinical prediction outperformed region of interest standardized uptake value ratio.

EFA classification may aid in stratifying patients to assess treatment effect.
Toxoplasma gondii clonal type III is the dominant genotype identified in Grenadian pigs
Authors: Chikweto Alfred , Alhassan Andy , Su Chunlei , Macpherson Calum , Bhaiyat Muhammad Iqbal , Dubey Jitender P.
Published: July 2022

Background

Toxoplasma gondii is a widespread zoonotic protozoan parasite capable of infecting all warm‐blooded animals. Although the genotypes of T. gondii in pigs have been reported worldwide, there is no information on the genotypes and diversity of T. gondii in pigs in Grenada, West Indies.

Objectives

The aims of the present study were to isolate, genotype and determine the diversity of T. gondii genotypes in pigs.

Methods

We carried out a modified agglutination test (MAT) on blood from 149 pig hearts collected from a local meat market. Myocardial tissue homogenate from pigs that tested positive for T. gondii was homogenized and inoculated into mice for isolation of the parasite. We collected mouse tissues and extracted DNA for genotyping based on 11 polymerase chain reaction‐restriction fragment length polymorphism markers (SAG1, SAG2, alt. SAG2, SAG 3, BTUB, GRA6, L358, PK1, C22‐8, C 29‐2 and Apico).

Results

Out of the 149 pig hearts, 31 (20.8%) tested positive for T. gondii on MAT. Bioassays in mice yielded 12 isolates designated TgpgGr1 to TgpgGr12. Molecular characterisation of T. gondii revealed four genotypes as follows: ToxoDB #2‐clonal type III (seven isolates); ToxoDB #7 (three isolates); ToxoDB #13 (one isolate); ToxoDB #30 (1 isolate). Overall, ToxoDB #2 was the most common (58%). Toxo database (DB) # 13, which causes interstitial pneumonia in affected mice, has also been reported.

Conclusion

The genetic diversity of T. gondii in pigs in Grenada is lower than that in other surrounding Caribbean areas.
Correction to: The Spread of Agriculture: Quantitative Laws in Prehistory?
Authors: Fort Joaquim
Published: July 2022

“The original version of chapter 2[“The Spread of Agriculture: Quantitative Laws in Prehistory?”] was previously published non-open access. It has now been changed to open access under a CC BY 4.0 license and the copyright holder updated to ‘The Author(s)’. The book has also been updated with this change.”
SDG-8: Decent Work and Economic Growth
Authors: Küfeoğlu Sinan
Published: July 2022

Economic growth can be defined by increasing consumption due to the increase in population and reaching production amounts to meet consumption with technological developments and governmental incentives. The correct placement of people in the production and consumption equation can be expressed as decent work. Although decent work and economic growth may seem like different terms at first glance, they are inseparable terms for each other. SDG-8, Decent Work and Economic Growth, aims to attain full and productive employment, as well as respectable work, for all women and men by 2030. This chapter presents the business models of 37 companies and use cases that employ emerging technologies and create value in SDG-8. We should highlight that one use case can be related to more than one SDG and it can make use of multiple emerging technologies.
SDG-11: Sustainable Cities and Communities
Authors: Küfeoğlu Sinan
Published: July 2022

City governance is vital for sustainable development goals and resource management and allocation as well as urban climate-related initiatives, as it is estimated that more people will reside in the urban areas in further years. As more people migrate to cities, the world steadily becomes more urbanised. The population of the cities accounts for 55% of the total population, and cities generate 85% of global gross domestic product and emit 75% of greenhouse gas emissions. SDG-11, Sustainable Cities and Communities, aims to ensure inclusive, safe, resilient, sustainable urban and human settlements by providing inexpensive transit solutions, decreasing urban sprawl, enhancing urban governance involvement, improving the protection of cultural assets and addressing urban resilience and climate change issues. This chapter presents the business models of 50 companies and use cases that employ emerging technologies and create value in SDG-11. We should highlight that one use case can be related to more than one SDG and it can make use of multiple emerging technologies.
SDG-14: Life Below Water
Authors: Küfeoğlu Sinan
Published: July 2022

Global systems and processes that assure the supply of rainwater, drinking water and oxygen are regulated by oceanic temperature chemistry, currents and life. Pollution, diminished fisheries and the loss of coastal habitats all have negative impacts on the ocean’s sustainability. Such activities have severely impacted around 40% of the world’s oceans. SDG-14, Life Below Water, aims to conserve marine ecosystems by establishing regulations for removing pollutants from the sea, decreasing sea acidification and regulating the fishing sector to ensure sustainable fishing. As a result, the major incentive for this goal is to protect and utilise marine ecosystem services sustainably. This chapter presents the business models of 36 companies and use cases that employ emerging technologies and create value in SDG-14. We should highlight that one use case can be related to more than one SDG and it can make use of multiple emerging technologies.
SDG-1 No Poverty
Authors: Küfeoğlu Sinan
Published: July 2022

Poverty, which has taken shape in different dimensions under the influence of the conditions from the past to the present, can be defined as the deficiency experienced by people in fulfilling their life functions or the living standards being below the average level. This chapter presents the business models of 39 companies and use cases that employ emerging technologies and create value in SDG-1, No Poverty. We should highlight that one use case can be related to more than one SDG and it can make use of multiple emerging technologies.
SDG-6 Clean Water and Sanitation
Authors: Küfeoğlu Sinan
Published: July 2022

The sixth sustainable development goal, Clean Water and Sanitation, is to ensure that everyone has access to safe, clean water. Everyone has the right to healthy, adequate, physically accessible and affordable water for household use under the right to water security. Acknowledging that millions of people lack access to clean water for sanitation, there is an urgent need for major investments in infrastructure and governance of water provisioning to ensure public health and increase resilience for transmissible diseases and virus outbreaks. This chapter presents the business models of 36 companies and use cases that employ emerging technologies and create value in SDG-6. We should highlight that one use case can be related to more than one SDG and it can make use of multiple emerging technologies.
Motivation und Aufbau des Buches
Authors: Oswald G. , Saueressig T. , Krcmar H.
Published: July 2022

Die digitale Transformation ist ein viel debattiertes Thema und bestimmt die Agenda von Unternehmen weltweit. Die zunehmende Digitalisierung unseres privaten, beruflichen und öffentlichen Lebens wird häufig als Veränderungsprozess bezeichnet, der die Art, wie Unternehmen untereinander konkurrieren, Werte schaffen und mit ihren Geschäftspartnern und Kunden interagieren grundlegend verändert.
Digitale Transformation bei den Berliner Philharmonikern
Authors: Soto-Setzke D. , Hoberg P. , Murgoci A. , Franzbonenkamp S. , Gaß J. , Wolff T. , Krcmar H.
Published: July 2022

Neue technologische Entwicklungen haben das Konsumentenverhalten auf grundlegende und vielfältige Weise verändert. Inzwischen haben diese Veränderungen auch die Kulturbranche erreicht. Vielen Organisationen aus diesem Sektor fehlen jedoch die nötigen Erfahrungen und Expertise, um sich auf eine neue Generation von Kunden in der digitalen Welt einzustellen. Die Berliner Philharmoniker entwickelten sich auf ihrer Reise der digitalen Transformation von einem traditionellen, klassischen Musikorchester zu einem digitalen Pionier. Dabei stellte sich das Orchester den Herausforderungen des digitalen Zeitalters durch die Einführung nachhaltiger organisatorischer Änderungen und durch den Erwerb neuer digitaler Kompetenzen und Fähigkeiten.
Digitale Transformation aus Perspektive der Wirtschaft
Authors: Saueressig T. , Oswald G.
Published: July 2022

Die digitale Transformation verändert unser gesellschaftliches Zusammenleben und wirtschaftliches Handeln. Sie unterscheidet sich von vorangegangenen Transformationen vor allem durch ihre Schnelligkeit, Komplexität, Interdisziplinarität und Globalität. Daher stellt sich sowohl für Unternehmen als auch für Wissenschaft und Forschung die Frage, wie die Transformation aktiv vorangetrieben werden kann, ohne gleichzeitig von den Entwicklungen überholt zu werden. Die Antwort darauf liegt in der Modularisierung – von der Technologie bis zum Prozess. Der folgende Beitrag gibt zunächst einen Überblick zu Herausforderungen und Chancen der digitalen Transformation. Anschließend gehen wir darauf ein, warum es für Unternehmen unausweichlich ist, die digitale Transformation aktiv zu treiben, um zukunftsfähig zu bleiben. Wir liefern Impulse dazu, wie erfolgreiche Digitalisierung in Unternehmen aussehen kann und welche Rolle aktuellen Technologietrends dabei zukommt.
Erfolgreiche digitale Transformation von HR bei ZF
Authors: Farr A. , Oberaigner L. , Stadler A. , Wetzel J.-P. , Floetgen R. J. , Krcmar H.
Published: July 2022

Die digitale Transformation stellt für die meisten Unternehmen eine große Herausforderung dar. Noch komplizierter wird es, wenn es viele Arbeiter in der Produktion sowie eine Vergangenheit mit einer Reihe von großen Fusionen und Übernahmen gibt. Der ZF-Konzern stellt sich diesem soziotechnischen Phänomen, indem er neue Technologien einsetzt und alle Mitarbeiter in den Prozess einbezieht. In den vergangenen drei Jahren hat das ZF-Personalwesen ein globales System eingeführt, um einheitliche, transparente Daten und Prozesse zu schaffen. In dieser Studie haben wir neue HR-Technologien evaluiert, die beschriebene digitale Transformation im ZF-Personalwesen untersucht und Mitarbeiterbefragungen durchgeführt. Basierend auf diesen Erkenntnissen haben wir fünf Schwerpunktbereiche für Verbesserungen identifiziert: Daten, Prozesse, Organisation, Veränderungsprozesse und IT-Systeme. Unter anderem haben wir festgestellt, dass teilweise Prozesse noch nicht optimal ausgerichtet sind und die aus der Firmenhistorie resultierende HR-Systemlandschaft Harmonisierungsbedarf aufweist. Was den Veränderungsprozess insgesamt angeht, empfehlen wir eine stärkere Promotorenrolle des Managements. Im Rahmen der anschließenden Ideation haben wir zehn Ansätze im Sinne von Stellhebeln entwickelt. Indem wir sie in den Gesamtkontext des Unternehmens stellen, liefern wir wertvolle Anregungen für mögliche zukünftige Projekte. Außerdem geben wir Einblicke in die aktuelle Mitarbeiterzufriedenheit mit der digitalen Transformation im Personalbereich von ZF. Abschließend liefern wir durch die Darstellung sowohl positiver als auch kritischer Stimmen Ideen, wie zukünftige Transformationsinitiativen bestmöglich durchgeführt werden können.
Partial implosions and quivers
Authors: Bourget Antoine , Dancer Andrew , Grimminger Julius F. , Hanany Amihay , Zhong Zhenghao
Published: July 2022

Abstract

We propose magnetic quivers for partial implosion spaces. Such partial implosions involve a choice of parabolic subgroup, with the Borel subgroup corresponding to the standard implosion. In the subregular case we test the conjecture by verifying that reduction by the Levi group gives the appropriate nilpotent orbit closure. In the case of a parabolic corresponding to a hook diagram we are also able to carry out this verification provided we work at nonzero Fayet-Iliopoulos parameters.
An Analytic Representation of the Second Symmetric Standard Elliptic Integral in Terms of Elementary Functions
Authors: Bujanda Blanca , López José L. , Pagola Pedro J. , Palacios Pablo
Published: July 2022

We derive new convergent expansions of the symmetric standard elliptic integral $$R_D(x,y,z)$$

R
D

(
x
,
y
,
z
)

, for $$x, y,z\in {\mathbb {C}}{\setminus }(-\infty ,0]$$

x
,
y
,
z
∈
C
\
(
-
∞
,
0
]

, in terms of elementary functions. The expansions hold uniformly for large and small values of one of the three variables x, y or z (with the other two fixed). We proceed by considering a more general parametric integral from which $$R_D(x,y,z)$$

R
D

(
x
,
y
,
z
)

is a particular case. It turns out that this parametric integral is an integral representation of the Appell function $$F_1(a;b,c;a+1;x,y)$$

F
1

(
a
;
b
,
c
;
a
+
1
;
x
,
y
)

. Therefore, as a byproduct, we deduce convergent expansions of $$F_1(a;b,c;a+1;x,y)$$

F
1

(
a
;
b
,
c
;
a
+
1
;
x
,
y
)

. We also compute error bounds at any order of the approximation. Some numerical examples show the accuracy of the expansions and their uniform features.
A surrogate model to accelerate non-intrusive global–local simulations of cracked steel structures
Authors: Fillmore Travis B. , Wu Zihan , Vega Manuel A. , Hu Zhen , Todd Michael D.
Published: July 2022

Physics-based digital twins often require many computations to diagnose current and predict future damage states in structures. This research proposes a novel iterative global–local method, where the local numerical model is replaced with a surrogate to simulate cracking quickly on large steel structures. The iterative global–local method bridges the scales from the operational level of a large steel structure to that of a cracked component. The linear global domain is efficiently simulated using static condensation, and the cracked local domain is quickly simulated using the adaptive surrogate modeling method proposed herein. This work compares solution time and accuracy of the proposed surrogate iterative global–local method with a reference model, a submodeling model, and an iterative global–local method with no surrogate model for the local domain. It is found that the surrogate iterative global–local method gives the fastest solution time with comparatively accurate results.
Effect of freezing, fast-freezing by liquid nitrogen or refrigeration to preserve premium extra virgin olive oil during storage
Authors: Díez-Betriu Anna , Romero Agustí , Ninot Antonia , Tres Alba , Vichi Stefania , Guardiola Francesc
Published: July 2022

During storage, premium extra virgin olive oils (PEVOO), which are oils of exceptional sensory quality, may lose the organoleptic characteristics that define them. This study assessed the effect of applying modified atmospheres and low temperatures (refrigeration and freezing) on the quality of 4 PEVOO for 24 months. Also, the effect of two freezing methods was studied (in the freezer at − 20 °C and in a bath of liquid nitrogen), along with the impact of freezing on the quality of the oils after thawing and storing at room temperature. Official quality parameters, organoleptic assessment, phenolic compounds, volatile compounds and oxidative stability index were measured periodically. While no significant effect of headspace composition was found, the oils stored at − 20 °C maintained their initial quality better than the oils stored at room temperature. Physicochemical quality parameters remained unchanged throughout the 24 months at − 20 °C. Polar phenolic and volatile compounds associated with green and fruity aromas were better preserved at − 20 °C, which translated into a minimum change in the sensory profile of the oils. While no significant difference was observed regarding oxidative parameters, freezing at − 20 °C maintained the initial volatile and sensory profile of the oils better than freezing with liquid nitrogen. Lastly, quality of thawed oils showed no significant differences compared to control oils during storage at room temperature. In conclusion, storage at − 20 °C maintains the quality of PEVOO, especially their sensory profile, and does not compromise their quality after thawing.
Irrigation water demand and elasticities: a case study of the High Plains aquifer
Authors: Pathak Santosh , Adusumilli Naveen C. , Wang Hua , Almas Lal K.
Published: July 2022

The agriculture of the Texas High Plains (THP) region is primarily dependent on groundwater irrigation. Changing weather patterns along with competing demands for water resources and other anthropogenic effects have dramatically increased withdrawals from the Ogallala aquifer. In addition to on-farm changes, policy tools based on off-farm mechanisms are equally indispensable in addressing sustainable groundwater use in the THP. One such policy tool is water pricing using estimates of price elasticity of irrigation water demand. This paper estimates the elasticity of irrigation water demand in the THP and assesses the influence of water price on major inputs used in dominant irrigated crops such as corn and cotton. Using the translog profit function on an annual county-level dataset of THP crop production, spanning 23 years (1998–2020), we find that irrigation water demand is price elastic for cotton (η = – 1.58) but inelastic for corn (η = – 0.81). Our findings suggest that a non-uniform pricing policy could be a useful tool to promote the efficient use of groundwater for irrigation.
Numerical algorithms for water waves with background flow over obstacles and topography
Authors: Ambrose David M. , Camassa Roberto , Marzuola Jeremy L. , McLaughlin Richard M. , Robinson Quentin , Wilkening Jon
Published: July 2022

We present two accurate and efficient algorithms for solving the incompressible, irrotational Euler equations with a free surface in two dimensions with background flow over a periodic, multiply connected fluid domain that includes stationary obstacles and variable bottom topography. One approach is formulated in terms of the surface velocity potential while the other evolves the vortex sheet strength. Both methods employ layer potentials in the form of periodized Cauchy integrals to compute the normal velocity of the free surface, are compatible with arbitrary parameterizations of the free surface and boundaries, and allow for circulation around each obstacle, which leads to multiple-valued velocity potentials but single-valued stream functions. We prove that the resulting second-kind Fredholm integral equations are invertible, possibly after a physically motivated finite-rank correction. In an angle-arclength setting, we show how to avoid curve reconstruction errors that are incompatible with spatial periodicity. We use the proposed methods to study gravity-capillary waves generated by flow around several elliptical obstacles above a flat or variable bottom boundary. In each case, the free surface eventually self-intersects in a splash singularity or collides with a boundary. We also show how to evaluate the velocity and pressure with spectral accuracy throughout the fluid, including near the free surface and solid boundaries. To assess the accuracy of the time evolution, we monitor energy conservation and the decay of Fourier modes and compare the numerical results of the two methods to each other. We implement several solvers for the discretized linear systems and compare their performance. The fastest approach employs a graphics processing unit (GPU) to construct the matrices and carry out iterations of the generalized minimal residual method (GMRES).
Preparation of laser microporous porcine acellular dermal matrix and observation of wound transplantation
Authors: Xia Weidong , Lin Cai , Tu Zhuolong , Li Yuan , Shen Guoliang
Published: July 2022

To prepare a new type of porcine acellular dermis matrix (PADM) with the new laser microporous technique and verify its safety and feasibility. A novel porcine acellular dermis matrix (ADM) was prepared by using sequential combined decellularization of trypsin, neutral protease and SDS solution method and fully rinsed with ultrasonic wave. Specific laser microporous technology was used to prepare the laser micropore porcine acellular dermal matrix (LPADM). SD rats were chose as the animal models and autologous skin was transplanted by one-step method to observe and detect the graft activity, immunogenicity and vascularization degree of the novel PADM. A porcelain white, shiny, soft and elastic dermal matrix was prepared in this study, the results showed low DNA residue and low cytotoxicity. HE staining and SEM observation revealed that the PADM had neither residual cells nor cell fragments, while the collagen bundles were intact and orderly arranged. All the SD rats survived. No infection or skin allergy was found after surgery. None of the animals lost weight. Histological examination showed that the LPADM was fully vascularized with little tissue destruction in the experiment group. Immunohistochemical staining for CD31 showed ideal vascularization in the experiment group, and immunohistochemical staining for TNF-α showed there were no statistical significance of inflammatory reaction in both groups. This study demonstrated that the novel PADM prepared by sequential combined decellularization of trypsin, neutral protease and SDS solution method and new laser microporous technique was effective and safe in animal transplantation.
Interacting with educational chatbots: A systematic review
Authors: Kuhail Mohammad Amin , Alturki Nazik , Alramlawi Salwa , Alhejori Kholood
Published: July 2022

Chatbots hold the promise of revolutionizing education by engaging learners, personalizing learning activities, supporting educators, and developing deep insight into learners’ behavior. However, there is a lack of studies that analyze the recent evidence-based chatbot-learner interaction design techniques applied in education. This study presents a systematic review of 36 papers to understand, compare, and reflect on recent attempts to utilize chatbots in education using seven dimensions: educational field, platform, design principles, the role of chatbots, interaction styles, evidence, and limitations. The results show that the chatbots were mainly designed on a web platform to teach computer science, language, general education, and a few other fields such as engineering and mathematics. Further, more than half of the chatbots were used as teaching agents, while more than a third were peer agents. Most of the chatbots used a predetermined conversational path, and more than a quarter utilized a personalized learning approach that catered to students’ learning needs, while other chatbots used experiential and collaborative learning besides other design principles. Moreover, more than a third of the chatbots were evaluated with experiments, and the results primarily point to improved learning and subjective satisfaction. Challenges and limitations include inadequate or insufficient dataset training and a lack of reliance on usability heuristics. Future studies should explore the effect of chatbot personality and localization on subjective satisfaction and learning effectiveness.
Phosphate-inducible poly-hydroxy butyrate production dynamics in CO2 supplemented upscaled cultivation of engineered Phaeodactylum tricornutum
Authors: Windhagauer Matthias , Abbriano Raffaela M. , Pittrich Dorothea A. , Doblin Martina A.
Published: July 2022

Diatoms such as Phaeodactylum tricornutum are emerging as sustainable alternatives to traditional eukaryotic microbial cell factories. In order to facilitate a viable process for production of heterologous metabolites, a rational genetic design specifically tailored to metabolic requirements as well as optimised culture conditions are required. In this study we investigated the effect of constitutive and inducible expression of the heterologous poly-3-hydroxybutyrate (PHB) pathway in P. tricornutum using non-integrative episomes in 3 different configurations. Constitutive expression led to downregulation of at least one individual gene out of three (phaA, phaB and phaC) and was outperformed by inducible expression. To further asses and optimise the dynamics of PHB accumulation driven by the inducible alkaline phosphatase 1 promoter, we upscaled the production to lab-scale bioreactors and tested the effect of supplemented CO2 on biomass and PHB accumulation. While ambient CO2 cultivation resulted in a maximum PHB yield of 2.3% cell dry weight (CDW) on day 11, under elevated CO2 concentrations PHB yield peaked at 1.7% CDW on day 8, coincident with PHB titres at 27.9 mg L−1 that were approximately threefold higher than ambient CO2. With other more valuable bio-products in mind, these results highlight the importance of the genetic design as well as substrate availability to supply additional reduction equivalents to boost biomass accumulation and relieve potential enzymatic bottlenecks for improved product accumulation.
Thalamocortical bistable switch as a theoretical model of fibromyalgia pathogenesis inferred from a literature survey
Authors: Demori Ilaria , Giordano Giulia , Mucci Viviana , Losacco Serena , Marinelli Lucio , Massobrio Paolo , Blanchini Franco , Burlando Bruno
Published: July 2022

Fibromyalgia (FM) is an unsolved central pain processing disturbance. We aim to provide a unifying model for FM pathogenesis based on a loop network involving thalamocortical regions, i.e., the ventroposterior lateral thalamus (VPL), the somatosensory cortex (SC), and the thalamic reticular nucleus (TRN). The dynamics of the loop have been described by three differential equations having neuron mean firing rates as variables and containing Hill functions to model mutual interactions among the loop elements. A computational analysis conducted with MATLAB has shown a transition from monostability to bistability of the loop behavior for a weakening of GABAergic transmission between TRN and VPL. This involves the appearance of a high-firing-rate steady state, which becomes dominant and is assumed to represent pathogenic pain processing giving rise to chronic pain. Our model is consistent with a bulk of literature evidence, such as neuroimaging and pharmacological data collected on FM patients, and with correlations between FM and immunoendocrine conditions, such as stress, perimenopause, chronic inflammation, obesity, and chronic dizziness. The model suggests that critical targets for FM treatment are to be found among immunoendocrine pathways leading to GABA/glutamate imbalance having an impact on the thalamocortical system.
Clinical and Immunological Features of SARS-CoV-2 Breakthrough Infections in Vaccinated Individuals Requiring Hospitalization
Authors: Lamacchia Giulia , Mazzoni Alessio , Spinicci Michele , Vanni Anna , Salvati Lorenzo , Peruzzi Benedetta , Bencini Sara , Capone Manuela , Carnasciali Alberto , Farahvachi Parham , Rocca Arianna , Kiros Seble Tekle , Graziani Lucia , Zammarchi Lorenzo , Mencarini Jessica , Colao Maria Grazia , Caporale Roberto , Liotta Francesco , Cosmi Lorenzo , Rossolini Gian Maria , Bartoloni Alessandro , Maggi Laura , Annunziato Francesco
Published: July 2022

Background and Purpose

Waning immunity and the surge of SARS-CoV-2 variants are responsible for breakthrough infections, i.e., infections in fully vaccinated individuals. Although the majority of vaccinated infected subjects report mild or no symptoms, some others require hospitalization. The clinical and immunological features of vaccinated hospitalized COVID-19 patients are currently unknown.

Methods

Twenty-nine unvaccinated and 36 vaccinated hospitalized COVID-19 patients were prospectively enrolled and clinical and laboratory data were gathered. Immunophenotyping of leukocytes’ subsets, T and B cell SARS-CoV-2-specific responses were evaluated via flow cytometry. Anti-IFN-α autoantibodies were measured via ELISA.

Results

Despite vaccinated patients were older and with more comorbidities, unvaccinated subjects showed higher levels of pro-inflammatory markers, more severe disease, and increased mortality rate. Accordingly, they presented significant alterations in the circulating leukocyte composition, typical of severe COVID-19. Vaccinated patients displayed higher levels of anti-Spike IgGs and Spike-specific B cells. Of all participants, survivors showed higher levels of anti-Spike IgGs and Spike-specific CD4+ T cells than non-survivors. At hospital admission, 6 out of 65 patients (9.2%) displayed high serum concentrations of autoantibodies targeting IFN-α. Remarkably, 3 were unvaccinated and eventually died, while the other 3 were vaccinated and survived.

Conclusion

Despite more severe pre-existing clinical conditions, vaccinated patients have good outcome. A rapid activation of anti-SARS-CoV-2-specific immunity is fundamental for the resolution of the infection. Therefore, prior immunization through vaccination provides a significant contribution to prevention of disease worsening and can even overcome the presence of high-risk factors (i.e., older age, comorbidities, anti-IFN-α autoantibodies).
Sol–gel encapsulation for power electronics utilizing 3-Glycidyloxypropyltriethoxysilane and 3-Mercaptopropyltrimethoxysilane
Authors: Kohler Tobias , Hejtmann Georg , Henneck Stefan , Schubert Martin , Guyenot Michael
Published: July 2022

3-Glycidyloxypropyltriethoxysilane and 3-Mercaptosilane were used to prepare a composite together with aluminum oxide. The compound is a potential candidate for being used as inorganic encapsulation. FTIR results paired with head-space analysis revealed a hardening of the composite at above 130 °C and degradation of the sol–gel-network above 150 °C. The adhesion of these compounds was tested via shear tests. It showed, that the addition of 3-Mercaptopropyltriethoxysilane enhanced the adhesion on silver significantly. This is attributed to the covalent nature of the Ag-S bond, which is forming as compared to the solely dispersive forces, when 3-Mercaptopropyltriethxysilane is not used. By conducting the shear test under temperature activation energies for the breakages were calculated. These coincide well with the binding energy of Ag-S in case silver surfaces are examined. In the case of a copper surface, a mixture of covalent and dipole–dipole interactions are found, since the activation energy for breakage is smaller as the Cu-O bond energy.
Plant-litter-soil feedbacks in common grass species are slightly negative and only marginally modified by litter exposed to insect herbivory
Authors: De Long Jonathan R. , Heinen Robin , Hannula S. Emilia , Jongen Renske , Steinauer Katja , Bezemer T. Martijn
Published: July 2022

Purpose

Insect herbivory affects plant growth, nutrient and secondary metabolite concentrations and litter quality. Changes to litter quality due to insect herbivory can alter decomposition, with knock on effects for plant growth mediated through the plant-litter-soil feedback pathway.

Methods

Using a multi-phase glasshouse experiment, we tested how changes in shoot and root litter quality of fast- and slow-growing grass caused by insect herbivores affect the performance of response plants in the soil in which the litter decomposed.

Results

We found that insect herbivory resulted in marginal changes to litter quality and did not affect growth when plants were grown with fast- versus slow-growing litter. Overall, presence of litter resulted in reduced root and shoot growth and this effect was significantly more negative in shoots versus roots. However, this effect was minimal, with a loss ofc.1.4% and 3.1% dry weight biomass in roots versus shoots, respectively. Further, shoot litter exposed to insect herbivory interacted with response plant identity to affect root growth.

Conclusions

Our results suggest that whether litter originates from plant tissues exposed to insect herbivory or not and its interaction with fast- versus slow-growing grasses is of little importance, but species-specific responses to herbivory-conditioned litter can occur. Taken collectively, the overall role of the plant-litter-soil feedback pathway, as well as its interaction with insect herbivory, is unlikely to affect broader ecosystem processes in this system.
Economic preferences and temperament traits among business leaders and paid employees
Authors: Vaaramo Mikko , Ala-Mursula Leena , Miettunen Jouko , Korhonen Marko
Published: July 2022

This paper explores individuals’ economic preferences and temperament traits among different categories of business leaders (i.e., managers, self-employed with employees, self-employed without employees) and paid employees. We assume that these quite stable preferences and traits play a role in predicting occupational choice toward leadership roles. We use a large individual-level survey dataset (n = 5890) from the Northern Finland Birth Cohort 1966 at age 46 with linkages to nationally registered data. We construct survey measures for three types of economic preferences: risk, time, and social preferences. We use Cloninger’s inventory to measure four main temperament traits: harm avoidance, reward dependence, novelty-seeking, and persistence. We show that business leaders, in general, have different economic preferences and temperament traits than paid employees. To become a manager, especially the temperament trait of novelty-seeking seems relevant; and to become self-employed, particularly the economic preference of risk-taking appears as important.
The identity of social impact venture capitalists: exploring social linguistic positioning and linguistic distinctiveness through text mining
Authors: Toschi Laura , Ughetto Elisa , Fronzetti Colladon Andrea
Published: July 2022

Impact investing is gaining momentum as an investment practice that optimizes both financial and social outcomes. However, the market is still in its emerging stage, and there is ambiguity regarding the definition of players and practices. In this paper, we adopt an investor identity perspective and use a linguistic approach to explore how social impact venture capitalists (SIVCs) communicate their identities and actions to their external stakeholders. Through a text mining analysis of the websites of 195 investors worldwide, our results reveal four types of investors who differ in terms of their social linguistic positioning and linguistic distinctiveness. Finally, by training a tree boosting machine learning model, we assess the extent to which the use of different linguistic styles is associated with website traffic.
Individual and cooperative portfolio optimization as linear program
Authors: Grechuk Bogdan , Hao Dawei
Published: July 2022

We derive a linear program for minimization, subject to a linear constraint, of an arbitrary positively homogeneous convex functional, whose dual set is given by linear inequalities, possibly involving auxiliary variables. This allows to reduce to linear programming individual and cooperative portfolio optimization problems with arbitrary deviation measures whose risk envelopes are given by a finite number of linear constraints. Earlier, such linear programs were known only for individual porfolio optimization problems with special examples of deviation measures, such as mean absolute deviation or CVaR deviation.
Gastrointestinal stromal tumors: a comprehensive radiological review
Authors: Inoue Akitoshi , Ota Shinichi , Yamasaki Michio , Batsaikhan Bolorkhand , Furukawa Akira , Watanabe Yoshiyuki
Published: July 2022

Gastrointestinal stromal tumors (GISTs) originating from the interstitial cells of Cajal in the muscularis propria are the most common mesenchymal tumor of the gastrointestinal tract. Multiple modalities, including computed tomography (CT), magnetic resonance imaging (MRI), fluorodeoxyglucose positron emission tomography, ultrasonography, digital subtraction angiography, and endoscopy, have been performed to evaluate GISTs. CT is most frequently used for diagnosis, staging, surveillance, and response monitoring during molecularly targeted therapy in clinical practice. The diagnosis of GISTs is sometimes challenging because of the diverse imaging findings, such as anatomical location (esophagus, stomach, duodenum, small bowel, colorectum, appendix, and peritoneum), growth pattern, and enhancement pattern as well as the presence of necrosis, calcification, ulceration, early venous return, and metastasis. Imaging findings of GISTs treated with antineoplastic agents are quite different from those of other neoplasms (e.g. adenocarcinomas) because only subtle changes in size are seen even in responsive lesions. Furthermore, the recurrence pattern of GISTs is different from that of other neoplasms. This review discusses the advantages and disadvantages of each imaging modality, describes imaging findings obtained before and after treatment, presents a few cases of complicated GISTs, and discusses recent investigations performed using CT and MRI to predict histological risk grade, gene mutations, and patient outcomes.
Taxonomic and community composition of epigeal arthropods in monoculture and mixed tree species plantations in a deciduous forest of Ghana
Authors: Damptey Frederick Gyasi , Opuni-Frimpong Emmanuel , Nsor Collins Ayine , Addai James , Debrah Daniel Kwame , Schnerch Benjamin , Bentsi-Enchill Felicity , Korjus Henn
Published: July 2022

Tropical forests provide several ecosystem services and functions and support approximately two-thirds of the world’s biodiversity but are seriously threatened by deforestation. Approaches to counteract this menace have revolved around afforestation with several or a single tree species. We thus investigated how plantation forests with either a single or several tree species influenced arthropod taxonomic and community composition using pitfall traps to sample selected groups of epigeal arthropods (Araneae, Coleoptera, Orthoptera and Hymenoptera) and with environmental variables assessed simultaneously. Our results revealed 54 taxonomic groups with significantly higher taxonomic richness, activity density, and diversity in the mixed stands than in the monoculture stands. The significant differences in community composition were mainly driven by families including Lycosidae, Formicidae, Staphylinidae, Scotylidae, Hydrophilidae, Gryllidae and Scarabaeidae and were explained by distinct habitat characteristics (canopy openness, litter depth, deadwood volume, and tree height). While the diverse tree communities and heterogeneous vegetation structure offered food and habitat resources for diverse arthropod groups, the allelopathic nature coupled with homogenous stand characteristics of the Tectona grandis stands in the monoculture suppressed the growth of understorey vegetation that could otherwise serve as food and habitat resources for arthropods, which might have led to limited activities and diversity of arthropods in the monoculture plantation stands. The findings thus highlight the need to promote mixed tree plantations in degraded tropical areas, especially when restoring biodiversity is the prime management focus.
Prophylactic Cefazolin Dosing in Obesity—a Systematic Review
Authors: Coates Matthew , Shield Alison , Peterson Gregory M. , Hussain Zahid
Published: July 2022

Currently, there is no consensus on whether a standard 2-g prophylactic cefazolin dose provides sufficient antimicrobial coverage in obese surgical patients. This systematic review analysed both outcome and pharmacokinetic studies, aiming to determine the appropriate cefazolin dose. A systematic search was conducted using 4 databases. In total, 3 outcome and 15 pharmacokinetic studies met the inclusion criteria. All 3 outcome studies concluded that there is no need for increased dose. Also, 9 pharmacokinetic studies reached this conclusion; however, 6 pharmacokinetic studies recommended that 2-g dose is insufficient to achieve adequate plasma or tissue concentrations. The stronger body of evidence supports that 2-g dose of cefazolin is sufficient for surgery lasting up to 4 h; however, large-scale outcome studies are needed to confirm this evidence.
Thermal dissociation kinetics of solid ammonium carbonate for use in NH3-SCR systems
Authors: Mohan Sooraj , Dinesha P.
Published: July 2022

Selective catalytic reduction (SCR) systems using solid ammonia carriers like carbamates, carbonates, etc., have gained interest in the recent past for NOx abatement from compression ignition engines. Solid ammonia carriers have successfully demonstrated their use in SCR systems. In this experimental study, the thermal dissociation study of ammonium carbonate is made using nonisothermal thermogravimetric analysis. Ammonium carbonate is subjected to three heating rates, $$\emptyset$$
∅
of 2, 4, and 8 K/min. The corresponding highest rates of reaction are obtained at temperatures ($$T_{p}$$

T
p

) of 96, 118, and 128 °C, respectively. At these points, the mass of the samples has been reduced to 1/3rd of the initial mass. From the Arrhenius plots, the average activation energy obtained is 77.39 kJ/mol which is 15% higher than that of ammonium carbamate. An expression for $$T_{p}$$

T
p

as a function of activation energy, $$\emptyset$$
∅
, and order of the reaction is developed using kinetic model. The model can predict the temperatures at which the reaction rates are maximum for a given heating rate.
A data analytics approach for university competitiveness: the QS world university rankings
Authors: Estrada-Real Ana Carmen , Cantu-Ortiz Francisco J.
Published: July 2022

In recent years, higher education has felt pressured to prepare its graduates for the highly competitive international market due to globalization. Thus, many institutions have turned to position themselves well in university rankings as a way to attract the best academic and student talent from all over the world. Our work presents a predictive model for measuring university performance in the QS world university rankings (QS-WUR). We used a ten-year dataset to build models with statistical and machine learning algorithms contained in the library Caret of the RStudio software tool, to forecast global university position in QS-WUR. With these tools, we designed a methodology to predict the university partners' Final Scores based on their historical performance, achieving errors in the range of one or two points out of 100. The modelling may be a useful aid for university officers to develop strategies for improving institutional processes to attract the best students, faculty, and funding, enhance international collaboration and outlook, and foster international university prestige.