bluuebunny/crossref_metadata_2025 huggingface dataset:
Calibrating machine learning approaches for probability estimation: A comprehensive comparison
Authors: Ojeda Francisco M. , Jansen Max L. , Thiéry Alexandre , Blankenberg Stefan , Weimar Christian , Schmid Matthias , Ziegler Andreas
Published: October 2023

Statistical prediction models have gained popularity in applied research. One challenge is the transfer of the prediction model to a different population which may be structurally different from the model for which it has been developed. An adaptation to the new population can be achieved by calibrating the model to the characteristics of the target population, for which numerous calibration techniques exist. In view of this diversity, we performed a systematic evaluation of various popular calibration approaches used by the statistical and the machine learning communities for estimating two‐class probabilities. In this work, we first provide a review of the literature and, second, present the results of a comprehensive simulation study. The calibration approaches are compared with respect to their empirical properties and relationships, their ability to generalize precise probability estimates to external populations and their availability in terms of easy‐to‐use software implementations. Third, we provide code from real data analysis allowing its application by researchers. Logistic calibration and beta calibration, which estimate an intercept plus one and two slope parameters, respectively, consistently showed the best results in the simulation studies. Calibration on logit transformed probability estimates generally outperformed calibration methods on nontransformed estimates. In case of structural differences between training and validation data, re‐estimation of the entire prediction model should be outweighted against sample size of the validation data. We recommend regression‐based calibration approaches using transformed probability estimates, where at least one slope is estimated in addition to an intercept for updating probability estimates in validation studies.
We Ask Students What they Understand, Not How they Understand: Making Reasoning Comprehension Processes Visible and Explicit
Authors: Lee Carol D.
Published: October 2023

This paper pushes beyond current debates over what is being called the science of reading to articulate a multidimensional complex conception of what is entailed in reading comprehension. Reading comprehension entails not only cognitive processes, but equally important is how issues of identity along multiple dimensions, perceptions of tasks and settings, social and emotional relationships intersect to shape effort and motivation to comprehend. The paper argues that a central problem in the typical teaching of reading comprehension in the K–12 sector is insufficient attention to processes or meaning making. Typical instruction focuses on the outcomes of comprehension, but not on how readers can/should go about trying to make sense of texts. Such instruction can be created by communities of teachers who examine the sources of text difficulty in texts they are teaching. The paper offers explicit criteria for evaluating sources of text complexity in informational and literary texts, and in so doing push beyond the boundaries of traditional Lexile scores.
Patient‐reported outcomes in the Kingdom of Saudi Arabia: An insight for a healthcare system undergoing reform
Authors: Fanous Nadia , Samarkandi Lujain , Al‐Bsheish Mohammad , Abu‐Elenin Mira M.
Published: October 2023

Patient‐reported outcomes (PROs) are closely related to the delivery of high‐quality care and services. Patient‐reported outcome measures (PROMs) are the tools used to measure the PROs. Despite the challenges and barriers associated with using PROs and PROMs, measuring PROs is valuable for a patient's health status and advancing evidence‐based medicine. Real‐world implementation of PROMs may especially open possibilities for healthcare systems under reform, such as Saudi Arabia. This paper highlights the concepts of PROs and PROMs. Moreover, it distinguishes between PROs and other concepts such as patient experience, quality of life, and patient satisfaction. It also explores the available literature in Saudi Arabia and the world regarding PROs and their role in improving healthcare systems. Last, this paper advocates for utilizing the national and comprehensive tools of PROMS in different levels and disciplines.
Modeling and analysis of scattering in trifurcated guided waves with hard and flexible outer surfaces: A mathematical study
Authors: Alahmadi Hani
Published: October 2023

This article discusses the scattering in a trifurcated guided wave featuring the combination of hard and flexible exterior surfaces. Through the formulation of the relevant boundary value problem and modes matching of orthogonal and non‐orthogonal functions, a comprehensive solution is obtained through infinite linear algebraic equations. The structural complexity of these structures introduces challenges related to non‐linearities in dispersive relations, and uncommon orthogonal characteristics of eigenfunctions. Therefore, by reorganizing the differential system into an algebraic one, a solution is obtained by truncating the system numerically. Further, analytical and numerical tests validate the solution, including graphical representations of relative powers versus frequency. The results reveal that transmission dominates reflection for frequencies above 900Hz in the symmetrical setting, with nearly equal power propagating through regions 2, 3, and 4. In the non‐symmetrical setting, power primarily transmits through region 4 for frequencies above 600Hz whereas most of the power being reflected at cut‐on frequencies when region 3 as rigid‐soft instead of rigid‐rigid. The obtained solution also confirms the properties of eigenfunctions, and the power distribution among different regions validates the accuracy of the solution. This work holds significance as it provides a standard procedure for modeling and solving a broad range of multifurcated problems with multiple dynamic boundary properties. The findings aid the understanding and development of waveguide systems, offering vision to practical applications in various fields involving complex wave propagation.
Why and How Territory
Authors: Mazzoleni Oscar
Published: October 2023

This introductory chapter highlights the relevance of the territorial dimension in contemporary democratic politics and how it can be incorporated into a conceptual configuration of a territory-oriented approach in political sociology. It also emphasises the need for an interdisciplinary dialogue between political sociology and the humanities—in particular, with geographic scholarship—to better understand the complexities of the territorial dimension in democratic politics.
Towards a Territory-Oriented Approach
Authors: Mazzoleni Oscar
Published: October 2023

This chapter discusses how the concept of territory is key to understanding contemporary democratic politics. Assuming its polysemic meaning and its different uses of the concept in humanities and social sciences, the heuristic strength of territory is identified in conjunction with a set of related concepts. Throughout an interdisciplinary dialogue, it is explored how the concept of territory takes on relevance in relation to space, political institution, strategy, appropriation, place, borders and networks.
Precision cosmological constraints on atomic dark matter
Authors: Bansal Saurabh , Barron Jared , Curtin David , Tsai Yuhsin
Published: October 2023

Abstract

Atomic dark matter is a simple but highly theoretically motivated possibility for an interacting dark sector that could constitute some or all of dark matter. We perform a comprehensive study of precision cosmological observables on minimal atomic dark matter, exploring for the first time the full parameter space of dark QED coupling and dark electron and proton masses (αD,$$ {m}_{e_D} $$

m

e
D

,$$ {m}_{p_D} $$

m

p
D

) as well as the two cosmological parameters of aDM mass fraction fD and temperature ratio ξ at time of SM recombination. We also show how aDM can accommodate the (H0, S8) tension from late-time measurements, leading to a better fit than ΛCDM or ΛCDM + dark radiation. Furthermore, including late-time measurements leads to closed contours of preferred ξ and dark hydrogen binding energy. The dark proton mass is seemingly unconstrained. Our results serve as an important new jumping-off point for future precision studies of atomic dark matter at non-linear and smaller scales.
Peculiarities of beta functions in sigma models
Authors: Gamayun Oleksandr , Losev Andrei , Shifman Mikhail
Published: October 2023

Abstract

In this paper we consider perturbation theory in generic two-dimensional sigma models in the so-called first-order formalism, using the coordinate regularization approach. Our goal is to analyze the first-order formalism in application to β functions and compare its results with the standard geometric calculations. Already in the second loop, we observe deviations from the geometric results that cannot be explained by the regularization/renormalization scheme choices. Moreover, in certain cases the first-order calculations produce results that are not symmetric under the classical diffeomorphisms of the target space. Although we could not present the full solution to this remarkable phenomenon, we found some indirect arguments indicating that an anomaly similar to that established in supersymmetric Yang-Mills theory might manifest itself starting from the second loop. We discuss why the difference between two answers might be an infrared effect, similar to that in β functions in supersymmetric Yang-Mills theories.

In addition to the generic Kähler target spaces we discuss in detail the so-called Lie-algebraic sigma models. In particular, this is the case when the perturbed field $$ {G}^{i\overline{j}} $$

G

i

j
¯

is a product of the holomorphic and antiholomorphic currents satisfying two-dimensional current algebra.
Die transformative Wirkung von künstlicher Intelligenz im Krankenhaus
Authors: Bures Dominik , Hosters Bernadette , Reibel Thomas , Jovy-Klein Florian , Schramm Johanna , Brendt-Müller Jennifer , Sander Jil , Diehl Anke
Published: October 2023

Rasante Fortschritte der digitalen Technologie und die vielversprechenden Potenziale von künstlicher Intelligenz (KI) verändern unseren Alltag und haben längst im Krankenhaus Einzug gehalten. Gerade KI-Anwendungen bieten ein breites Spektrum an Einsatzmöglichkeiten und verfügen über ein beträchtliches Potenzial zur Verbesserung der medizinischen und pflegerischen Versorgung. In der radiologischen Diagnostik beispielsweise gibt es bereits vielfach gut erforschte Anwendungen zur KI-gestützten Bildauswertung. In dieser Arbeit werden weitere KI-Entwicklungen vorgestellt, die dazu beitragen können, das Gesundheitspersonal zu entlasten, um mehr Zeit für die direkte Patient*innenversorgung zu schaffen. Begleitend werden zentrale Aspekte rund um die Entwicklung und den Transfer von KI-basierten Anwendungen beleuchtet. Denn maßgeblich für die Integration von KI in die medizinische Praxis ist, dass sie mit äußerster Sorgfalt und Umsicht erfolgt. Datenschutz und ethische Aspekte dürfen keinesfalls vernachlässigt werden, und es ist von essenzieller Bedeutung, die Zuverlässigkeit und Integrität der KI-Systeme zu gewährleisten, um das Vertrauen sowohl der Patient*innen als auch des Gesundheitspersonals zu gewinnen. Eine umfassende Überprüfung auf mögliche Verzerrungen in den zugrunde liegenden Daten und Algorithmen ist dabei unverzichtbar. Im Spannungsfeld zwischen vielversprechenden Möglichkeiten und ethischen Herausforderungen kann die digitale Transformation in Medizin und Pflege zur Erhöhung der Patient*innensicherheit und zur Entlastung des Personals beitragen.
Functional enhancement of mesothelin-targeted TRuC-T cells by a PD1-CD28 chimeric switch receptor
Authors: McCarthy Derrick , Lofgren Michael , Watt Amy , Horton Holly , Kieffer-Kwon Philippe , Ding Jian , Kobold Sebastian , Baeuerle Patrick A. , Hofmeister Robert , Gutierrez Dario A. , Tighe Robert
Published: October 2023

T cells expressing a mesothelin (MSLN)-specific T cell receptor fusion construct (TRuC®), called TC-210, have demonstrated robust antitumor activity in preclinical models of mesothelioma, ovarian cancer, and lung cancer. However, they are susceptible to suppression by the programmed cell death protein 1 (PD-1)/programmed cell death protein ligand 1 (PD-L1) axis and lack intrinsic costimulatory signaling elements. To enhance the function of anti-MSLN TRuC-T cells, chimeric switch receptors (CSRs) have been designed to co-opt the immunosuppressive PD-1/PD-L1 axis and to deliver a CD28-mediated costimulatory signal. Here, we report that coexpression of the PD1-CD28 CSR in TRuC-T cells enhanced T cell receptor signaling, increased proinflammatory effector cytokines, decreased anti-inflammatory cytokines, and sustained effector function in the presence of PD-L1 when compared with TC-210. Anti-MSLN TRuC-T cells engineered to coexpress PD1-CD28 CSRs comprising the ectodomain of PD-1 and the intracellular domain of CD28 linked by the transmembrane domain of PD-1 were selected for integration into an anti-MSLN TRuC-T cell therapy product called TC-510. In vitro, TC-510 showed significant improvements in persistence and resistance to exhaustion upon chronic stimulation by tumor cells expressing MSLN and PD-L1 when compared with TC-210. In vivo, TC-510 showed a superior ability to provide durable protection following tumor rechallenge, versus TC-210. These data demonstrate that integration of a PD1-CD28 CSR into TRuC-T cells improves effector function, resistance to exhaustion, and prolongs persistence. Based on these findings, TC-510 is currently being evaluated in patients with MSLN-expressing solid tumors.
Interobserver reliability and diagnostic accuracy of prehospital triage for identifying traumatic brain injury in paediatric patients: a systematic review
Authors: Alsuwais Sara , Alqurashi Naif , Body Richard , Carley Simon
Published: October 2023

Purpose

The consistency and accuracy of paediatric TBI triage tools can be affected by different factors, such as patients’ characteristics and the level of knowledge and skill of the caregiver. This systematic review included all the available data on the level of agreement between paramedics and ED physicians about the reliability of tools to identify paediatric TBI and the diagnostic accuracy of several such tools in prehospital settings when used by paramedics.

Methods

MEDLINE (OVID), EMBASE (OVID), Cochrane Library (OVID), and CINAHL Plus (EBSCO) databases were searched from inception to 27 October 2022. Quality, bias, and applicability were assessed using COSMIN for interobserver reliability studies and QUADAS-2 tool for diagnostic accuracy studies. Narrative synthesis was employed because data were unsuitable for meta-analysis.

Results

Initial searches identified 660 papers in total. Five met the inclusion criteria. Two studies showed moderate agreement between paramedics and ED physicians for GCS assessment. The PTS overtriage rate was 10% and the undertriage rate was 62%, while the triage tape had an overtriage rate of 18% and an undertriage rate of 68%. Pre-hospital GCS had 86.67% sensitivity and 71.43% specificity [95% CI]: 0.74–0.96 for neurosurgically significant TBI.

Conclusion

Low level of GCS agreement and poor diagnostic accuracy may cause further harm to the patient; thus, further studies are recommended to improve the prehospital management of children with head injuries.
Adjacency Graphs of Polyhedral Surfaces
Authors: Arseneva Elena , Kleist Linda , Klemz Boris , Löffler Maarten , Schulz André , Vogtenhuber Birgit , Wolff Alexander
Published: October 2023

We study whether a given graph can be realized as an adjacency graph of the polygonal cells of a polyhedral surface in $${\mathbb {R}}^3$$

R

3

. We show that every graph is realizable as a polyhedral surface with arbitrary polygonal cells, and that this is not true if we require the cells to be convex. In particular, if the given graph contains $$K_5$$

K
5

, $$K_{5,81}$$

K

5
,
81

, or any nonplanar 3-tree as a subgraph, no such realization exists. On the other hand, all planar graphs, $$K_{4,4}$$

K

4
,
4

, and $$K_{3,5}$$

K

3
,
5

can be realized with convex cells. The same holds for any subdivision of any graph where each edge is subdivided at least once, and, by a result from McMullen et al. (Isr. J. Math. 46(1–2), 127–144 (1983)), for any hypercube. Our results have implications on the maximum density of graphs describing polyhedral surfaces with convex cells: The realizability of hypercubes shows that the maximum number of edges over all realizable n-vertex graphs is in $$\Omega (n\log n)$$

Ω
(
n
log
n
)

. From the non-realizability of $$K_{5,81}$$

K

5
,
81

, we obtain that any realizable n-vertex graph has $${\mathcal {O}}(n^{9/5})$$

O
(

n

9
/
5

)

edges. As such, these graphs can be considerably denser than planar graphs, but not arbitrarily dense.
An Identity for the Coefficients of Characteristic Polynomials of Hyperplane Arrangements
Authors: Kabluchko Zakhar
Published: October 2023

Consider a finite collection of affine hyperplanes in $$\mathbb R^d$$

R
d

. The hyperplanes dissect $$\mathbb R^d$$

R
d

into finitely many polyhedral chambers. For a point $$x\in \mathbb R^d$$

x
∈

R
d

and a chamber P the metric projection of x onto P is the unique point $$y\in P$$

y
∈
P

minimizing the Euclidean distance to x. The metric projection is contained in the relative interior of a uniquely defined face of P whose dimension is denoted by $$\text {dim}(x,P)$$

dim
(
x
,
P
)

. We prove that for every given $$k\in \{0,\ldots , d\}$$

k
∈
{
0
,
…
,
d
}

, the number of chambers P for which $$\text {dim}(x,P) = k$$

dim
(
x
,
P
)
=
k

does not depend on the choice of x, with an exception of some Lebesgue null set. Moreover, this number is equal to the absolute value of the k-th coefficient of the characteristic polynomial of the hyperplane arrangement. In a special case of reflection arrangements, this proves a conjecture of Drton and Klivans [A geometric interpretation of the characteristic polynomial of reflection arrangements. Proc. Amer. Math. Soc. 138(8), 2873–2887 (2010)].
Support vector machine guided reproducing kernel particle method for image-based modeling of microstructures
Authors: Wang Yanran , Baek Jonghyuk , Tang Yichun , Du Jing , Hillman Mike , Chen Jiun-Shyan
Published: October 2023

This work presents an approach for automating the discretization and approximation procedures in constructing digital representations of composites from micro-CT images featuring intricate microstructures. The proposed method is guided by the Support Vector Machine (SVM) classification, offering an effective approach for discretizing microstructural images. An SVM soft margin training process is introduced as a classification of heterogeneous material points, and image segmentation is accomplished by identifying support vectors through a local regularized optimization problem. In addition, an Interface-Modified Reproducing Kernel Particle Method (IM-RKPM) is proposed for appropriate approximations of weak discontinuities across material interfaces. The proposed method modifies the smooth kernel functions with a regularized Heaviside function concerning the material interfaces to alleviate Gibb's oscillations. This IM-RKPM is formulated without introducing duplicated degrees of freedom associated with the interface nodes commonly needed in the conventional treatments of weak discontinuities in the meshfree methods. Moreover, IM-RKPM can be implemented with various domain integration techniques, such as Stabilized Conforming Nodal Integration (SCNI). The extension of the proposed method to 3-dimension is straightforward, and the effectiveness of the proposed method is validated through the image-based modeling of polymer-ceramic composite microstructures.
Mycorrhizal status and host genotype interact to shape plant nutrition in field grown maize (Zea mays ssp. mays)
Authors: Li Meng , Perez-Limón Sergio , Ramírez-Flores M. Rosario , Barrales-Gamez Benjamín , Meraz-Mercado Marco Antonio , Ziegler Gregory , Baxter Ivan , Olalde-Portugal Víctor , Sawers Ruairidh J. H.
Published: October 2023

Arbuscular mycorrhizal fungi (AMF) establish symbioses with the major cereal crops, providing plants with increased access to nutrients while enhancing their tolerance to toxic heavy metals. However, not all plant varieties benefit equally from this association. In this study, we used quantitative trait loci (QTL) mapping to evaluate the combined effect of host genotypic variation (G) and AMF across 141 genotypes on the concentration of 20 mineral elements in the leaves and grain of field grown maize (Zea mays spp. mays). Our mapping design included selective incorporation of a castor AMF-incompatibility mutation, allowing estimation of AMF, QTL and QTLxAMF effects by comparison of mycorrhizal and non-mycorrhizal plants. Overall, AMF compatibility was associated with higher concentrations of boron (B), copper (Cu), molybdenum (Mo), phosphorus (P), selenium (Se) and zinc (Zn) and lower concentrations of arsenic (As), iron (Fe), magnesium (Mg), manganese (Mn), potassium (K) and strontium (Sr). In addition to effects on individual elements, pairwise correlation matrices for element concentration differed between mycorrhizal and non-mycorrhizal plants. We mapped 22 element QTLs, including 18 associated with QTLxAMF effects that indicate plant genotype-specific differences in the impact of AMF on the host ionome. Although there is considerable interest in AMF as biofertilizers, it remains challenging to estimate the impact of AMF in the field. Our design illustrates an effective approach for field evaluation of AMF effects. Furthermore, we demonstrate the capacity of the ionome to reveal host genotype-specific variation in the impact of AMF on plant nutrition.
Evaluation of friction calculation methods for rolling bearings
Authors: Zander M. , Otto M. , Lohner T. , Stahl K.
Published: October 2023

In gearboxes, rolling bearing power losses often make up a large amount of the total gearbox power losses. Therefore, an exact calculation of rolling bearing power losses is very important for resource and energy efficient gearbox design. The state of the art offers numerous friction calculation methods with different levels of detail to calculate power losses of rolling bearings. Bearing manufacturers like SKF and Schaeffler offer popular bearing-based/global calculation methods for standard rolling bearings. Contact-based/local calculation methods can consider a wider application field by generalization of tribological relations, which enables its application to e.g. hybrid bearings or non-standard bearings. The different methods may yield widely differing results. For its validation, measurement results are required. In this study, a broad comparison of calculation results with substantial measurement results is shown. Based on the validation a classification of the calculation methods is derived, which provides guidance for the design engineer to choose the appropriate method for the respective application. Contact-based/local calculation methods have the potential to predict friction in rolling bearings precisely.
Neurological complications due to copper deficiency in the context of Wilson disease treatment: a case report with long-term follow-up and review of the literature
Authors: Tornabene Danilo , Bini Paola , Gastaldi Matteo , Vegezzi Elisa , Asteggiano Carlo , Marchioni Enrico , Diamanti Luca
Published: October 2023

The objective is to investigate the presentation, complications, management, and outcomes of copper deficiency-induced neurological pathologies due to Wilson disease (WD) overtreatment. We examined the case of a WD patient who developed a low thoracic dorsal myelopathy due to chronic hypocupremia from excessive zinc therapy. A comprehensive literature review was conducted to identify similar cases. Ten additional cases of neurological pathology resulting from copper deficiency in the context of WD over-treatment were identified, all occurring during therapy with zinc salts. Myelopathy and peripheral neuropathy were the most common complications, while two additional groups reported leukoencephalopathy. Early cytopenia was often associated with copper deficiency-related neurological pathology appearing early in the context of copper deficiency. WD patients undergoing treatment, especially with zinc salts, should be closely monitored to prevent over-treatment and the consequent copper deficiency. Regular complete blood counts could provide early detection of copper deficiency, avoiding irreversible neurological damage. Swift recognition of new neurological signs not consistent with WD and timely discontinuation of the decoppering therapy are critical for improving outcomes. The optimal management, including the potential benefit of copper supplementation in patients with WD and subsequent therapy adjustments, remains unclear and necessitates further investigation. Despite the general poor functional neurological outcomes, there were some exceptions that warrant further exploration.
Sustainable employability, technology acceptance and task performance in workers collaborating with cobots: a pilot study
Authors: Picco Eleonora , Miglioretti Massimo , Le Blanc Pascale M.
Published: October 2023

Sustainable Employability (SE) and task performance of workers-collaborating-with-cobots is challenged. Whether SE policies can impact workers’ task performance in digitalized workplaces is still unknown. Drawing on two SE models, this study aims to ascertain whether the relationship between SE policies and task performance is mediated by health and productive capabilities, and whether this effect is moderated by the levels of User Acceptance and Use of Technology (UTAUT) predictors. 88 employees collaborating with cobots, or expected to do so in the near future, answered a cross-sectional survey. SE policies were positively related to task performance via health and productive capabilities. This indirect effect was moderated by the levels of UTAUT predictors, being significant only at low or medium levels of the moderators. SE policies contribute to employee capabilities, and in turn to workers’ task performance. Fostering health and productive capabilities is fundamental when employee levels of cobots’ acceptance are not high yet.
Evaluation of seagrass as a nature-based solution for coastal protection in the German Wadden Sea
Authors: Jacob Benjamin , Dolch Tobias , Wurpts Andreas , Staneva Joanna
Published: October 2023

Global climate change increases the overall risks for coastal flooding and erosion. Meanwhile, nature-based solutions (NbS) are increasingly becoming a focus of coastal protection measures to improve the climate adaptability. In this study, the present and potential future role of seagrass in coastal risk reduction strategies were explored for the highly energetic Wadden Sea area of the German Bight. The methodology in this study combined seagrass coverage data (Zostera marina and Zostera noltei) obtained by field surveys and what-if scenario simulations using the SCHISM unstructured grid model framework, coupling hydrodynamics, waves, sediments, and a seagrass module. The results suggest that the introduction of seagrass meadows locally can reduce both current velocities and significant wave heights in the order of up to 30$$\%$$
%
in the deeper areas and above 90$$\%$$
%
in the shallow areas. Reduction in bottom shear stress of a similar relative magnitude significantly reduced sediment mobilisation on the order of 2 g/L in the 95th quantile of bottom layer sediment concentrations. Effectively altering hydromorphodynamic conditions favouring sediment accumulation, seagrass expansion could help tidal flats height growths to keep up with SLR, thus further maintaining the bathymetry-induced tidal dampening and lowering flooding and erosion risks as well the amount of energy at dike infrastructure. The accumulated effect of seagrass under calm weather conditions is considered more important than the increased attenuation in absolute values it provides during extreme conditions. The overall conclusion is that seagrass expansion could be a useful addition to engineered coastal protection measures.
Cortical bone adaptation response is region specific, but not peak load dependent: insights from $$\mu$$CT image analysis and mechanostat simulations of the mouse tibia loading model
Authors: Miller Corey J. , Pickering Edmund , Martelli Saulo , Dall’Ara Enrico , Delisser Peter , Pivonka Peter
Published: October 2023

The two major aims of the present study were: (i) quantify localised cortical bone adaptation at the surface level using contralateral endpoint imaging data and image analysis techniques, and (ii) investigate whether cortical bone adaptation responses are universal or region specific and dependent on the respective peak load. For this purpose, we re-analyse previously published $$\mu$$
μ
CT data of the mouse tibia loading model that investigated bone adaptation in response to sciatic neurectomy and various peak load magnitudes (F = 0, 2, 4, 6, 8, 10, 12 N). A beam theory-based approach was developed to simulate cortical bone adaptation in different sections of the tibia, using longitudinal strains as the adaptive stimuli. We developed four mechanostat models: universal, surface-based, strain directional-based, and combined surface and strain direction-based. Rates of bone adaptation in these mechanostat models were computed using an optimisation procedure (131,606 total simulations), performed on a single load case (F = 10 N). Subsequently, the models were validated against the remaining six peak loads. Our findings indicate that local bone adaptation responses are quasi-linear and bone region specific. The mechanostat model which accounted for differences in endosteal and periosteal regions and strain directions (i.e. tensile versus compressive) produced the lowest root mean squared error between simulated and experimental data for all loads, with a combined prediction accuracy of 76.6, 55.0 and 80.7% for periosteal, endosteal, and cortical thickness measurements (in the midshaft of the tibia). The largest root mean squared errors were observed in the transitional loads, i.e. F = 2 to 6 N, where inter-animal variability was highest. Finally, while endpoint imaging studies provide great insights into organ level bone adaptation responses, the between animal and loaded versus control limb variability make simulations of local surface-based adaptation responses challenging.
COMPASSO mission and its iodine clock: outline of the clock design
Authors: Kuschewski Frederik , Wüst Jan , Oswald Markus , Blomberg Tim , Gohlke Martin , Bischof Jonas , Boac Alex , Alam Tasmim , Bußmeier André , Abich Klaus , Röder Niklas , Döringshoff Klaus , Hrabina Jan , Holá Miroslava , Oulehla Jindřich , Schuldt Thilo , Braxmaier Claus
Published: October 2023

One of the limiting factors for GNSS geolocation capabilities is the clock technology deployed on the satellites and the knowledge of the satellite position. Consequently, there are numerous ongoing efforts to improve the stability of space-deployable clocks for next-generation GNSS. The COMPASSO mission is a German Aerospace Center (DLR) project to demonstrate high-performance quantum optical technologies in space with two laser-based absolute frequency references, a frequency comb and a laser communication and ranging terminal establishing a link with the ground station located in Oberpfaffenhofen, Germany. A successful mission will strongly improve the timing stability of space-deployable clocks, demonstrate time transfer between different clocks and allow for ranging in the mm-range. Thus, the technology is a strong candidate for future GNSS satellite clocks and offers possibilities for novel satellite system architectures and can improve the performance of scientific instruments as well. The COMPASSO payload will be delivered to the international space station in 2025 for a mission time of 2 years. In this article, we will highlight the key systems and functionalities of COMPASSO, with the focus set to the absolute frequency references.
Photobiomodulation and Wound Healing: Low-Level Laser Therapy at 661 nm in a Scratch Assay Keratinocyte Model
Authors: Mathioudaki Evdoxia , Rallis Michail , Politopoulos Konstantinos , Alexandratou Eleni
Published: October 2023

This study aims to investigate the effectiveness of low power red light (661 nm) in accelerating the wound healing process of an in vitro scratch assay model of keratinocytes. Furthermore, the study aims to clarify the role of light irradiation parameters, optimize them and gain additional insight into the mechanisms of wound closure as a result of photobiomodulation. Wound healing was studied using scratch assay model of NCTC 2544 keratinocytes. Cells were irradiated with a laser at various power densities and times. Images were acquired at 0, 24, 48 and 72 h following the laser treatment. Cellular proliferation was studied by MTT. ROS were studied at 0 and 24 h by fluorescence microscopy. Image analysis was used to determine the wound closure rates and quantify ROS. The energy range of 0.18–7.2 J/cm2 was not phototoxic, increased cell viability and promoted wound healing. Power and irradiation time proved to be more important than energy. The results indicated the existence of two thresholds in both power and irradiation time that need to be overcome to improve wound healing. An increase in ROS production was observed at 0 h only in the group with the lowest healing rate. This early response seemed to block proliferation and finally wound healing. Low level laser light at 661 nm enhanced both proliferation and migration in keratinocytes, providing evidence that it could possibly stimulate wound healing in vivo. The observed results are dependent on irradiance and irradiation time rather than energy dose in total.
How do the people that feed Europe feed themselves? Exploring the (in)formal food practices of Almería’s migrant and seasonal food workers
Authors: Martínez María Alonso , Brons Anke , Wertheim-Heck Sigrid C. O.
Published: October 2023

The EU's Farm to Fork strategy (European Commission European Commission. 2020. Farm to Fork strategy. https://food.ec.europa.eu/horizontal-topics/farm-fork-strategy_en. Accessed 31 August 2023.) highlights the need for a resilient food system capable of providing affordable food to citizens in all circumstances. Behind the provision of affordable food for EU citizens there is the effort of many migrant and seasonal food workers (MSFWs). In Almería, Spain, the area with the biggest concentration of greenhouses in the world, MSFWs face vulnerability in the form of physical and institutional invisibility despite performing the essential task of providing affordable food for the EU’s food system. This paper aims to move on from structuralist concerns and place MSFWs’ lived experiences at the center, including the (in)formal nature of their food practices, to understand how the people that feed Europe feed themselves. A combination of social practice theories and diverse economies is used to explore MFSWs’ daily food routines. These theories are used as lenses that inform the data collection process, performed through semi-structured interviews, photography, and observations. The findings of the study reflect a dynamic portfolio of (in)formal practices that evolve based on the length of stay in the county. These practices demonstrate how the EU food system resilience relies on the diverse economies of migrant settlements. We conclude that informality is a reality in the EU food system, and that shedding light on previously hidden food practices and their structures can help us envision food security interventions that are inclusive for all actors involved.
Machine learning for leaf disease classification: data, techniques and applications
Authors: Yao Jianping , Tran Son N. , Sawyer Samantha , Garg Saurabh
Published: October 2023

The growing demand for sustainable development brings a series of information technologies to help agriculture production. Especially, the emergence of machine learning applications, a branch of artificial intelligence, has shown multiple breakthroughs which can enhance and revolutionize plant pathology approaches. In recent years, machine learning has been adopted for leaf disease classification in both academic research and industrial applications. Therefore, it is enormously beneficial for researchers, engineers, managers, and entrepreneurs to have a comprehensive view about the recent development of machine learning technologies and applications for leaf disease detection. This study will provide a survey in different aspects of the topic including data, techniques, and applications. The paper will start with publicly available datasets. After that, we summarize common machine learning techniques, including traditional (shallow) learning, deep learning, and augmented learning. Finally, we discuss related applications. This paper would provide useful resources for future study and application of machine learning for smart agriculture in general and leaf disease classification in particular.
Seismic behaviour of reinforced-masonry aggregate under different types of interaction between adjacent dwellings
Authors: Torres-Olivares Sebastian , González-Rodrigo Beatriz , Saavedra-Flores Erick I. , Mosquera-Feijoo Juan Carlos
Published: October 2023

Assessing the seismic vulnerability of existing buildings is an essential task for the management of earthquake disasters. For this purpose, the seismic behaviour of buildings is usually determined under the assumption of isolated conditions, although aggregate structures are one of the most common typologies found in urban centres. This study aims to investigate the nonlinear static behaviour of aggregate dwellings consisting of grouted reinforced concrete block configurations commonly observed in San José, Costa Rica. This research investigates the use of several strategies to model connections between adjacent buildings which are typically found in modern building practises in this country. The methodology used here to analyse the seismic behaviour of isolated and row-aggregated dwellings reveals significant differences in their response under seismic loads, especially when acting perpendicular to the aggregate. The study reveals that the type of interaction considered between adjacent buildings has a very important impact on the seismic capacity and failure mechanisms of the aggregated structures. This procedure can also be applied to the vulnerability assessment and retrofit of existing aggregates.
Seismic vulnerability of industrial steel structures with masonry infills using a numerical approach
Authors: Liguori Francesco S. , Madeo Antonio , Formisano Antonio
Published: October 2023

Recent earthquakes have highlighted the high vulnerability of the industrial structures that are not specifically designed for accounting seismic forces. Among them, a widespread typology is characterised by steel structures without bracing or other anti-seismic details and with masonry infills. With the aim of increasing the knowledge on the seismic behaviour of these structures, this work focuses on a mechanical-based approach for the evaluation of fragility curves for industrial areas. The exposure data are obtained by in-situ survey and acquiring information available in existing databases, like the Italian Cartis-GL one that is specifically devised for industrial structures. The variability of geometrical and mechanical data and the presence of epistemic uncertainties are considered by constructing a population of structures using the Monte Carlo method. Each structure is analysed through static-nonlinear simulations adopting mixed finite elements accounting for geometrical and constitutive nonlinearities. The approach is tested for infilled steel structures in the industrial area of the municipality of Spezzano Albanese (Italy). Results show that the presence of masonry infill drastically modifies the seismic behaviour of this structural typology. In particular, it turns out that if the mechanical contribution of the infill is neglected, the structures exhibit high damages even for low intensities of the seismic action.
An Implementation Evaluation of the Comprehensive Addiction Recovery Act (CARA) Policy in New Mexico
Authors: Sharp Nicholas , Fuchs Jessi , Drake Amy
Published: October 2023

Purpose

The purpose of this field report is to describe an evaluation of the fidelity with which the comprehensive addiction and recovery act (CARA) policy has been implemented in New Mexico.

Description

The CARA program in New Mexico focuses on providing nonpunitive supportive care for pregnant people affected by substance use and on coordinating services for parents, caregivers, and family members of newborns affected by substance exposure. The evaluation used information from program reports, a family follow-up survey, the plan of safe care database, and a data linkage between CARA participant records with Medicaid claims data.

Results

Follow-up survey data substantiated the program reports. Both sources showed that families were not engaged consistently in developing or receiving information about plans of safe care. The survey answers also indicated that the time-period immediately after the delivery of a baby is not the best time to communicate the contents of the plan of safe care to families. Additionally, the survey found that respondents believed that medical staff judged them for using substances during pregnancy. The Medicaid data linkage showed that 40.3% of families of infants exposed to substances in-utero did not receive a plan of safe care. Program reports revealed that limited resources existed for implementing CARA.

Conclusion

Program funding, limited system capacity, lack of systematic screening for prenatal substance use, regional differences in access to care, and provider biases toward pregnant people using substances affected health-care workers’ ability to identify at-risk families and develop plans of safe care. To support CARA implementation, healthcare systems must implement universal prenatal substance use screening, increase the level of anti-bias training pertaining to substance use, increase hospital supports, and improve data management systems.
Knockout of M-LP/Mpv17L, a newly identified atypical PDE, induces physiological afferent cardiac hypertrophy in mice
Authors: Iida Reiko , Ueki Misuzu , Yasuda Toshihiro
Published: October 2023

M-LP/Mpv17L (Mpv17-like protein) is an atypical cyclic nucleotide phosphodiesterase (PDE) without the molecular structure characteristic of the PDE family. Deficiency of M-LP/Mpv17L in mice has been found to result in development of β-cell hyperplasia and improved glucose tolerance. Here, we report another phenotype observed in M-LP/Mpv17L-knockout (KO) mice: afferent cardiac hypertrophy. Although the hearts of M-LP/Mpv17L-KO mice did not differ in size from those of wild-type mice, there was marked narrowing of the left ventricular lumen and thickening of the ventricular wall. The diameter and cross-sectional area of cardiomyocytes in 8-month-old M-LP/Mpv17L-KO mice were increased 1.16-fold and 1.35-fold, respectively, relative to control mice, but showed no obvious abnormalities of cell structure, fibrosis or impaired cardiac function. In 80-day-old KO mice, the expression of hypertrophic marker genes, brain natriuretic peptide (BNF), actin alpha cardiac muscle 1 (ACTC1) and actin alpha 1 skeletal muscle (ACTA1), as well as the Wnt/β-catenin pathway target genes, lymphoid enhancer-binding factor-1 (LEF1), axis inhibition protein 2 (AXIN2) and transcription factor 7 (TCF7), was significantly up-regulated relative to control mice, whereas fibrosis-related genes such as fibronectin 1 (FN1) and connective tissue growth factor (CTGF) were down-regulated. Western blot analysis revealed increased phosphorylation of molecules downstream of the cAMP/PKA signaling pathway, such as β-catenin, ryanodine receptor 2 (RyR2), phospholamban (PLN) and troponin I (cTnI), as well as members of the MEK1-ERK1/2 signaling pathway, which is strongly involved in afferent cardiac hypertrophy. Taken together, these findings indicate that M-LP/Mpv17L is one of the PDEs actively functioning in the heart and that deficiency of M-LP/Mpv17L in mice promotes physiological cardiac hypertrophy.
The association between blood nickel level and handgrip strength in patients undergoing maintenance hemodialysis
Authors: Tang Ruiying , Chen Jiexin , Ma Huijuan , Deng Jihong , Zhang Yanxia , Xu Qingdong
Published: October 2023

Background

Progressive loss of peripheral muscle strength is highly pronounced in patients receiving maintenance hemodialysis (MHD), of which the pathological mechanism tends to be multifactorial. Plasma nickel was reportedly correlated with muscular strength in non-dialysis patients. However, scarce is known regarding the association between blood nickel level and handgrip strength among the patients undergoing MHD.

Methods

This cross-sectional study included patients undergoing MHD at our center in October 2021. Blood samples were collected before the hemodialysis sessions. Nickel level was measured using inductively coupled plasma mass spectrometry. Eligible patients were stratified into three groups by the blood nickel level: tertile 1 (≥ 5.2 ug/L); tertile 2 (< 5.2 ug/L and ≥ 4.5 ug/L); and tertile 3 (< 4.5 ug/L). Handgrip strength measurement was used to evaluate the muscle status. Spearman’s analyses and multivariable linear regression analyses were performed to study the relationship between blood nickel level and handgrip strength.

Results

A total of 236 patients were enrolled, with an average age of 55.51 ± 14.27 years and a median dialysis vintage of 83 (IQR: 48–125) months. Patients in group with a higher blood nickel level (tertile 1) tended to be female, had longer dialysis vintage and higher Kt/V, but lower BMI, serum creatinine, hemoglobin, and handgrip strength level (all p < 0.05). After adjustment for confounding factors in multivariable models, for every 1ug/L increase in nickel level, the patient’s handgrip strength decreases by 2.81 kg (β: − 2.810, 95% confidence interval: − 5.036 to − 0.584, p = 0.014). Restricted cubic spline confirmed the relationship was nearly linear.

Conclusions

Our study highlighted that blood nickel level was related to handgrip strength in patients undergoing MHD. Prospective studies with larger sample sizes are still needed to confirm the result.
Inferring Attention Shifts for Salient Instance Ranking
Authors: Siris Avishek , Jiao Jianbo , Tam Gary K. L. , Xie Xianghua , Lau Rynson W. H.
Published: October 2023

The human visual system has limited capacity in simultaneously processing multiple visual inputs. Consequently, humans rely on shifting their attention from one location to another. When viewing an image of complex scenes, psychology studies and behavioural observations show that humans prioritise and sequentially shift attention among multiple visual stimuli. In this paper, we propose to predict the saliency rank of multiple objects by inferring human attention shift. We first construct a new large-scale salient object ranking dataset, with the saliency rank of objects defined by the order that an observer attends to these objects via attention shift. We then propose a new deep learning-based model to leverage both bottom-up and top-down attention mechanisms for saliency rank prediction. Our model includes three novel modules: Spatial Mask Module (SMM), Selective Attention Module (SAM) and Salient Instance Edge Module (SIEM). SMM integrates bottom-up and semantic object properties to enhance contextual object features, from which SAM learns the dependencies between object features and image features for saliency reasoning. SIEM is designed to improve segmentation of salient objects, which helps further improve their rank predictions. Experimental results show that our proposed network achieves state-of-the-art performances on the salient object ranking task across multiple datasets. Code and data are available at https://github.com/SirisAvishek/Attention_Shift_Ranks.