bluuebunny/crossref_metadata_2025_split huggingface dataset:
The GALORE project
Authors: Romagnoni Marco , Bandiera Laura , Carraro Chiara , De Salvador Davide , Guidi Vincenzo , Mazzolari Andrea , Scatizza Luigi , Sgarbossa Francesco , Soldani Mattia , Sytov Alexei , Tamisari Melissa 
Published: August 2022

Abstract
Bent crystals are a compact and versatile tool to manipulate ultra-relativistic particle beams in accelerators. Indeed, the unrivaled steering power achievable exploiting channeling of particles between the atomic planes is comparable to that of a $$10^{2-3}$$

10

2
-
3

Tesla magnetic dipole. Since the first experiments in the 1980s, extensive research has been delivering important results for new physics experiments and applications in accelerators. The substantial technological development, accompanied by reliable Monte Carlo simulations, has increased the steering efficiency from a few % to the intrinsic maximum efficiency of $$\sim 80\%$$

∼
80
%

, limited by scattering of the particles with nuclei inside the crystal. The recently started two-year (2022–2023) project GALORE of INFN aims to assess experimentally the possibility to overcome this hard limit by developing a new generation of bent crystals, featuring an innovative geometry characterized by a crystalline microstructure which influences particle dynamic in the crystal lattice to boost efficiency close to 100%. The manufacturing process will exploit well-established techniques developed for silicon microelectronics, and experimental testing will be carried out at the extracted beamlines of CERN North Area with high-energy hadron beams. The success of this project could strongly impact the employment of bent crystal in frontier energy accelerators, boosting performance of already proposed schemes as well as enabling completely inedited use of bent crystal in particle physics experiment in accelerators.

Graphic Abstract
Tunneling gravimetry
Authors: Schach Patrik , Friedrich Alexander , Williams Jason R. , Schleich Wolfgang P. , Giese Enno 
Published: August 2022

AbstractWe examine the prospects of utilizing matter-wave Fabry–Pérot interferometers for enhanced inertial sensing applications. Our study explores such tunneling-based sensors for the measurement of accelerations in two configurations: (a) a transmission setup, where the initial wave packet is transmitted through the cavity and (b) an out-tunneling scheme with intra-cavity generated initial states lacking a classical counterpart. We perform numerical simulations of the complete dynamics of the quantum wave packet, investigate the tunneling through a matter-wave cavity formed by realistic optical potentials and determine the impact of interactions between atoms. As a consequence we estimate the prospective sensitivities to inertial forces for both proposed configurations and show their feasibility for serving as inertial sensors.
About this title - Straits and Seaways: Controls, Processes and Implications in Modern and Ancient Systems
Authors: Rossi V. M. , Longhitano S. G. , Olariu C. , Chiocci F. L. 
Published: August 2022

Straits and seaways are the key features that connect oceans, seas and lakes. They regulate water, sediment and biota exchanges, and influence local and global climate. A good understanding of the dynamic evolution of straits and seaways is therefore fundamental to accurately reconstruct the palaeogeography, tectonics, palaeoecology and stratigraphy of interconnected basins, the climate dynamics of Earth's past as well as to exploit both conventional and renewable energy resources.
This volume provides a comprehensive collection of articles dealing with both ancient and modern case studies, bringing together different but complementary disciplines, such as marine geology, process sedimentology and stratigraphy.
With the contents encompassing the evolution, geomorphology, stratigraphy, sedimentology, oceanography and palaeogeography of straits and seaways, and their influence on climate, the book will be of interest to Earth scientists working in many fields.
Domain Generalization for Activity Recognition via Adaptive Feature Fusion
Authors: Qin Xin , Wang Jindong , Chen Yiqiang , Lu Wang , Jiang Xinlong 
Published: August 2022

Human activity recognition requires the efforts to build a generalizable model using the training datasets with the hope to achieve good performance in test datasets. However, in real applications, the training and testing datasets may have totally different distributions due to various reasons such as different body shapes, acting styles, and habits, damaging the model’s generalization performance. While such a distribution gap can be reduced by existing domain adaptation approaches, they typically assume that the test data can be accessed in the training stage, which is not realistic. In this article, we consider a more practical and challenging scenario: domain-generalized activity recognition (DGAR) where the test dataset
cannot
be accessed during training. To this end, we propose
Adaptive Feature Fusion for Activity Recognition (AFFAR)
, a domain generalization approach that learns to fuse the domain-invariant and domain-specific representations to improve the model’s generalization performance. AFFAR takes the best of both worlds where domain-invariant representations enhance the transferability across domains and domain-specific representations leverage the model discrimination power from each domain. Extensive experiments on three public HAR datasets show its effectiveness. Furthermore, we apply AFFAR to a real application, i.e., the diagnosis of Children’s Attention Deficit Hyperactivity Disorder (ADHD), which also demonstrates the superiority of our approach.
A Novel Enolase-1 Antibody Targets Multiple Interacting Players in the Tumor Microenvironment of Advanced Prostate Cancer
Authors: Chen Mao-Lin , Yuan Ta-Tung , Chuang Chi-Fen , Huang Yung-Tsang , Chung I-Che , Huang Wei-Ching 
Published: August 2022

Abstract
Prostate cancer is one of the most common causes of cancer death in men worldwide, and the treatment options are limited for patients with advanced stages of prostate cancer. Upon oncogenic or inflammatory stimulation, tumor cells or immune cells express cell surface enolase-1 (ENO1) as plasminogen receptor to facilitate their migration via plasmin activation. Little is known about the roles of ENO1 in prostate cancer, especially in the tumor microenvironment (TME). We hypothesized that targeting surface ENO1 with specific mAbs would exert multifactorial therapeutic potentials against prostate cancer. In vivo, we showed ENO1 mAb (HuL227) reduced the growth of subcutaneous PC-3 xenograft, monocytes recruitment, and intratumoral angiogenesis. In a PC-3 intratibial implantation model, HuL227 reduced tumor growth and osteoclast activation in the bone. To investigate the antitumor mechanism of ENO1 mAb, we found that blocking surface ENO1 significantly reduced VEGF-A–induced tube formation of endothelial cells in vitro. Furthermore, HuL227 inhibited inflammation-enhanced osteoclasts activity and the secretion of invasion-related cytokines CCL2 and TGFβ from osteoclasts. In addition, inflammation-induced migration and chemotaxis of androgen-independent prostate cancer cells were dose-dependently inhibited by HuL227. In summary, we showed that, ENO1 mAb targets multiple TME niches involved in prostate cancer progression and bone metastasis via a plasmin-related mechanism, which may provide a novel immunotherapy approach for men with advanced prostate cancer.
Adaptable Leukemia Cells Resisting CAR T-cell Attack via B-cell Activation
Authors: Zhao Ziran , Melenhorst Jan Joseph 
Published: August 2022

Abstract
Chimeric antigen receptor (CAR) T-cell therapy has achieved remarkable milestones in the treatment of B-cell malignancies. However, cancer cells frequently survive CAR T-cell killing in a large cohort of patients. Relapse oftentimes is associated with antigen loss. In this issue, Im and colleagues report a new mechanism of leukemic-cell resistance to anti-CD19 CAR T cells: Leukemic cells can enable a B-cell activation and germinal center reaction signature, which causes CD19 transcriptional downregulation and survival from CAR exposure.
See related article by Im et al., p. 1055 (5).
Tee-ing up a New Follicular Lymphoma Classification System
Authors: Melnick Ari M. 
Published: August 2022

Summary:In this issue of Blood Cancer Discovery, Han and colleagues find that follicular lymphomas (FL) can be stratified into distinct classes with clinical and functional relevance based on their T-cell subset composition. Their findings further indicate that pairing of FL cell MHCII expression with specific T-cell markers may represent a useful diagnostic approach to select patients for particular immunotherapies or immune augmentation therapies independent of genetic profiling.See related article by Han et al., p. 428 (4).
Multinational Federated Learning Approach to Train ECG and Echocardiogram Models for Hypertrophic Cardiomyopathy Detection
Authors: Goto Shinichi , Solanki Divyarajsinhji , John Jenine E. , Yagi Ryuichiro , Homilius Max , Ichihara Genki , Katsumata Yoshinori , Gaggin Hanna K. , Itabashi Yuji , MacRae Calum A. , Deo Rahul C. 
Published: August 2022

Background:
Novel targeted treatments increase the need for prompt hypertrophic cardiomyopathy (HCM) detection. However, its low prevalence (0.5%) and resemblance to common diseases present challenges that may benefit from automated machine learning–based approaches. We aimed to develop machine learning models to detect HCM and to differentiate it from other cardiac conditions using ECGs and echocardiograms, with robust generalizability across multiple cohorts.

Methods:
Single-institution HCM ECG models were trained and validated on external data. Multi-institution models for ECG and echocardiogram were trained on data from 3 academic medical centers in the United States and Japan using a federated learning approach, which enables training on distributed data without data sharing. Models were validated on held-out test sets for each institution and from a fourth academic medical center and were further evaluated for discrimination of HCM from aortic stenosis, hypertension, and cardiac amyloidosis. Last, automated detection was compared with manual interpretation by 3 cardiologists on a data set with a realistic HCM prevalence.

Results:
We identified 74 376 ECGs for 56 129 patients and 8392 echocardiograms for 6825 patients at the 4 academic medical centers. Although ECG models trained on data from each institution displayed excellent discrimination of HCM on internal test data (C statistics, 0.88–0.93), the generalizability was limited, most notably for a model trained in Japan and tested in the United States (C statistic, 0.79–0.82). When trained in a federated manner, discrimination of HCM was excellent across all institutions (C statistics, 0.90–0.96 and 0.90–0.96 for ECG and echocardiogram model, respectively), including for phenotypic subgroups. The models further discriminated HCM from hypertension, aortic stenosis, and cardiac amyloidosis (C statistics, 0.84, 0.83, and 0.88, respectively, for ECG and 0.93, 0.94, 0.85, respectively, for echocardiogram). Analysis of electrocardiography-echocardiography paired data from 11 823 patients from an external institution indicated a higher sensitivity of automated HCM detection at a given positive predictive value compared with cardiologists (0.98 versus 0.81 at a positive predictive value of 0.01 for ECG and 0.78 versus 0.59 at a positive predictive value of 0.24 for echocardiogram).

Conclusions:
Federated learning improved the generalizability of models that use ECGs and echocardiograms to detect and differentiate HCM from other causes of hypertrophy compared with training within a single institution.
Prediction of Neurological Deterioration After Intracerebral Hemorrhage: The SIGNALS Score
Authors: He Quanwei , Guo Hongxiu , Bi Rentang , Chen Shaoli , Shen Jing , Long Chunnan , Li Man , Xia Yuanpeng , Zhang Lei , Sun Zhou , Chen Xiaolu , Wang Zhaowei , Gong Daokai , Xu Jingwen , Zhu Dondya , Wan Yan , Hu Bo 
Published: August 2022

Background
Intracerebral hemorrhage is the most disabling and lethal form of stroke. We aimed to develop a novel clinical score for neurological deterioration during hospitalization after intracerebral hemorrhage.

Methods and Results

We analyzed data from the CHERRY (Chinese Cerebral Hemorrhage: Mechanism and Intervention) study. Two‐thirds of eligible patients were randomly allocated into the training cohort (n=1027) and one‐third into the validation cohort (n=515). Multivariable logistic regression was used to identify factors associated with neurological deterioration (an increase in National Institutes of Health Stroke Scale of ≥4 or death) within 15 days after symptom onset. A prediction score was developed based on regression coefficients derived from the logistic model. The site, size, gender, National Institutes of Health Stroke Scale, age, leukocyte, sugar (SIGNALS) score was developed as a sum of individual points (0–8) based on site (1 point for infratentorial location), size (3 points for >20 mL of supratentorial hematoma volume or 2 points for >10 mL of infratentorial hematoma volume), sex (1 point for male sex), National Institutes of Health Stroke Scale score (1 point for >10), age (1 point for ≥70 years), white blood cell (1 point for>9.0×10
9
/L), and fasting blood glucose (1 point>7.0 mmol/L). The proportion of patients who suffered from neurological deterioration increased with higher SIGNALS score, showing good discrimination and good calibration in the training cohort (C statistic, 0.821; Hosmer‐Lemeshow test,
P
=0.687) and in the validation cohort (C statistic, 0.848; Hosmer‐Lemeshow test,
P
=0.592), respectively.

Conclusions
The SIGNALS score reliably predicts the risk of in‐hospital neurological deterioration of patients with intracerebral hemorrhage.
Sefer ha-Pardes by Jedaiah ha-Penini
Authors: Torollo David 
Published: August 2022

This groundbreaking new work is the first full critical edition and English translation of the Hebrew book Sefer ha-Pardes [The Book of the Orchard], written at the end of the thirteenth century by the Provençal Jewish author Jedaiah ha-Penini. It is purportedly an example of musar: a compilation of wise epigrams and meshalim [parables] that teach moral lessons on different topics, such as the service of God, friendship, the deceitfulness of the world, medicine, logic, music, magic, and poetry. However, it is in reality a compendium of sayings that reveal the author’s personal views and feelings on a variety of religious topics, secular sciences, and their practitioners.
David Torollo presents a fluent and illuminating English-Hebrew parallel text based on four sixteenth-century witnesses: three manuscripts and a printed edition. A rigorous study accompanies and contextualises the Hebrew work, exploring Sefer ha-Pardes’s transmission and reception in different places over time; its structure and content; its place in the intellectual environment and literary tradition of Provence; and possible lines of enquiry for future research.
This essential new work offers a significant contribution to scholarship in the field of Medieval Hebrew Hispano-Provencal literature.
Can Decision Theory Help End-Users Take the Appropriate Action in an Emergency?
Authors: Harvey Natalie J. , Western Luke M. , Dacre Helen F. , Capponi Antonio 
Published: August 2022

Abstract
Making decisions about the appropriate action to take when presented with uncertain information is difficult, particularly in an emergency response situation. Decision-makers can be influenced by factors such as how information is framed, their risk sensitivity, and the impact of false alarms. Uncertainty arising from limited knowledge of the current state or future outcome of an event is unavoidable when making decisions. However, there is no universally agreed method on the design and presentation of uncertainty information. The aim of this article is to demonstrate that decision theory can be applied to an ensemble of plausible realizations of a situation to build a transparent framework that can then be used to determine the optimal action by assigning losses to different decision outcomes. The optimal action is then visualized, enabling the uncertainty information to be presented in a condensed manner suitable for decision-makers. The losses are adaptable depending on the hazard and the individual operational model of the decision-maker. To illustrate this approach, decision theory will be applied to an ensemble of volcanic ash simulations used for the purpose of airline flight planning, focusing on the 2019 eruption of Russian volcano Raikoke. Three idealized scenarios are constructed to show the impact of different loss models on the optimal action. In all cases, applying decision theory can significantly alter the regions, and therefore potential flight tracks, identified as potentially hazardous. Thus, we show that different end-users would and should make different decisions when presented with the same probabilistic information based on their individual user requirements.
Mechanisms of a Meteorological Drought Onset: Summer 2020 to Spring 2021 in Southwestern North America
Authors: Seager Richard , Ting Mingfang , Alexander Patrick , Nakamura Jennifer , Liu Haibo , Li Cuihua , Simpson Isla R. 
Published: August 2022

Abstract
By summer 2021 moderate to exceptional drought impacted 28% of North America, focused west of the Mississippi, with serious impacts on fire, water resources, and agriculture. Here, using reanalyses and SST-forced climate models, we examine the onset and development of this southwestern drought from its inception in summer 2020 through winter and spring 2020/21. The drought severity in summer 2021 resulted from four consecutive prior seasons in which precipitation in the southwest United States was the lowest on record or, at least, extremely dry. The dry conditions in summer 2020 arose from internal atmospheric variability but are beyond the range of what the studied atmosphere models simulate for that season. From winter 2020 through spring 2021 the worsening drought conditions were guided by the development of a La Niña in the tropical Pacific Ocean. Decadal variability in the Pacific Ocean aided drought in the southern part of the region by driving the cool season to be drier during the last two decades. There is also evidence that the southern part of the region in spring is drying due to human-driven climate change. In sum the drought onset was driven by a combination of internal atmospheric variability and interannual climate variability and aided by natural decadal variability and human-driven climate change.
The Dynamics of a Barotropic Current Impinging on an Ice Front
Authors: Steiger Nadine , Darelius Elin , Kimura Satoshi , Patmore Ryan D. , Wåhlin Anna K. 
Published: August 2022

Abstract
The vertical front of ice shelves represents a topographic barrier for barotropic currents that transport a considerable amount of heat toward the ice shelves. The blocking effect of the ice front on barotropic currents has recently been observed to substantially reduce the heat transport into the cavity beneath the Getz Ice Shelf in West Antarctica. We use an idealized numerical model to study the vorticity dynamics of an externally forced barotropic current at an ice front and the impact of ice shelf thickness, ice front steepness, and ocean stratification on the volume flux entering the cavity. Our simulations show that thicker ice shelves block a larger volume of the barotropic flow, in agreement with geostrophic theory. However, geostrophy breaks locally at the ice front, where relative vorticity and friction become essential for the flow to cross the discontinuity in water column thickness. The flow entering the cavity accelerates and induces high basal melt rates in the frontal region. Tilting the ice front, as undertaken in sigma-coordinate models, reduces this acceleration because the flow is more geostrophic. Viscous processes—typically exaggerated in low-resolution models—break the potential vorticity constraint and bring the flow deeper into the ice shelf cavity. The externally forced barotropic current can only enter the cavity if the stratification is weak, as strong vertical velocities are needed at the ice front to squeeze the water column beneath the ice shelf. If the stratification is strong, vertical velocities are suppressed and the barotropic flow is almost entirely blocked by the ice front.

Significance Statement
Ice shelves in West Antarctica are thinning, mostly from basal melting through oceanic heat entering the underlying ice shelf cavities. Thinning of ice shelves reduces their ability to buttress the grounded ice resting upstream, leading to sea level rise. To model the ice sheet’s contribution to sea level rise more accurately, the processes governing the oceanic heat flux into the ice shelf cavity must be articulated. This modeling study investigates the dynamics of a depth-independent current approaching the ice shelf; it corroborates previous findings on the blocking of such a current at the ice front. The amount of water that enters the cavity strongly depends on ice shelf thickness and ocean stratification. For a well-mixed ocean, the upper part of the flow can dive underneath the ice shelf and increase basal melting near the ice front. In a stratified ocean, the approaching depth-independent current is almost entirely blocked by the ice front.
Development of an app-based maintenance programme to promote skin protection behaviour for patients with work-related skin diseases
Authors: Ristow Nele , Wilke Annika , Malte John Swen , Ludewig Michaela 
Published: August 2022

Objectives: Digital interventions are increasingly used to support behaviour change. In the prevention of chronic work-related skin diseases, the sustainable implementation of appropriate skin protection behaviour following tertiary individual prevention is important. However, there exists no intervention to support the maintenance of these behaviour changes until now. We report the systematic development of a technology-based maintenance programme to support patients to sustainably implement skin protection behaviour and to overcome barriers. Design: Complex intervention development based on a five-step multi-methods process. Setting: Tertiary individual prevention of work-related skin disease in Germany. Methods: Intervention development comprised the following steps: literature review, qualitative focus groups with stakeholders, quantitative assessment of the patients’ needs, development of a programme theory, and intervention development and concept validation. Results: We developed a concept for a complex intervention based on results from the literature review, with seven reviews meeting the criteria; qualitative focus groups involving three dermatologists, five health educators, two psychologists and three employees of an accident insurance institution; and a quantitative needs assessment with 72 patients. Key requirements were derived from this process: for example, the need to develop an app to self-monitor skin protection behaviour and skin condition and to inform the individual about ways of dealing with barriers encountered during the uptake and maintenance of skin protection behaviour. In addition, patients will participate in an individual goal-setting exercise to identify individual behavioural goals. Conclusion: A technology-based approach to the prevention of work-related skin diseases was developed. During the process of development, the perspectives of relevant stakeholders and the target group were considered in a participatory way.