bluuebunny/crossref_metadata_2025 huggingface dataset:
Structure‐preserving exponential wave integrator methods and the long‐time convergence analysis for the Klein‐Gordon‐Dirac equation with the small coupling constant
Authors: Li Jiyong , Jin Xiaoqian
Published: March 2023

Recently, the numerical methods for long‐time dynamics of PDEs with weak nonlinearity (or small potentials) have received more and more attention. For the Klein‐Gordon‐Dirac (KGD) equation with the small coupling constant , we propose two time symmetric and structure‐preserving exponential wave integrator Fourier pseudo‐spectral (TSSPEWIFP) methods under periodic boundary conditions. The new methods are proved to preserve the energy in discrete level and in addition the first one preserves the modified discrete mass. Through rigorous error analysis, we establish uniform error bounds of the numerical solutions at up to the time at for where and are the mesh size and time step, respectively, and depends on the regularity conditions. Compared with the results of existing numerical analysis, our analysis has the advantage of showing the long time numerical errors for the KGD equation with the small coupling constant. The tools for error analysis mainly include cut‐off technique and the standard energy method. We also extend the results on error bounds, structure‐preservation and time symmetry to the oscillatory KGD equation with wavelength at in time which is equivalent to the KGD equation with small coupling constant. Numerical experiments confirm that the theoretical results are correct. Our methods are novel because that to the best of our knowledge there has not been any energy‐preserving exponential wave integrator method and any relevant long time analysis for the KGD equation.
Impact of co‐teaching on general educator self‐reported knowledge and use of inclusive practices for students with emotional and behavioral disabilities: A pilot investigation
Authors: McKenna John W. , Newton Xiaoxia , Brigham Frederick
Published: March 2023

This pilot study examined the self‐reported knowledge and implementation of recommended practices for supporting students with emotional and/or behavioral disorders (EBDs) in general education classrooms. Participants were general educators who had either limited experience in co‐teaching with a special educator or general educators with more consistent experience co‐teaching with a special educator. General educators with frequent opportunities to co‐teach with a special educator reported significantly higher levels of knowledge of classroom management and differentiation procedures. Additionally, general educators with more frequent opportunities to co‐teach with a special educator reported significantly higher levels of use of classroom management practices. Based on these results, we suggest that in the absence of adequate direct support from special education professionals, students with EBD who are placed in general education settings may be denied adequate and appropriate educational opportunities. However, this hypothesis requires further investigation utilizing methods such as systematic observation.
Structural basis of the inhibition of cystathionine γ‐lyase from Toxoplasma gondii by propargylglycine and cysteine
Authors: Fernández‐Rodríguez Carmen , Conter Carolina , Oyenarte Iker , Favretto Filippo , Quintana Iban , Martinez‐Chantar Maria Luz , Astegno Alessandra , Martínez‐Cruz Luis Alfonso
Published: March 2023

Cystathionine γ‐lyase (CGL) is a PLP‐dependent enzyme that catalyzes the last step of the reverse transsulfuration route for endogenous cysteine biosynthesis. The canonical CGL‐catalyzed process consists of an α,γ‐elimination reaction that breaks down cystathionine into cysteine, α‐ketobutyrate, and ammonia. In some species, the enzyme can alternatively use cysteine as a substrate, resulting in the production of hydrogen sulfide (H2S). Importantly, inhibition of the enzyme and consequently of its H2S production activity, makes multiresistant bacteria considerably more susceptible to antibiotics. Other organisms, such as Toxoplasma gondii, the causative agent of toxoplasmosis, encode a CGL enzyme (TgCGL) that almost exclusively catalyzes the canonical process, with only minor reactivity to cysteine. Interestingly, the substitution of N360 by a serine (the equivalent amino acid residue in the human enzyme) at the active site changes the specificity of TgCGL for the catalysis of cystathionine, resulting in an enzyme that can cleave both the CγS and the CβS bond of cystathionine. Based on these findings and to deepen the molecular basis underlying the enzyme‐substrate specificity, we have elucidated the crystal structures of native TgCGL and the variant TgCGL‐N360S from crystals grown in the presence of cystathionine, cysteine, and the inhibitor d,l‐propargylglycine (PPG). Our structures reveal the binding mode of each molecule within the catalytic cavity and help explain the inhibitory behavior of cysteine and PPG. A specific inhibitory mechanism of TgCGL by PPG is proposed.
Curcumin in the treatment of liver cancer: From mechanisms of action to nanoformulations
Authors: Shelash Al‐Hawary Sulieman Ibraheem , Abdalkareem Jasim Saade , M. Kadhim Mustafa , Jaafar Saadoon Sarah , Ahmad Irfan , Romero Parra Rosario Mireya , Hasan Hammoodi Suzan , Abulkassim Roua , M. Hameed Noora , K. Alkhafaje Waleed , Mustafa Yasser Fakri , Javed Ansari Mohammad
Published: March 2023

Liver cancer is the sixth most prevalent cancer and ranks third in cancer‐related death, after lung and colorectal cancer. Various natural products have been discovered as alternatives to conventional cancer therapy strategies, including radiotherapy, chemotherapy, and surgery. Curcumin (CUR) with antiinflammatory, antioxidant, and antitumor activities has been associated with therapeutic benefits against various cancers. It can regulate multiple signaling pathways, such as PI3K/Akt, Wnt/β‐catenin, JAK/STAT, p53, MAPKs, and NF‐ĸB, which are involved in cancer cell proliferation, metastasis, apoptosis, angiogenesis, and autophagy. Due to its rapid metabolism, poor oral bioavailability, and low solubility in water, CUR application in clinical practices is restricted. To overcome these limitations, nanotechnology‐based delivery systems have been applied to use CUR nanoformulations with added benefits, such as reducing toxicity, improving cellular uptake, and targeting tumor sites. Besides the anticancer activities of CUR in combating various cancers, especially liver cancer, here we focused on the CUR nanoformulations, such as micelles, liposomes, polymeric, metal, and solid lipid nanoparticles, and others, in the treatment of liver cancer.
Xanthohumol inhibits non‐small cell lung cancer via directly targeting T‐lymphokine‐activated killer cell‐originated protein kinase
Authors: Zhao Shuang , Cui Jinling , Cao Lixing , Han Kai , Ma Xuan , Chen Hui , Yin Shutao , Zhao Chong , Ma Changwei , Hu Hongbo
Published: March 2023

Xanthohumol is a principal prenylated chalcone isolated from hops. Previous studies have shown that xanthohumol was effective against various types of cancer, but the mechanisms, especially the direct targets for xanthohumol to exert an anticancer effect, remain elusive. Overexpression of T‐lymphokine‐activated killer cell‐originated protein kinase (TOPK) promotes tumorigenesis, invasion and metastasis, implying the likely potential for targeting TOPK in cancer prevention and treatment. In the present study, we found that xanthohumol significantly inhibited the cell proliferation, migration and invasion of non‐small cell lung cancer (NSCLC) in vitro and suppressed tumor growth in vivo, which is well correlated with inactivating TOPK, evidenced by reduced phosphorylation of TOPK and its downstream signaling histone H3 and Akt, and decreased its kinase activity. Moreover, molecular docking and biomolecular interaction analysis showed that xanthohumol was able to directly bind to the TOPK protein, suggesting that TOPK inactivation by xanthohumol is attributed to its ability to directly interact with TOPK. The findings of the present study identified TOPK as a direct target for xanthohumol to exert its anticancer activity, revealing novel insight into the mechanisms underlying the anticancer activity of xanthohumol.
Adopting Dr. Robot: Responses to competitor adoption of innovation
Authors: Sundaresan Shirish , Boysen Andrew , Nerkar Atul
Published: March 2023

Research Summary

How do an organization's task requirements affect the ways in which it reacts to competitors' strategic investments? This study uses a novel measure of task requirements (Case Mix Index), to test the competitive and spillover effects of prior adoption on a focal organization's timing of adoption, while accounting for the underlying demand‐side drivers of adoption. Results of an empirical study of the adoption of robotic surgery systems by U.S. hospitals validate our measure as a predictor of the timing of adoption. Further, this measure moderates the effect of adoption by competitors, delaying investment in the technology for those hospitals most likely to adopt robotic surgery based on their patient population, while accelerating adoption for those with the lowest demand for the technology.

Managerial Summary

When a nearby competitor adopts an important innovation, an organization may react by either imitating their strategy in order to stay competitive or deferring the choice to adopt the technology in order to differentiate and focus elsewhere. Which of these paths it decides to follow may be influenced by the type and difficulty of problems it handles for its customers (task requirements). Using the adoption of robotic surgery in the U.S. Hospital industry, we find that organizations that serve more difficult customer needs defer investment in response to a competitor's technology adoption, while those who address less difficult problems on average are likely to respond by accelerating adoption.
Unbinned multivariate observables for global SMEFT analyses from machine learning
Authors: Ambrosio Raquel Gomez , ter Hoeve Jaco , Madigan Maeve , Rojo Juan , Sanz Veronica
Published: March 2023

Abstract

Theoretical interpretations of particle physics data, such as the determination of the Wilson coefficients of the Standard Model Effective Field Theory (SMEFT), often involve the inference of multiple parameters from a global dataset. Optimizing such interpretations requires the identification of observables that exhibit the highest possible sensitivity to the underlying theory parameters. In this work we develop a flexible open source frame-work, ML4EFT, enabling the integration of unbinned multivariate observables into global SMEFT fits. As compared to traditional measurements, such observables enhance the sensitivity to the theory parameters by preventing the information loss incurred when binning in a subset of final-state kinematic variables. Our strategy combines machine learning regression and classification techniques to parameterize high-dimensional likelihood ratios, using the Monte Carlo replica method to estimate and propagate methodological uncertainties. As a proof of concept we construct unbinned multivariate observables for top-quark pair and Higgs+Z production at the LHC, demonstrate their impact on the SMEFT parameter space as compared to binned measurements, and study the improved constraints associated to multivariate inputs. Since the number of neural networks to be trained scales quadratically with the number of parameters and can be fully parallelized, the ML4EFT framework is well-suited to construct unbinned multivariate observables which depend on up to tens of EFT coefficients, as required in global fits.
Institutions and economic development: new measurements and evidence
Authors: Acquah Esther , Carbonari Lorenzo , Farcomeni Alessio , Trovato Giovanni
Published: March 2023

We propose a new set of indices to capture the multidimensionality of a country’s institutional setting. Our indices are obtained by employing a dimension reduction approach on the institutional variables provided by the Fraser Institute (2018). We estimate the impact that institutions have on the level and the growth rate of per capita GDP, using a large sample of countries over the period 1980–2015. To identify the causal effect of our institutional indices on a country’s GDP we employ the Generalized Propensity Score method. Institutions matter especially in low- and middle-income countries, and not all institutions are alike for economic development. We also document non-linearities in the causal effects that different institutions have on growth and the presence of threshold effects.
Innovate to lead or innovate to prevail: When do monopolistic rents induce growth?
Authors: Piazza Roberto , Zheng Yu
Published: March 2023

This paper extends the standard Schumpeterian model of creative destruction by allowing the cost of innovation for followers to increase in their technological distance from the leader. This assumption is motivated by the observation that the more technologically advanced the leader is, the harder it is for a follower to leapfrog without incurring extra cost for using leader’s patented knowledge. Under this R &D cost structure, leaders have an incentive to play an “endpoint strategy": they increase their technological advantage, counting on the fact that followers will eventually stop innovating—allowing leadership to prevail. We find that several results in the standard model fail to hold. In addition to the high-growth steady state in which only followers innovate, there now exists a second saddle-path-stable steady state: a low-growth steady state that features both leaders and followers innovating. A policy that increases monopolistic rents or extends parent duration can push the economy toward the low-growth steady state, causing, in some cases, irreversible harm to long-run growth.
Isomonodromic Tau Functions on a Torus as Fredholm Determinants, and Charged Partitions
Authors: Del Monte Fabrizio , Desiraju Harini , Gavrylenko Pavlo
Published: March 2023

We prove that the isomonodromic tau function on a torus with Fuchsian singularities and generic monodromies in $$GL(N,{\mathbb {C}})$$

G
L
(
N
,
C
)

can be written in terms of a Fredholm determinant of Plemelj operators. We further show that the minor expansion of this Fredholm determinant is described by a series labeled by charged partitions. As an example, we show that in the case of $$SL(2,{\mathbb {C}})$$

S
L
(
2
,
C
)

this combinatorial expression takes the form of a dual Nekrasov–Okounkov partition function, or equivalently of a free fermion conformal block on the torus. Based on these results we also propose a definition of the tau function of the Riemann–Hilbert problem on a torus with generic jump on the A-cycle.
Can the Realization of an External Wirsungostomy be an Option for High‐Risk Pancreatic Anastomosis After Pancreaticoduodenectomy?
Authors: Codjia Tatiana , Roussel Edouard , Papet Eloise , Pinson Jean , Monge Matthieu , Tortajada Pauline , Tuech Jean‐Jacques , Schwarz Lilian
Published: March 2023

Background

Clinically relevant postoperative pancreatic fistula (POPF) occurs in 15–20% of patients after pancreaticoduodenectomy (PD) and reintervention in the setting of Grade C POPF remains associated with a mortality rate of up to 25%. In patients at high risk of POPF, PD with external wirsungostomy (EW) could be a safe alternative that avoids pancreatico‐enteric anastomosis while preserving the remnant pancreas.

Methods

Of the 155 consecutive patients who underwent PD from November 2015 to December 2020, 10 patients were managed using an EW, all with a fistula risk score (FRS) ≥ 7 and BMI ≥30 kg/m2, and/or major associated abdominal surgery. The pancreatic duct was cannulated with a polyethylene tube to allow good external drainage of the pancreatic fluid. We retrospectively analyzed postoperative complications and endocrine and exocrine insufficiencies.

Results

The median alternative FRS was 36.9% [22.1–45.2]. There was no postoperative death. The 90‐day overall severe complication (grade  ≥3) rate was 30% (n = 3 patients), no patient required reoperation, and 2 hospital readmissions occurred. 3 patients experienced Grade B POPF (30%), managed using image‐guided drainage for 2 patients. The external pancreatic drain was removed after a median drainage time of 75 days [63–80]. Two patients presented with late symptoms (> 6 months) warranting interventional management (pancreaticojejunostomy and transgastric drainage). Six patients experienced significant weight loss (> 2 kg) 3 months after surgery. One year after surgery, 4 patients still complained of diarrhea and were treated with transit‐delaying drugs. One patient presented new‐onset diabetes one year after surgery, and 1 of the 4 patients with preexisting diabetes experienced worsening disease.

Conclusion

EW after PD might be a solution to reduce post‐operative mortality following PD in high‐risk patients.
Scaling Surgical Resources: A Capacity Analysis of C‐arm Machines in Haiti Following the 2021 Earthquake
Authors: Franco Helena , Simister Samuel , Njai Abdoulie , Woolley Pierre Marie , Joseph Michelle Nyah
Published: March 2023

Background

In 2021, a 7.2 magnitude earthquake struck Haiti resulting in a surge of orthopaedic trauma requiring immediate surgical treatment. Safe and efficient operative management of orthopaedic trauma injuries requires intraoperative fluoroscopy through C‐arm machines. The Haitian Health Network (HHN) received a philanthropic donation of three C‐arm machines and considered an analytical tool may guide efficacious placement of those machines. The study objective was to develop and apply a clinical needs and hospital readiness measuring tool relevant to C‐arm machines, which may guide decision‐makers, such as HHN, in response to an emergency situation with a surge in need for orthopaedic treatment.

Methods

An online survey to assess surgical volume and capacity was created and then completed by a senior surgeon or hospital administrator based at hospitals within the HHN. Multiple‐choice and free‐text answer data were collected and classified into five categories: staff, space, stuff, systems, and surgical capacity. Each hospital received a final score out of 100, calculated by equal weighting of each category.

Results

Ten out of twelve hospitals completed the survey. The average weighted score for the staff category was 10.2 (SD 5.12), the space category was 13.1 (SD 4.09), the stuff category was 15.6 (SD 2.56), the systems category was 12.25 (SD 6.50), and the surgical capacity category was 9.5 (SD 6.47). The average final hospital scores ranged from 29.5 to 83.0.

Conclusion

This analysis tool provided data as to the clinical demand and capabilities of hospitals within the HHN to receive a C‐arm machine and reaffirmed the critical need for more C‐arms in Haiti. This methodology may be utilised by other health systems to provide data to distribute orthopaedic trauma equipment, which would benefit communities during periods of surge capacity, such as natural disasters.
On Two Coupled Degenerate Parabolic Equations Motivated by Thermodynamics
Authors: Mielke Alexander
Published: March 2023

We discuss a system of two coupled parabolic equations that have degenerate diffusion constants depending on the energy-like variable. The dissipation of the velocity-like variable is fed as a source term into the energy equation leading to conservation of the total energy. The motivation of studying this system comes from Prandtl’s and Kolmogorov’s one- and two-equation models for turbulence, where the energy-like variable is the mean turbulent kinetic energy. Because of the degeneracies, there are solutions with time-dependent support like in the porous medium equation, which is contained in our system as a special case. The motion of the free boundary may be driven by either self-diffusion of the energy-like variable or by dissipation of the velocity-like variable. The crossover of these two phenomena is exemplified for the associated planar traveling fronts. We provide existence of suitably defined weak and very weak solutions. After providing a thermodynamically motivated gradient structure, we also establish convergence into steady state for bounded domains and provide a conjecture on the asymptotically self-similar behavior of the solutions in $$\mathbb {R}^d$$

R

d

for large times.
Esmethadone-HCl (REL-1017): a promising rapid antidepressant
Authors: Fava Maurizio , Stahl Stephen M. , De Martin Sara , Mattarei Andrea , Bettini Ezio , Comai Stefano , Alimonti Andrea , Bifari Francesco , Pani Luca , Folli Franco , Guidetti Clotilde , Furlan Alberto , Sgrignani Jacopo , Locatelli Patrizia , Cavalli Andrea , O’Gorman Cedric , Traversa Sergio , Inturrisi Charles E. , Pappagallo Marco , Manfredi Paolo L.
Published: March 2023

This review article presents select recent studies that form the basis for the development of esmethadone into a potential new drug. Esmethadone is a promising member of the pharmacological class of uncompetitive N-methyl-D-aspartate receptor (NMDAR) antagonists that have shown efficacy for major depressive disorder (MDD) and other diseases and disorders, such as Alzheimer’s dementia and pseudobulbar affect. The other drugs in the novel class of NMDAR antagonists with therapeutic uses that are discussed for comparative purposes in this review are esketamine, ketamine, dextromethorphan, and memantine. We present in silico, in vitro, in vivo, and clinical data for esmethadone and other uncompetitive NMDAR antagonists that may advance our understanding of the role of these receptors in neural plasticity in health and disease. The efficacy of NMDAR antagonists as rapid antidepressants may advance our understanding of the neurobiology of MDD and other neuropsychiatric diseases and disorders.
Diagnosis and treatment of MPN in real life: exploratory and retrospective chart review including 960 MPN patients diagnosed with ET or MF in Germany
Authors: Schmidt Andreas , Bernhardt Christiane , Bürkle Dieter , Fries Stefan , Hannig Carla V. , Jentsch-Ullrich Kathleen , Josting Andreas , Kreher Stephan , Reiser Marcel , Steinmetz Hans Tilman , Tesch Hans , Terner Stephanie , Schulte Alexander , Crodel Carl C. , Palandri Francesca , Heidel Florian H.
Published: March 2023

Purpose

The WHO 2016 re-classification of myeloproliferative neoplasms resulted in a separation of essential thrombocythemia (ET) from the pre-fibrotic and fibrotic (overt) phases of primary myelofibrosis (MF). This study reports on a chart review conducted to evaluate the real life approach regarding clinical characteristics, diagnostic assessment, risk stratification and treatment decisions for MPN patients classified as ET or MF after implementation of the WHO 2016 classification.

Methods

In this retrospective chart review, 31 office-based hematologists/oncologists and primary care centers in Germany participated between April 2021 and May 2022. Physicians reported available data obtained from patient charts via paper–pencil based survey (secondary use of data). Patient features were evaluated using descriptive analysis, also including diagnostic assessment, therapeutic strategies and risk stratification.

Results

Data of 960 MPN patients diagnosed with essential thrombocythemia (ET) (n = 495) or myelofibrosis (MF) (n = 465) after implementation of the revised 2016 WHO classification of myeloid neoplasms was collected from the patient charts. While they met at least one minor WHO-criteria for primary myelofibrosis, 39.8% of those diagnosed with ET did not have histological BM testing at diagnosis. 63.4% of patients who were classified as having MF, however, did not obtain an early prognostic risk assessment. More than 50% of MF patients showed characteristics consistent with the pre-fibrotic phase, which was emphasized by the frequent use of cytoreductive therapy. Hydroxyurea was the most frequently used cytoreductive medication in 84.7% of ET and 53.1% of MF patients. While both ET and MF cohorts showed cardiovascular risk factors in more than 2/3 of the cases, the use of platelet inhibitors or anticoagulants varied between 56.8% in ET and 38.1% in MF patients.

Conclusions

Improved histopathologic diagnostics, dynamic risk stratification including genetic risk factors for cases of suspected ET and MF are recommended for precise risk assessment and therapeutic stratification according to WHO criteria.
Comparison of outcomes of proximal versus distal and combined splenic artery embolization in the management of blunt splenic injury: a report of 202 cases from a single trauma center
Authors: Lin Being-Chuan , Wu Cheng-Hsien , Wong Yon-Cheong , Chen Huan-Wu , Fu Chen-Ju , Huang Chen-Chih , Wu Chen-Te , Ku Yi-Kang , Chen Chien-Cheng , Sheng Ting-Wen , Chang Chun-Bi
Published: March 2023

Background

To compare the outcomes of blunt splenic injuries (BSI) managed with proximal (P) versus distal (D) versus combined (C) splenic artery embolization (SAE).

Methods

This retrospective study included patients with BSI who demonstrated vascular injuries on angiograms and were managed with SAE between 2001 and 2015. The success rate and major complications (Clavien–Dindo classification ≥ III) were compared between the P, D, and C embolizations.

Results

In total, 202 patients were enrolled (P, n = 64, 31.7%; D, n = 84, 41.6%; C, n = 54, 26.7%). The median injury severity score was 25. The median times from injury to SAE were 8.3, 7.0, and 6.6 h for the P, D, and C embolization, respectively. The overall haemostasis success rates were 92.6%, 93.8%, 88.1%, and 98.1% in the P, D, and C embolizations, respectively, with no significant difference (p = 0.079). Additionally, the outcomes were not significantly different between the different types of vascular injuries on angiograms or the materials used in the location of embolization. Splenic abscess occurred in six patients (P, n = 0; D, n = 5; C, n = 1), although it occurred more commonly in those who underwent D embolization with no significant difference (p = 0.092).

Conclusions

The success rate and major complications of SAE were not significantly different regardless of the location of embolization. The different types of vascular injuries on angiograms and agents used in different embolization locations also did not affect the outcomes.

Graphical abstract
A deep learning-based histopathology classifier for Focal Cortical Dysplasia
Authors: Vorndran Jörg , Neuner Christoph , Coras Roland , Hoffmann Lucas , Geffers Simon , Honke Jonas , Herms Jochen , Roeber Sigrun , Hamer Hajo , Brandner Sebastian , Hartlieb Till , Pieper Tom , Kudernatsch Manfred , Bien Christian G. , Kalbhenn Thilo , Simon Matthias , Adle-Biassette Homa , Cienfuegos Jesús , Di Giacomo Roberta , Garbelli Rita , Miyata Hajime , Mühlebner Angelika , Raicevic Savo , Rauramaa Tuomas , Rogerio Fabio , Blümcke Ingmar , Jabari Samir
Published: March 2023

A light microscopy-based histopathology diagnosis of human brain specimens obtained from epilepsy surgery remains the gold standard to confirm the underlying cause of a patient’s focal epilepsy and further inform postsurgical patient management. The differential diagnosis of neocortical specimens in the realm of epilepsy surgery remains, however, challenging. Herein, we developed an open access, deep learning-based classifier to histopathologically assess whole slide microscopy images (WSI) and to automatically recognize various subtypes of Focal Cortical Dysplasia (FCD), according to the ILAE consensus classification update of 2022. We trained a convolutional neuronal network (CNN) with fully digitalized WSI of hematoxylin–eosin stainings obtained from 125 patients covering the spectrum of mild malformation of cortical development (mMCD), mMCD with oligodendroglial hyperplasia in epilepsy (MOGHE), FCD ILAE Type 1a, 2a and 2b using 414 formalin-fixed and paraffin-embedded archival tissue blocks. An additional series of 198 postmortem tissue blocks from 59 patients without neurological disorders served as control to train the CNN for homotypic frontal, temporal and occipital areas and heterotypic Brodmann areas 4 and 17, entorhinal cortex and dentate gyrus. Special stains and immunohistochemical reactions were used to comprehensively annotate the region of interest. We then programmed a novel tile extraction pipeline and graphical dashboard to visualize all areas on the WSI recognized by the CNN. Our deep learning-based classifier is able to compute 1000 × 1000 µm large tiles and recognizes 25 anatomical regions and FCD categories with an accuracy of 98.8% (F1 score = 0.82). Microscopic review of regions predicted by the network confirmed these results. This deep learning-based classifier will be made available as online web application to support the differential histopathology diagnosis in neocortical human brain specimens obtained from epilepsy surgery. It will also serve as blueprint to build a digital histopathology slide suite addressing all major brain diseases encountered in patients with surgically amenable focal epilepsy.
Spatial coherence patterns of extreme winter precipitation in the U.S.
Authors: Banerjee Abhirup , Kemter Matthias , Goswami Bedartha , Merz Bruno , Kurths Jürgen , Marwan Norbert
Published: March 2023

Extreme precipitation events have a significant impact on life and property. The U.S. experiences huge economic losses due to severe floods caused by extreme precipitation. With the complex terrain of the region, it becomes increasingly important to understand the spatial variability of extreme precipitation to conduct a proper risk assessment of natural hazards such as floods. In this work, we use a complex network-based approach to identify distinct regions exhibiting spatially coherent precipitation patterns due to various underlying climate mechanisms. To quantify interactions between event series of different locations, we use a nonlinear similarity measure, called the edit-distance method, which considers not only the occurrence of the extreme events but also their intensity, while measuring similarity between two event series. Using network measures, namely, degree and betweenness centrality, we are able to identify the specific regions affected by the landfall of atmospheric rivers in addition to those where the extreme precipitation due to storm track activity is modulated by different mountain ranges such as the Rockies and the Appalachians. Our approach provides a comprehensive picture of the spatial patterns of extreme winter precipitation in the U.S. due to various climate processes despite its vast, complex topography.
Deployment of distributed ledger and decentralized technology for transition to smart industries
Authors: Anthony Bokolo
Published: March 2023

Industries are now deploying smart initiatives and innovative business models towards digital transformation. One of such initiatives is the adoption of distributed ledger technology (DLT) which promises to support smart industrial revolution. DLT facilitates non trusted entities to communicate and achieve a consensus in a fully distributed method through an immutable and cryptographically secure ledger. DLT ensures traceability and secure exchange of information while ensuring confidentiality and portability of data. However, only fewer studies have explored the extent to which DLT can support digitalization to achieve smart industrial process. Besides, the governance role of DLT in industrial sectors is still considered a nascent domain of research and DLT governance design and archetypes for smart industries are still in the early stage. Also, there are fewer studies in the literature that presents consensus mechanisms for integrating DLT for digitalization of smart industries. Grounded on the secondary data this study examines the practical benefits and challenges faced in achieving a smart industrial operation. Findings from this study identifies governance and security issues that influences DLT deployment in industrial sectors. More importantly, several factors that impacts the deployment of DLT for smart industries are presented. Implications from this study will be useful for industrial regulators, practitioners and researchers interested in gaining innovative insights about how smart industries can leverage DLT to create value for competitive advantage.
Stochastic games with lexicographic objectives
Authors: Chatterjee Krishnendu , Katoen Joost-Pieter , Mohr Stefanie , Weininger Maximilian , Winkler Tobias
Published: March 2023

We study turn-based stochastic zero-sum games with lexicographic preferences over objectives. Stochastic games are standard models in control, verification, and synthesis of stochastic reactive systems that exhibit both randomness as well as controllable and adversarial non-determinism. Lexicographic order allows one to consider multiple objectives with a strict preference order. To the best of our knowledge, stochastic games with lexicographic objectives have not been studied before. For a mixture of reachability and safety objectives, we show that deterministic lexicographically optimal strategies exist and memory is only required to remember the already satisfied and violated objectives. For a constant number of objectives, we show that the relevant decision problem is in $$\textsf{NP}\cap \textsf{coNP}$$

NP
∩
coNP

, matching the current known bound for single objectives; and in general the decision problem is $$\textsf{PSPACE}$$
PSPACE
-hard and can be solved in $$\textsf{NEXPTIME}\cap \textsf{coNEXPTIME}$$

NEXPTIME
∩
coNEXPTIME

. We present an algorithm that computes the lexicographically optimal strategies via a reduction to the computation of optimal strategies in a sequence of single-objectives games. For omega-regular objectives, we restrict our analysis to one-player games, also known as Markov decision processes. We show that lexicographically optimal strategies exist and need either randomization or finite memory. We present an algorithm that solves the relevant decision problem in polynomial time. We have implemented our algorithms and report experimental results on various case studies.
Protean career processes in young adults:
Relationships with perceived future employability, educational performance, and
commitment
Authors: Kim Sujin , Creed Peter A. , Hood Michelle , Bath Debra
Published: March 2023

Protean career processes of vocational identity awareness, career
adaptability, and career agency have been hypothesized to mediate the relationships between
protean career orientation and career-related outcomes. To date, the role of these process
mechanisms has not been assessed directly in young adults, and little attention has been
paid to educational outcomes, which are important career-related goals for young people on
the way to their desired career. To address this gap, we tested this indirect-effects model
in a sample of young adult undergraduates (N = 396;
Mage = 20.19, SD = 2.99; 72.2% women) and included career-related goals
(perceived future employability, educational performance, and commitment) as outcomes.
Identity awareness and career adaptability partially explained the relationship between
protean career orientation and perceived future employability and completely explained the
relationships with educational performance and commitment. Contrary to protean career
theory, there were no significant indirect paths via career agency to any of the
outcomes.
“I’ll be Okay”: Survivors’ Perspectives on Participation in Domestic Violence Research
Authors: Dragiewicz Molly , Woodlock Delanie , Easton Helen , Harris Bridget , Salter Michael
Published: March 2023

Purpose

This article investigates survivors’ experiences participating in research interviews about technology-facilitated domestic violence. University research ethics committees often assume that participating in research on violence and abuse is distressing for survivors. Scholars have called for research testing this assumption. This article contributes to the evidence base on the benefits and risks of asking research participants about gender-based violence.

Methods

This article is based on semi-structured interviews with 20 Australian domestic violence survivors. Template analysis was used to code the interviews and develop key themes.

Results

The five themes derived from the interviews include reflection on recovery and personal growth; helping other women; rejecting victim-shaming; empowerment; and the importance of timing.

Conclusion

All participants reported positive experiences taking part in the study. However, the authors noticed substantial differences in participant narratives across service cohorts. The implications of recruiting through channels associated with different points in trauma trajectories warrant attention.
Risk Factors for Gambling Disorder: A Systematic Review
Authors: Moreira Diana , Azeredo Andreia , Dias Paulo
Published: March 2023

Gambling disorder is a common and problematic behavioral disorder associated with depression, substance abuse, domestic violence, bankruptcy, and high suicide rates. In the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5), pathological gambling was renamed “gambling disorder” and moved to the Substance-Related and Addiction Disorders chapter to acknowledge that research suggests that pathological gambling and alcohol and drug addiction are related. Therefore, this paper provides a systematic review of risk factors for gambling disorder. Systematic searches of EBSCO, PubMed, and Web of Science identified 33 records that met study inclusion criteria. A revised study acknowledges as risk factors for developing/maintaining a gambling disorder being a single young male, or married for less than 5 years, living alone, having a poor education, and struggling financially.
Learn an Index Operator by CNN for Solving Diffusive Optical Tomography: A Deep Direct Sampling Method
Authors: Guo Ruchi , Jiang Jiahua , Li Yi
Published: March 2023

In this work, we investigate the diffusive optical tomography (DOT) problem in the case that limited boundary measurements are available. Motivated by the direct sampling method (DSM) proposed in Chow et al. (SIAM J Sci Comput 37(4):A1658–A1684, 2015), we develop a deep direct sampling method (DDSM) to recover the inhomogeneous inclusions buried in a homogeneous background. In this method, we design a convolutional neural network to approximate the index functional that mimics the underling mathematical structure. The benefits of the proposed DDSM include fast and easy implementation, capability of incorporating multiple measurements to attain high-quality reconstruction, and advanced robustness against the noise. Numerical experiments show that the reconstruction accuracy is improved without degrading the efficiency, demonstrating its potential for solving the real-world DOT problems.
Recent Advances in Various Starch Formulation for Wastewater Purification via Adsorption Technique: A Review
Authors: Abd El-Ghany Nahed A , Elella Mahmoud H. Abu , Abdallah Heba M. , Mostafa Mervat S. , Samy Moshera
Published: March 2023

Water purification is considered one of the most essential issues in our lives. Therefore, the contamination of water surfaces owing to the hasty upsurge in industrialization has received great global attention because of its potential danger to human health and the eco-system. Particularly, the discharge of various non-biodegradable contaminants into the water body—heavy metal ions, organic dyes, pharmaceutical antibiotics, pesticides, and oils—causes these contaminants to accumulate on the water's surface and have harmful impacts on humans and the environment. Several conventional methods can be applied to solve this problem, including chemical oxidation, precipitation, coagulation, and so on. However, they suffer from serious limitations: high cost, limited functionality, prolonged and heavy energy use, and poor separation efficiency. Conversely, the adsorption technique has recently attracted a lot of attention for wastewater treatment thanks to its remarkable benefits of being a simple, highly selective, and low-cost technique. Recently, natural polysaccharides (especially starch)-based adsorbents have received great interest in water purification owing to their outstanding properties, including being easily available, non-toxic, low-cost, biodegradable, and biocompatible. However, it possesses notable drawbacks that prevent it from being used alone as an adsorbent for wastewater treatment, including low thermal stability, slight water solubility, and rapid degradability in water. Therefore, this review highlights a comprehensive presentation about various starch modifications: starch-based grafts, hydrogels, aerogels, beads, nanofibers, and nanocomposite formulations to remove several toxic contaminants, including toxic heavy metal ions, organic dyes, pharmaceutical antibiotics, pesticides, and oils.
Analysis of security and privacy issues in wearables for minors
Authors: Fúster Jaime , Solera-Cotanilla Sonia , Pérez Jaime , Vega-Barbas Mario , Palacios Rafael , Álvarez-Campana Manuel , Lopez Gregorio
Published: March 2023

The increased use of wearables in recent years has fostered a great technological development in this area, although without the appropriate supervision usability may go first than security. In addition to this, the fact that wearables have been requiring more and more personal data from the user makes them attractive devices for an attacker. In this paper we propose a set of tests for evaluating the security and privacy of wearables and we apply them to analyse the security and privacy of a set of commercial wearables that are targeted at minors, who represent a group with especially high requirements in this regard. We define the testing scenario, expose the tools to support the research, and specify the testing process to be followed. Based on the obtained results, although the considered low-end devices are broadly speaking less secure than high-end ones, most of them present security and privacy flaws, which illustrates the necessity of regulation that ensures the fulfilment of appropriate security and privacy requirements.
TTL: transformer-based two-phase transfer learning for cross-lingual news event detection
Authors: Hettiarachchi Hansi , Adedoyin-Olowe Mariam , Bhogal Jagdev , Gaber Mohamed Medhat
Published: March 2023

Today, we have access to a vast data amount, especially on the internet. Online news agencies play a vital role in this data generation, but most of their data is unstructured, requiring an enormous effort to extract important information. Thus, automated intelligent event detection mechanisms are invaluable to the community. In this research, we focus on identifying event details at the sentence and token levels from news articles, considering their fine granularity. Previous research has proposed various approaches ranging from traditional machine learning to deep learning, targeting event detection at these levels. Among these approaches, transformer-based approaches performed best, utilising transformers’ transferability and context awareness, and achieved state-of-the-art results. However, they considered sentence and token level tasks as separate tasks even though their interconnections can be utilised for mutual task improvements. To fill this gap, we propose a novel learning strategy named Two-phase Transfer Learning (TTL) based on transformers, which allows the model to utilise the knowledge from a task at a particular data granularity for another task at different data granularity, and evaluate its performance in sentence and token level event detection. Also, we empirically evaluate how the event detection performance can be improved for different languages (high- and low-resource), involving monolingual and multilingual pre-trained transformers and language-based learning strategies along with the proposed learning strategy. Our findings mainly indicate the effectiveness of multilingual models in low-resource language event detection. Also, TTL can further improve model performance, depending on the involved tasks’ learning order and their relatedness concerning final predictions.
Impact of Intensive Forest Management Practices on Wood Quality from Conifers: Literature Review and Reflection on Future Challenges
Authors: Barrette Julie , Achim Alexis , Auty David
Published: March 2023

Purpose of Review

Intensive forest management practices are being implemented worldwide to meet future global demand for wood and wood products while facilitating the protection of natural forest ecosystems. A potential decline in wood properties associated with rapid tree growth makes it essential to quantify the potential impact of intensive management on the process of wood formation and, in turn, on its suitability for various end-uses.

Recent Findings

Wood produced over short rotations is generally of lower quality because wood properties tend to improve with cambial age (i.e. the number of annual growth rings from the pith). The intensification of silvicultural practices can thus have measurable consequences for the forest products value chain. The use of new planting material from tree improvement programs could offset such effects, but questions arise as to the effects of a changing climate on wood produced from these plantations and the best silvicultural approaches to manage them.

Based on these recent findings, we provide reflections on the need for a modelling framework that uses the effects of cambial age, ring width and position along the stem to summarise the effects of tree growth scenarios on wood properties. We then present challenges related to our limited understanding of the effects of several drivers of wood properties, such as climate variation, genetic material, and forest disturbances, among others, and highlight the need for further data collection efforts to better anticipate the quality attributes of the future wood fibre resource. We conclude by providing examples of promising new tools and technologies that will help move wood quality research forward by allowing (1) fast, efficient characterisation of wood properties, and (2) up-scaling predictions at the landscape level to inform forest management decisions.
Unwarranted variations in end-of-life care and the impact of using an electronic coordination system
Authors: Chumbley Karen , Wilson Tim , Ison Erica , Orlowski Andi
Published: March 2023

This study looks at the variations in end-of-life care in North-East Essex (eastern England) combining hospital records, official death records and the local electronic end-of-life coordination tool. These differences included dying in hospital (versus a general wish to die in the usual place of residence), and inequity in care provision: the place of death varying according to the cause of death (even for highly predictable conditions); and deprivation being associated with a greater likelihood of dying in hospital. There was a positive correlation between the use of an electronic end-of-life coordination system and dying in the preferred place of care. The results suggest two actions for policy makers. First, look at variations in end-of-life care so that areas of need can be identified. Second, use of an electronic end-of-life coordination tool is correlated with a reduction in unwarranted variation in the place of death.