bluuebunny/crossref_metadata_2025_split huggingface dataset:
Characterisation of a high granularity multi-channel prompt γ-ray detection system prototype for proton range verification based on the PETsys TOFPET2 ASIC
Authors: Novgorodova O. , Glatte A. , Hentges R. , Kögler T. , Lutz B. , Roemer K. , Teichmann T. , Weinberger D. , Straessner A. 
Published: February 2024

Abstract
Proton therapy requires range verification in order to
exploit its full potential. One of the most promising approaches is
to monitor prompt gamma-rays produced by nuclear interactions of the
therapeutic particles in the patient tissues. A detector with a
wide energy range from 100 keV to 15 MeV and excellent time
resolution is required to achieve millimetric precision in proton
range. During patient treatment, the detector count rates are
usually above 106 s-1 and the fraction of pile-up events is
very high for commonly used fast inorganic scintillators. We are
investigating a full acceptance approach with increased granularity
in order to reduce the size of the scintillators and consequently
the count rate per channel. Stacking the scintillators in matrices
requires suitable multi-channel photo-multipliers and a fitting
acquisition system. Here, we present two geometries of CeBr3
crystals 5×5×20 mm3 and
10×10×30 mm3, together with modern silicon
photo-multipliers (SiPM) adapted to work with the PETsys TOFPET2
ASIC. The TOFPET2 ASIC was developed for Time-of-Flight Positron
Emission Tomography (TOF-PET) applications. Here we show its
potential for higher gamma-ray energies and future hybrid imaging.
First results of energy resolution of 6.1%–7.8% are achieved
at 3.42 MeV using a 241Am9Be source. The time resolution
was found to be below 100 ps and studies of the count rates and the
dead time of the full system were performed. Different SiPM models
are analysed for their impact on the coincidence time resolution.
Growth of Ni loaded CdS in nanorods structure for photocatalytic and dye degradation applications under solar irradiation
Authors: Kumar Vikash , Raj Benjamin , Kommu Parmeshwar , Paswan Sanjeet Kumar , Singh Gajendra Prasad 
Published: February 2024

Abstract
Due to the exponential increase in global energy consumption and the degradation of environmental conditions caused by fossil fuels, it is critical to improve inexhaustible and sustainable resources. Generally, solar energy is one of the clean and environmentally agreeable energy sources. By harvesting solar energy for photocatalysis and considering it as a promising solution for various energy generation applications such as hydrogen production. Herein we are using Cadmium Sulphide and Nickel-doped Cadmium Sulphide in 0.5, 1 and 5 weight percent which act as photocatalyst for water splitting which will eventually produce an enormous amount of Hydrogen (H2). Cadmium sulphide was prepared through the chemical precipitation method and Ni-CdS by hydrothermal technique. The purity and phase formation were examined by the X-ray diffraction (XRD) and validated via Rietveld refinement by using Full Prof software. The surface morphology and the structure of as-synthesized material were evaluated by Field Emission Scanning Electron Microscopy (FESEM) and Transmission Electron Microscope (TEM) spectroscopic techniques. Following the results, the Ni-CdS nanocomposite having 1.0 wt% of Ni exhibits the highest H2 evolution rate of 9 mmolg−1 in 5 h with strong photo-stability, which is about 50 times higher than that of CdS. The material was tested to degrade organic dye for its photocatalytic operations. The newly prepared composite materials (CdS-Ni-NiO) were used for the photocatalytic degradation of the methylene blue (MB) dye. Ni(1.0 wt%)-CdS shows an optimal degradation percentage of 95.436 in the presence of artificial solar light in 90 min. Crystal growth mechanism shows the spherical structure of CdS agglomerate to form nanorods structure when doped with Ni metal which is also verified by the TEM images of CdS and Ni-doped CdS. The XPS peaks observed at 854.88 eV and 861.07 eV for Ni2+ with an energy separation of 6.18 eV confirmed the existence of NiO with Ni/CdS. The Raman bands of pure CdS and Ni (1.0 wt%)-CdS nanorods were observed at 300 cm-1 and 293 cm−1 for 1LO phonon and 601 cm−1 and 586 cm−1 for 2LO phonon corresponds. The Ni tuned the CdS band gap from 2.36 to 2.20 eV. The results pave the way for designing multi-component CdS-Ni nano-composites for highly efficient H2 evolution and other environmental applications.
First-principles screening of metal–organic frameworks for entangled photon pair generation
Authors: Raj Sanoj , Paiva Simón , Fritz Rubén A , Herrera Felipe , Colón Yamil J 
Published: February 2024

Abstract
The transmission of strong laser light in nonlinear optical materials can generate output photons sources that carry quantum entanglement in multiple degrees of freedom, making this process a fundamentally important tool in optical quantum technology. However, the availability of efficient optical crystals for entangled light generation is severely limited in terms of diversity, thus reducing the prospects for the implementation of next-generation protocols in quantum sensing, communication and computing. To overcome this, we developed and implemented a multi-scale first-principles modeling technique for the computational discovery of novel nonlinear optical devices based on metal–organic framework (MOF) materials that can efficiently generate entangled light via spontaneous parametric down-conversion (SPDC). Using collinear degenerate type-I SPDC as a case study, we computationally screen a database of 114 373 synthesized MOF materials to establish correlations between the structure and chemical composition of MOFs with the brightness and coherence properties of entangled photon pairs. We identify a subset of 49 non-centrosymmetric mono-ligand MOF crystals with high chemical and optical stability that produce entangled photon pairs with intrinsic

G

(
2
)

correlation times

τ
c

∼
10
−
30

fs and pair generation rates in the range

10
4

−

10

10

s

−
1

m
W

−
1

m
m

−
1

at 1064 nm. Conditions for optimal type-I phase matching are given for each MOF and relationships between pair brightness, crystal band gap and optical birefringence are discussed. Correlations between the optical properties of crystals and their constituent molecular ligands are also given. Our work paves the way for the computational design of MOF-based devices for optical quantum technology.
Defining and Studying Restraint
Authors: Edelman R David 
Published: February 2024

AbstractChapter 2 explains why restraint is the focus of such a study, and how it will go about considering restraint’s role in state decision-making and ultimately international politics. As broad as the concept is, it is certainly not the only force shaping contemporary international relations; nor are cyberattacks the only tool borne of computing that merit restraint. But, as the subsequent chapters will continue to argue, it is the most important force we may have to bring about the most important change to the status quo. It argues why it is important to focus on restraint; defines what is meant here by the concept and its manifestations, explains how abstract notions of restraint shape actual state decision-making, and provides some insights into its operation. The chapter concludes by connecting this discussion to the oft-cited discourse on cyber norms, and addressing several important critiques, before previewing the rest of the book’s arguments in-depth.
Conclusion
Authors: Edelman R David 
Published: February 2024

AbstractThe conclusion draws together the analysis of the prior chapters, engaging with their intersection and providing several opportunities for the continuation of this line of research and other, adjacent considerations. While recognizing the fraught present-day environment for bilateral and plurilateral negotiations on arms control matters, it considers whether this new resituation of the norms debate might serve as a point for mutual alignment of interest among key state. Among several others, it examines the emerging role that artificial intelligence (AI) might have on both the conclusions of the prior chapters and the international cybersecurity dynamic going forward. It also ponders the potential for deeper alignment between emerging interpretations of fundamental rights, accessibility of information infrastructure, and exceptional criminality in wartime. It concludes that in light of the alternative—an international system that regularizes large-scale cyberattacks and the collateral consequences that company them—there may be compelling reasons for states to try to beat the long odds and try to effectively and specifically cultivate a cyberattack taboo. That, however, will be for policymakers to decide.
The Annual Rhythms in Sleep, Sedentary Behavior, and Physical Activity of Australian Adults: A Prospective Cohort Study
Authors: Ferguson Ty , Curtis Rachel , Fraysse François , Olds Timothy , Dumuid Dorothea , Brown Wendy , Esterman Adrian , Maher Carol 
Published: February 2024

AbstractBackgroundSleep, sedentary behavior, and physical activity have fundamental impacts on health and well-being. Little is known about how these behaviors vary across the year.PurposeTo investigate how movement-related behaviors change across days of the week and seasons, and describe movement patterns across a full year and around specific temporal events.MethodsThis cohort study included 368 adults (mean age = 40.2 years [SD = 5.9]) who wore Fitbit activity trackers for 12 months to collect minute-by-minute data on sleep, sedentary behavior, light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA). Data were analyzed descriptively, as well as through multilevel mixed-effects linear regression to explore associations with specific temporal cycles (day-of-the-week, season) and events.ResultsMovement patterns varied significantly by day-of-the-week and season, as well as during annual events like Christmas-New Year and daylight saving time (DST) transitions. For example, sleep was longer on weekends (+32 min/day), during autumn and winter relative to summer (+4 and +11 min/day), and over Christmas-New Year (+24 min/day). Sedentary behavior was longer on weekdays, during winter, after Christmas-New Year, and after DST ended (+45, +7, +12, and +8 min/day, respectively). LPA was shorter in autumn, winter, and during and after Christmas-New Year (−6, −15, −17, and −31 min/day, respectively). Finally, there was less MVPA on weekdays and during winter (−5 min/day and −2 min/day, respectively).ConclusionsAcross the year, there were notable variations in movement behaviors. Identifying high-risk periods for unfavorable behavior changes may inform time-targeted interventions and health messaging.
Pharmacist perspectives on emerging T cell–engaging bispecific therapies in cancer therapeutics
Authors: Moore Donald C , Digiantonio Naomi , Oxencis Carolyn J , Taucher Kate D 
Published: February 2024

Abstract

Purpose
To summarize the pharmacology, efficacy, safety, dosing, administration, and pharmacist perspectives related to operationalization of new and emerging bispecific therapies indicated for the treatment of various cancers.

Summary
In recent years, there have been significant advancements in the expansion of immunotherapeutics in the treatment of various malignancies. Bispecific T cell–engaging therapies represent an emerging therapeutic drug class for the treatment of cancer. These therapies are unique antibody constructs that bind simultaneously to 2 targets, a tumor-specific antigen and CD3 on T cells, to elicit an immune response. Recently, several bispecific therapies have been approved, including epcoritamab, glofitamab, mosunetuzumab, tebentafusp, and teclistamab. Epcoritamab and glofitamab have been approved for diffuse large B cell lymphoma, while mosunetuzumab, tebentafusp, and teclistamab have been approved for follicular lymphoma, uveal melanoma, and multiple myeloma, respectively. As a result of their mechanism of action, the approved bispecific therapies have the potential to cause cytokine release syndrome, and, along with this, they all have unique and specific monitoring parameters and operational considerations that require clinician awareness when administering these therapies. Such operational challenges include within-patient dose escalations at therapy initiation, hospitalization for monitoring, and various pharmacological strategies for prophylaxis of cytokine release syndrome.

Conclusion
Bispecific therapies have continued to evolve the therapeutic landscape of cancer, primarily in hematological malignancies. Health-system pharmacists have the opportunity to play a key role in the operationalization and management of this new and emerging drug class.
Drug poisoning deaths by occupation and drug type, Massachusetts 2010–2019
Authors: Kaki Sahith , Hawkins Devan 
Published: February 2024

Abstract

Objective
To investigate variation in drug poisoning mortality rates by drug type and occupation in Massachusetts.

Methods
Death certificates for deaths by drug poisonings occurring between 2010 and 2019 in Massachusetts were coded based on the decedent’s occupation. Mortality rates and rate ratios (with all other occupations as the reference group) were calculated based on the occupation of the workers according to drug type. Poisson regression was used to determine significantly elevated mortality rates and trends in drug poisoning deaths by occupation and drug type.

Results
The rate of drug poisoning deaths increased from 2010 to 2016 after which they plateaued. With respect to specific substances, fentanyl- and cocaine-related deaths increased throughout the surveillance period. For drug poisoning deaths overall, workers in construction trades (3,017); food preparation and serving (1,116); transportation and material moving (1,062) occupations had the highest number of drug poisoning deaths. When adjusting for age, sex, race/ethnicity, and educational attainment, workers in 7 occupations had significantly elevated mortality rate ratios for drug poisonings overall: farming, fishing, and forestry (3.42, P &lt; 0.001); construction trades (2.58, P &lt; 0.001); health care support (1.61, P &lt; 0.001); community and social service (1.60, P &lt; 0.001); food preparation and serving related (1.54, P &lt; 0.001); personal care and service (1.37, P &lt; 0.001); and arts, design, entertainment, sports, and media (1.21, P = 0.010). In many cases, workers in these same occupations had elevated mortality rate ratios for poisonings from specific substances. Health care practitioners and technical occupation workers only had elevated rates for methadone-related poisonings (1.73, P = 0.010).

Conclusions
These findings highlight that workers in certain occupations have an elevated risk for drug poisonings and that the patterns differ with respect to the drug type. These findings can be useful for providing services to workers in high-risk occupations and in identifying occupational factors that may be related to the risk of drug poisoning death. While previous research has begun to uncover work-related factors that may contribute to opioid use, further work is needed to identify occupational factors that may contribute to psychostimulant and benzodiazepine use.
Continually adapting pre-trained language model to universal annotation of single-cell RNA-seq data
Authors: Wan Hui , Yuan Musu , Fu Yiwei , Deng Minghua 
Published: February 2024

Abstract

Motivation
Cell-type annotation of single-cell RNA-sequencing (scRNA-seq) data is a hallmark of biomedical research and clinical application. Current annotation tools usually assume the simultaneous acquisition of well-annotated data, but without the ability to expand knowledge from new data. Yet, such tools are inconsistent with the continuous emergence of scRNA-seq data, calling for a continuous cell-type annotation model. In addition, by their powerful ability of information integration and model interpretability, transformer-based pre-trained language models have led to breakthroughs in single-cell biology research. Therefore, the systematic combining of continual learning and pre-trained language models for cell-type annotation tasks is inevitable.

Results
We herein propose a universal cell-type annotation tool, called CANAL, that continuously fine-tunes a pre-trained language model trained on a large amount of unlabeled scRNA-seq data, as new well-labeled data emerges. CANAL essentially alleviates the dilemma of catastrophic forgetting, both in terms of model inputs and outputs. For model inputs, we introduce an experience replay schema that repeatedly reviews previous vital examples in current training stages. This is achieved through a dynamic example bank with a fixed buffer size. The example bank is class-balanced and proficient in retaining cell-type-specific information, particularly facilitating the consolidation of patterns associated with rare cell types. For model outputs, we utilize representation knowledge distillation to regularize the divergence between previous and current models, resulting in the preservation of knowledge learned from past training stages. Moreover, our universal annotation framework considers the inclusion of new cell types throughout the fine-tuning and testing stages. We can continuously expand the cell-type annotation library by absorbing new cell types from newly arrived, well-annotated training datasets, as well as automatically identify novel cells in unlabeled datasets. Comprehensive experiments with data streams under various biological scenarios demonstrate the versatility and high model interpretability of CANAL.

Availability
An implementation of CANAL is available from https://github.com/aster-ww/CANAL-torch.

Contact
dengmh@pku.edu.cn

Supplementary information
Supplementary data are available at Journal Name online.
A comprehensive computational benchmark for evaluating deep learning-based protein function prediction approaches
Authors: Wang Wenkang , Shuai Yunyan , Yang Qiurong , Zhang Fuhao , Zeng Min , Li Min 
Published: February 2024

Abstract
Proteins play an important role in life activities and are the basic units for performing functions. Accurately annotating functions to proteins is crucial for understanding the intricate mechanisms of life and developing effective treatments for complex diseases. Traditional biological experiments struggle to keep pace with the growing number of known proteins. With the development of high-throughput sequencing technology, a wide variety of biological data provides the possibility to accurately predict protein functions by computational methods. Consequently, many computational methods have been proposed. Due to the diversity of application scenarios, it is necessary to conduct a comprehensive evaluation of these computational methods to determine the suitability of each algorithm for specific cases. In this study, we present a comprehensive benchmark, BeProf, to process data and evaluate representative computational methods. We first collect the latest datasets and analyze the data characteristics. Then, we investigate and summarize 17 state-of-the-art computational methods. Finally, we propose a novel comprehensive evaluation metric, design eight application scenarios and evaluate the performance of existing methods on these scenarios. Based on the evaluation, we provide practical recommendations for different scenarios, enabling users to select the most suitable method for their specific needs. All of these servers can be obtained from https://csuligroup.com/BEPROF and https://github.com/CSUBioGroup/BEPROF.
HOTAIR/miR-1277-5p/FBN2 signaling axis is involved in recurrent spontaneous abortion by regulating the growth, migration, and invasion of HTR-8/SVneo cells
Authors: Long Na , Sun Ru-liang , Lai Qing-hua , Lu Mei-yin , Li Xiao-hong , Chen Yan-na , Zhu Dong-yan 
Published: February 2024

Abstract

Objective
This study aimed to explore the specific pathways by which HOX transcript antisense intergenic RNA contributes to the pathogenesis of unexplained recurrent spontaneous abortion.

Methods
Real-time quantitative PCR was employed to assess the differential expression levels of HOX transcript antisense intergenic RNA in chorionic villi tissues from unexplained recurrent spontaneous abortion patients and women with voluntarily terminated pregnancies. HTR-8/SVneo served as a cellular model. Knockdown and overexpression of HOX transcript antisense intergenic RNA in the cells were achieved through siRNA transfection and pcDNA3.1 transfection, respectively. Cell viability, migration, and invasion were evaluated using cell counting kit-8, scratch, and Transwell assays, respectively. The interaction among the HOX transcript antisense intergenic RNA /miR-1277-5p/fibrillin 2 axis was predicted through bioinformatics analysis and confirmed through in vitro experiments. Furthermore, the regulatory effects of the HOX transcript antisense intergenic RNA /miR-1277-5p/fibrillin 2 signaling axis on cellular behaviors were validated in HTR-8/SVneo cells.

Results
We found that HOX transcript antisense intergenic RNA was downregulated in chorionic villi tissues from unexplained recurrent spontaneous abortion patients. Overexpression of HOX transcript antisense intergenic RNA significantly enhanced the viability, migration, and invasion of HTR-8/SVneo cells, while knockdown of HOX transcript antisense intergenic RNA had the opposite effects. We further confirmed the regulatory effect of the HOX transcript antisense intergenic RNA /miR-1277-5p/fibrillin 2 signaling axis in unexplained recurrent spontaneous abortion. Specifically, HOX transcript antisense intergenic RNA and fibrillin 2 were found to reduce the risk of unexplained recurrent spontaneous abortion by enhancing cell viability, migration, and invasion, whereas miR-1277-5p exerted the opposite effects.

Conclusion
HOX transcript antisense intergenic RNA promotes unexplained recurrent spontaneous abortion development by targeting inhibition of miR-1277-5p/fibrillin 2 axis.
A rank-based approach to evaluate a surrogate marker in a small sample setting
Authors: Parast Layla , Cai Tianxi , Tian Lu 
Published: February 2024

ABSTRACT
In clinical studies of chronic diseases, the effectiveness of an intervention is often assessed using “high cost” outcomes that require long-term patient follow-up and/or are invasive to obtain. While much progress has been made in the development of statistical methods to identify surrogate markers, that is, measurements that could replace such costly outcomes, they are generally not applicable to studies with a small sample size. These methods either rely on nonparametric smoothing which requires a relatively large sample size or rely on strict model assumptions that are unlikely to hold in practice and empirically difficult to verify with a small sample size. In this paper, we develop a novel rank-based nonparametric approach to evaluate a surrogate marker in a small sample size setting. The method developed in this paper is motivated by a small study of children with nonalcoholic fatty liver disease (NAFLD), a diagnosis for a range of liver conditions in individuals without significant history of alcohol intake. Specifically, we examine whether change in alanine aminotransferase (ALT; measured in blood) is a surrogate marker for change in NAFLD activity score (obtained by biopsy) in a trial, which compared Vitamin E ($n=50$) versus placebo ($n=46$) among children with NAFLD.