bluuebunny/crossref_metadata_2025 huggingface dataset:
Signal shapes in multiwire proportional chamber-based TPCs
Authors: Alme J. , Alt T. , Appelshäuser H. , Arslandok M. , Averbeck R. , Bartsch E. , Becht P. , Bratrud L. , Braun-Munzinger P. , Buesching H. , Caines H. , Christiansen P. , Costa F. , Frankenfeld U. , Gaardhøje J.J. , Garabatos C. , Glässel P. , Gunji T. , Hamagaki H. , Harris J.W. , Hellbär E. , Helstrup H. , Ivanov M. , Jung J. , Jung M. , Junique A. , Kalweit A. , Keidel R. , Kirsch S. , Kleiner M. , Kowalski M. , Krüger M. , Lippmann C. , Mager M. , Masciocchi S. , Matyja A. , Miśkowiec D. , Munzer R.H. , Musa L. , Nielsen B.S. , Otwinowski J. , Pikna M. , Rehman A. , Renfordt R. , Röhrich D. , Scheid H.S. , Schmidt C. , Schmidt H.R. , Schweda K. , Sekiguchi Y. , Silvermyr D. , Sitar B. , Stachel J. , Ullaland K. , Veenhof R. , Vislavicius V. , Wiechula J. , Windelband B. ,   The ALICE TPC collaboration
Published: February 2024

A large-volume Time Projection Chamber (TPC) is the main
tracking and particle identification (PID) detector of the ALICE
experiment at the CERN LHC. PID in the TPC is performed via
specific energy-loss measurements (dE/dx), which are derived
from the average pulse-height distribution of ionization generated
by charged-particle tracks traversing the TPC volume. During Runs 1
and 2, until 2018, the gas amplification stage was based on
multiwire proportional chambers (MWPC). Signals from the MWPC show
characteristic long negative tails after an initial positive peak
due to the long ion drift times in the MWPC amplification
region. This so-called ion tail can lead to a significant amplitude
loss in subsequently measured signals, especially in the
high-multiplicity environment of high-energy Pb-Pb collisions, which
results in a degradation of the dE/dx resolution. A detailed
study of the signal shapes measured with the ALICE TPC with the
Ne-CO2 (90-10) and Ar-CO2 (90-10) gas mixtures is presented,
and the results are compared with three-dimensional Garfield
simulations. The impact of the ion tail on the PID performance is
studied employing the ALICE simulation framework and the feasibility
of an offline correction procedure to account for the ion tail is
demonstrated.
Unveiling the benefits and gaps of wild pollinators on nutrition and income
Authors: Duarte Gabriela T , Schuster Richard , Mitchell Matthew G E
Published: February 2024

Pollinators play a crucial role in global crop production, enhancing crop yields, nutritional value and fruit quality. However, their wild populations worldwide have been experiencing alarming declines. We investigated the contribution of wild pollinators to nutrition and farmer income in Canada, while examining the spatial distribution of pollination services. We used publicly available data on crop types, yields, nutrient content, and farm gate values, alongside information on natural habitats. Our findings suggest that wild pollinators in Canada help sustain the equivalent of approximately 24.4 million people each year in terms of nutrition and generate an annual income of nearly CAD$2.8 billion for farmers. To provide context, these estimates exceed half of the Canadian population and correspond to 5% of total national crop-related farm income. However, significant benefit gaps exist due to the lack of nearby pollinator habitat and insufficient pollination of dependent crops at a national scale. Addressing these gaps could potentially provide an additional nutrition supply for nearly 30 million equivalent people and increase farmer income by CAD$3 billion. We discuss how and where efforts focused on preserving and enhancing wild pollinator habitats, promoting sustainable farming practices, and raising awareness among stakeholders are crucial for the long-term viability of wild pollinator populations and the sustainability of agricultural systems in Canada. Our research underscores the urgent need for a national strategy aimed at safeguarding wild pollinators. Implementing such a strategy would not only contribute to strengthening local economies but also ensure the production of nutritionally essential food.
Challenges in accelerating net-zero transitions: insights from transport electrification in Germany and California
Authors: Rogge Karoline S , Goedeking Nicholas
Published: February 2024

Addressing the climate crisis necessitates accelerating transitions towards climate-neutral systems of production and consumption, with electrification emerging as a crucial decarbonisation strategy. The acceleration of such net-zero transitions across multiple systems faces significant resistance and contestation. In this paper, we propose an extended list of challenges unique to the acceleration phase of socio-technical transitions: we introduce ‘expansion and contestation’, ‘justice’, and ‘international dynamics’ as additional challenge types to complement the already acknowledged challenge types of ‘whole systems change’, ‘interaction between multiple systems’, ‘decline and resistance’, ‘consumers and social practices’, and ‘governance’. We apply this extended analytical framework to the electrification of private-passenger vehicles and investigate the unfolding transition to e-mobility with evidence from 35 expert interviews in Germany and California. We uncover over 50 real-world challenges associated with these net-zero transitions at the beginning of the acceleration phase. Most challenges fall within the categories of ‘expansion and contestation’ and ‘governance’. While Germany and California share many real-world challenges, we also find significant variation between both jurisdictions, which we attribute to differences in their automotive incumbency, transition governance approaches, and institutional contexts. We discuss implications for future research, arguing for greater attention to the dual politics of acceleration during net-zero transitions: political conflict not only centres around the decline of old industries and future losses, but also around the expansion of the new system and associated future gains.
Solvable non-Hermitian skin effects and real-space exceptional points: non-Hermitian generalized Bloch theorem
Authors: Zhang Xintong , Song Xiaoxiao , Zhang Shubo , Zhang Tengfei , Liao Yuanjie , Cai Xinyi , Li Jing
Published: February 2024

Non-Hermitian systems can exhibit extraordinary boundary behaviors, known as the non-Hermitian skin effects, where all the eigenstates are localized exponentially at one side of lattice model. To give a full understanding and control of non-Hermitian skin effects, we have developed the non-Hermitian generalized Bloch theorem to provide the analytical expression for all solvable eigenvalues and eigenstates, in which translation symmetry is broken due to the open boundary condition. By introducing the Vieta’s theorem for any polynomial equation with arbitrary degree, our approach is widely applicable for one-dimensional non-Hermitian tight-binding models. With the non-Hermitian generalized Bloch theorem, we can analyze the condition of existence or non-existence of the non-Hermitian skin effects at a mathematically rigorous level. Additionally, the non-Hermitian generalized Bloch theorem allows us to explore the real-space exceptional points. We also establish the connection between our approach and the generalized Brillouin zone method. To illustrate our main results, we examine two concrete examples including the Su–Schrieffer–Heeger chain model with long-range couplings, and the ladder model with non-reciprocal interaction. Our non-Hermitian generalized Bloch theorem provides an efficient way to analytically study various non-Hermitian phenomena in more general cases.
Applicability of normalized resistance rate model for predicting fatigue life and resistance evolution in composite conductive inks
Authors: Li Qiushi , Pierron Olivier , Antoniou Antonia
Published: February 2024

The electrical resistance of metal-polymer conductive inks increases as they undergo cyclic loading, posing a major challenge to their reliability as interconnect materials for flexible electronic devices. To characterize an ink’s fatigue performance, extensive electro-mechanical testing is usually performed. Phenomenological models that can accurately predict the resistance increase with cyclic loading can save time and be useful in flexible conductor design against fatigue failure. One such model was recently developed for only one composite ink type. The model is based on experiments monitoring resistance under monotonic stretch data and multiple experiments measuring the rate of increase of the resistance under different strain amplitudes and mean strains. The current work examines whether such resistance rate model could be generalized to apply for more types of composite inks. Two composite inks with different binder material, metal flake sizes and shapes, and substrate material were experimentally tested under monotonic and cyclic loading. It was found that the two new inks are also more sensitive to strain amplitude than mean strain. The resistance rate model accurately predicts early/catastrophic failure (<1000 cycles) in all inks and conservatively estimates high fatigue life for low strain amplitudes. A protocol detailing the procedures for applying the resistance model to new inks is outlined.
Trends and advances in silk based 3D printing/bioprinting towards cartilage tissue engineering and regeneration
Authors: Singh Yogendra Pratap , Bandyopadhyay Ashutosh , Dey Souradeep , Bhardwaj Nandana , Mandal Biman B
Published: February 2024

Cartilage repair remains a significant clinical challenge in orthopedics due to its limited self- regeneration potential and often progresses to osteoarthritis which reduces the quality of life. 3D printing/bioprinting has received vast attention in biofabrication of functional tissue substitutes due to its ability to develop complex structures such as zonally structured cartilage and osteochondral tissue as per patient specifications with precise biomimetic control. Towards a suitable bioink development for 3D printing/bioprinting, silk fibroin has garnered much attention due to its advantageous characteristics such as shear thinning behavior, cytocompatibility, good printability, structural fidelity, affordability, and ease of availability and processing. This review attempts to provide an overview of current trends/strategies and recent advancements in utilizing silk-based bioinks/biomaterial-inks for cartilage bioprinting. Herein, the development of silk-based bioinks/biomaterial-inks, its components and the associated challenges, along with different bioprinting techniques have been elaborated and reviewed. Furthermore, the applications of silk-based bioinks/biomaterial-inks in cartilage repair followed by challenges and future directions are discussed towards its clinical translations and production of next-generation biological implants.
Research and development of a new combination of piezo-thermoelectric energy harvester systems from roadways
Authors: Randriantsoa Ando Ny Aina , Fakra Damien Ali Hamada , Rakotondrajaona Luc , Benelmir Riad
Published: February 2024

Due to the problems associated with fossil fuels, scientists and governments are investigating alternative energy sources. In recent decades, there has been an increase in interest in initiatives involving the collection of clean, limitless energy. This paper focuses on two renewable energy harvesting combination technologies: mechanical vibration utilizing piezoelectric technology and thermal sources utilizing thermoelectric technology. Existing scientific literature proposes various techniques for producing and modeling each system individually. This study proposes a novel piezo-thermoelectric pavement model with piezo-thermoelectric coupling. Due to the lack of typical experimentation in the scientific literature, a new laboratory experimental prototype proposes to reproduce artificially and simultaneously heat harvesting on the artificial road surface and mechanical vibration caused by passing vehicles. Testing the laboratory-developed prototype has determined the efficacy of the piezo-thermoelectric coupling electronic model. This study demonstrated that a hybrid piezo-thermoelectric system is more suitable for road pavement applications than a piezo-thermoelectric coupling system. A hybrid combination system can continue to produce energy even if one of the energy sources is unavailable or malfunctioning, whereas a coupling combination system cannot. In laboratory testing, the combined piezo-thermoelectric harvester proposed could generate up to 1.75 μW without optimizing the materials or power generation. This innovative study demonstrates the feasibility and applicability of combining thermoelectric and piezoelectric technology to harvest energy from road surfaces.
Powering of IOTs through single jersey wearable tribo-electric nano generator
Authors: Amir Muhammad , Butt Rizwan Aslam , Naqvi Shenela , Hasany Syed Farhan
Published: February 2024

A simple, lightweight, and easy to develop Single Jersey Wearable Tribo-Electric Nano Generators (SJ-WTENG) were constructed using Cotton and Acrylic fabrics (Triboelectric series materials). Fabrics were also coated with Maghemite (γ-Fe2O3) nanoparticles (13 nm) to increase the electrical conductance of the samples. Compression and Vertical contact-separation modes were adopted for studying the performance of the developed samples. Along with a Single WTENG sample, the outputs of two samples connected in series were also measured. To study the effect of developed Maghemite (γ-Fe2O3) nanoparticle coating, non-coated fabrics WTENGs were also constructed and tested. The maximum voltage reached with the Maghemite (γ-Fe2O3) nanoparticle-coated SJ-WTENG samples was a time-varying signal of 7.68 volts peak to peak volts with an approximate frequency of 50.5 Hertz. A shotky diode-based full bridge rectifier was used to get the DC voltage. The rectified DC signal was observed to be 5 volts which was enough to light up an LED with a threshold voltage of 1.7 volts DC as well as charge 3.7 volts, 3.6Ah Li-ion battery pack. Results confirmed that the application of Maghemite (γ-Fe2O3) nanoparticles was useful in augmenting the output of the proposed SJ-WTENG design. The proposed system can be used to power the battery powered IOT (Internet of Things) devices, widely used in medical and body sensor network applications.
VCSEL-based photonic spiking neural networks for ultrafast detection and tracking
Authors: Robertson Joshua , Kirkland Paul , Di Caterina Gaetano , Hurtado Antonio
Published: February 2024

Inspired by efficient biological spike-based neural networks, we demonstrate for the first time the detection and tracking of target patterns in image and video inputs at high-speed rates with networks of multiple artificial spiking optical neurons. Using photonic systems of in-parallel spiking vertical cavity surface emitting lasers (VCSELs), we demonstrate the implementation of multiple convolutional kernel operators which, in combination with optical spike signalling, enable the detection and tracking of target features in images/video feeds at an ultrafast photonic operation speed of 1 ns per pixel. Alongside a single layer optical spiking neural network (SNN) demonstration, a multi-layer network of photonic (GHz-rate) spike-firing neurons is reported where the photonic system successfully tracks a large complex feature (Handwritten Digit 3). The consecutive photonic layers perform spike-enabled image reduction and convolution operations, and interact with a software-implemented SNN, that learns the feature patterns that best identify the target to provide a high detection efficiency even in the presence of a distractor feature. This work therefore highlights the effectiveness of combining neuromorphic photonic hardware and software SNNs, for efficient learning and ultrafast operation, thanks to the use of spiking light signals, towards tackling complex AI and computer vision problems.
Tailored risk assessment and forecasting in intermittent claudication
Authors: Ravindhran Bharadhwaj , Prosser Jonathon , Lim Arthur , Mishra Bhupesh , Lathan Ross , Hitchman Louise H , Smith George E , Carradice Daniel , Chetter Ian C , Thakker Dhaval , Pymer Sean
Published: February 2024

Background

Guidelines recommend cardiovascular risk reduction and supervised exercise therapy as the first line of treatment in intermittent claudication, but implementation challenges and poor patient compliance lead to significant variation in management and therefore outcomes. The development of a precise risk stratification tool is proposed through a machine-learning algorithm that aims to provide personalized outcome predictions for different management strategies.

Methods

Feature selection was performed using the least absolute shrinkage and selection operator method. The model was developed using a bootstrapped sample based on patients with intermittent claudication from a vascular centre to predict chronic limb-threatening ischaemia, two or more revascularization procedures, major adverse cardiovascular events, and major adverse limb events. Algorithm performance was evaluated using the area under the receiver operating characteristic curve. Calibration curves were generated to assess the consistency between predicted and actual outcomes. Decision curve analysis was employed to evaluate the clinical utility. Validation was performed using a similar dataset.

Results

The bootstrapped sample of 10 000 patients was based on 255 patients. The model was validated using a similar sample of 254 patients. The area under the receiver operating characteristic curves for risk of progression to chronic limb-threatening ischaemia at 2 years (0.892), risk of progression to chronic limb-threatening ischaemia at 5 years (0.866), likelihood of major adverse cardiovascular events within 5 years (0.836), likelihood of major adverse limb events within 5 years (0.891), and likelihood of two or more revascularization procedures within 5 years (0.896) demonstrated excellent discrimination. Calibration curves demonstrated good consistency between predicted and actual outcomes and decision curve analysis confirmed clinical utility. Logistic regression yielded slightly lower area under the receiver operating characteristic curves for these outcomes compared with the least absolute shrinkage and selection operator algorithm (0.728, 0.717, 0.746, 0.756, and 0.733 respectively). External calibration curve and decision curve analysis confirmed the reliability and clinical utility of the model, surpassing traditional logistic regression.

Conclusion

The machine-learning algorithm successfully predicts outcomes for patients with intermittent claudication across various initial treatment strategies, offering potential for improved risk stratification and patient outcomes.
What are We Talking about When We are Talking about ‘Decolonising’ Social Work?
Authors: Garrett Paul Michael
Published: February 2024

The core concern is the ‘decolonial turn’ which is said to be taking place in a number of universities and other institutions. In this context, attempts are being made to unmask the colonial ideologies and common sense rooted in various disciplines including social work. The article examines key terms such as ‘Decolonisation’, ‘Eurocentrism’, ‘Coloniality’ and ‘Decoloniality’. In conclusion, some of the obstacles that may be encountered by those aiming to decolonise social work are discussed and possible ways forward are identified.
VentRa: distinguishing frontotemporal dementia from psychiatric disorders
Authors: Manera Ana L , Dadar Mahsa , Ducharme Simon , Collins D Louis
Published: February 2024

The volume of the lateral ventricles is a reliable and sensitive indicator of brain atrophy and disease progression in behavioural variant frontotemporal dementia. In this study, we validate our previously developed automated tool using ventricular features (known as VentRa) for the classification of behavioural variant frontotemporal dementia versus a mixed cohort of neurodegenerative, vascular and psychiatric disorders from a clinically representative independent dataset. Lateral ventricles were segmented for 1110 subjects—14 behavioural variant frontotemporal dementia, 30 other frontotemporal dementia, 70 Lewy body disease, 898 Alzheimer’s disease, 62 vascular brain injury and 36 primary psychiatric disorder from the publicly accessible National Alzheimer’s Coordinating Center dataset to assess the performance of VentRa. Using ventricular features to discriminate behavioural variant frontotemporal dementia subjects from primary psychiatric disorders, VentRa achieved an accuracy rate of 84%, a sensitivity rate of 71% and a specificity rate of 89%. VentRa was able to identify behavioural variant frontotemporal dementia from a mixed age–matched cohort (i.e. other frontotemporal dementia, Lewy body disease, Alzheimer’s disease, vascular brain injury and primary psychiatric disorders) and to correctly classify other disorders as ‘not compatible with behavioral variant frontotemporal dementia’ with a specificity rate of 83%. The specificity rates against each of the other individual cohorts were 80% for other frontotemporal dementia, 83% for Lewy body disease, 83% for Alzheimer’s disease, 84% for vascular brain injury and 89% for primary psychiatric disorders. VentRa is a robust and generalizable tool with potential usefulness for improving the diagnostic certainty of behavioural variant frontotemporal dementia, particularly for the differential diagnosis with primary psychiatric disorders.
Instruments for racial health equity: a scoping review of structural racism measurement, 2019–2021
Authors: Hing Anna K , Chantarat Tongtan , Fashaw-Walters Shekinah , Hunt Shanda L , Hardeman Rachel R
Published: February 2024

Progress toward racial health equity cannot be made if we cannot measure its fundamental driver: structural racism. As in other epidemiologic studies, the first step is to measure the exposure. But how to measure structural racism is an ongoing debate. To characterize the approaches epidemiologists and other health researchers use to quantitatively measure structural racism, highlight methodological innovations, and identify gaps in the literature, we conducted a scoping review of the peer-reviewed and gray literature published during 2019–2021 to accompany the 2018 published work of Groos et al., in which they surveyed the scope of structural racism measurement up to 2017. We identified several themes from the recent literature: the current predominant focus on measuring anti-Black racism; using residential segregation as well as other segregation-driven measures as proxies of structural racism; measuring structural racism as spatial exposures; increasing calls by epidemiologists and other health researchers to measure structural racism as a multidimensional, multilevel determinant of health and related innovations; the development of policy databases; the utility of simulated counterfactual approaches in the understanding of how structural racism drives racial health inequities; and the lack of measures of antiracism and limited work on later life effects. Our findings sketch out several steps to improve the science related to structural racism measurements, which is key to advancing antiracism policies.
Prevalence of diverse antimicrobial resistance genes and bacteria in sewage treatment plant-derived sludge environment
Authors: Patra Mrinmoy , Pandey Bhavana , Dubey Suresh Kumar
Published: February 2024

Antimicrobial resistance (AMR) contamination in the environment is one of the most significant worldwide threats of the 21st century. Since sludge is heavily exposed to diverse contaminants, including pharmaceuticals, the inhabitant bacterial population is expected to exhibit resistance to antimicrobial agents. In this study, sewage treatment plant (STP) sludge samples were analyzed to assess the antibiotic-resistant bacterial population, abundance of AMR genes (ermF, qnrS, Sul1, blaGES, blaCTX-M, and blaNDM), and mobile genetic elements (intl1 and IS26). Out of 16, six bacterial isolates exhibited resistance to 13 antibiotics with a high multiple antibiotic resistance index (MARI) (0.93) and high metal tolerance. Quantitative polymerase chain reaction showed the abundance of target genes ranging from 6.6 × 103 to 6.5 × 108 copies g−1 sludge. The overall outcome reveals that STP sludge comprised varied multidrug-resistant bacterial populations. It will give insights into the functions of heavy metals and biofilm development in the selection and spread of AMR genes and the associated bacteria. Therefore, the application of sludge needs proper screening for AMR and metal contamination prior to its countless applications. This study will contribute immensely to the risk analysis of STP effluents on environmental health, including control of AMR transmission.
In vitro modelling of bacterial pneumonia: a comparative analysis of widely applied complex cell culture models
Authors: Mahieu Laure , Van Moll Laurence , De Vooght Linda , Delputte Peter , Cos Paul
Published: February 2024

Bacterial pneumonia greatly contributes to the disease burden and mortality of lower respiratory tract infections among all age groups and risk profiles. Therefore, laboratory modelling of bacterial pneumonia remains important for elucidating the complex host–pathogen interactions and to determine drug efficacy and toxicity. In vitro cell culture enables for the creation of high-throughput, specific disease models in a tightly controlled environment. Advanced human cell culture models specifically, can bridge the research gap between the classical two-dimensional cell models and animal models. This review provides an overview of the current status of the development of complex cellular in vitro models to study bacterial pneumonia infections, with a focus on air–liquid interface models, spheroid, organoid, and lung-on-a-chip models. For the wide scale, comparative literature search, we selected six clinically highly relevant bacteria (Pseudomonas aeruginosa, Mycoplasma pneumoniae, Haemophilus influenzae, Mycobacterium tuberculosis, Streptococcus pneumoniae, and Staphylococcus aureus). We reviewed the cell lines that are commonly used, as well as trends and discrepancies in the methodology, ranging from cell infection parameters to assay read-outs. We also highlighted the importance of model validation and data transparency in guiding the research field towards more complex infection models.
Leveraging Country Expertise: How Scholars in International Studies Can Support the Asylum Process
Authors: Chapman Hannah S , Schwartz Rachel A
Published: February 2024

Bridging the divide between research and practice has become a growing concern within international studies. One under-explored avenue through which international studies scholars can enhance their “real world” impact is by serving as country conditions experts in asylum cases. This article provides an overview of the asylum process, the role of country conditions experts within it, and how scholars with in-depth country knowledge can leverage their expertise to make a difference, using examples from the United States and the United Kingdom. It also details several key issues one should consider when deciding whether to undertake expert witness work and the challenges and dilemmas it often entails. Finally, we provide actionable ways for international studies scholars to get involved and expand the community of individuals engaged in expert witnessing.
Clinical risk prediction using language models: benefits and considerations
Authors: Acharya Angeela , Shrestha Sulabh , Chen Anyi , Conte Joseph , Avramovic Sanja , Sikdar Siddhartha , Anastasopoulos Antonios , Das Sanmay
Published: February 2024

Objective

The use of electronic health records (EHRs) for clinical risk prediction is on the rise. However, in many practical settings, the limited availability of task-specific EHR data can restrict the application of standard machine learning pipelines. In this study, we investigate the potential of leveraging language models (LMs) as a means to incorporate supplementary domain knowledge for improving the performance of various EHR-based risk prediction tasks.

Methods

We propose two novel LM-based methods, namely “LLaMA2-EHR” and “Sent-e-Med.” Our focus is on utilizing the textual descriptions within structured EHRs to make risk predictions about future diagnoses. We conduct a comprehensive comparison with previous approaches across various data types and sizes.

Results

Experiments across 6 different methods and 3 separate risk prediction tasks reveal that employing LMs to represent structured EHRs, such as diagnostic histories, results in significant performance improvements when evaluated using standard metrics such as area under the receiver operating characteristic (ROC) curve and precision-recall (PR) curve. Additionally, they offer benefits such as few-shot learning, the ability to handle previously unseen medical concepts, and adaptability to various medical vocabularies. However, it is noteworthy that outcomes may exhibit sensitivity to a specific prompt.

Conclusion

LMs encompass extensive embedded knowledge, making them valuable for the analysis of EHRs in the context of risk prediction. Nevertheless, it is important to exercise caution in their application, as ongoing safety concerns related to LMs persist and require continuous consideration.
Effects of crude protease produced by Bacillus subtilis (MAFIC Y7) on growth performance, immune indices, and anti-inflammatory responses of broilers fed soybean meal- or cottonseed meal-based diets
Authors: Guo Xiangyue , Li Qianxi , Wang Lixue , Zhang Ying , Johnston Lee J , Levesque Crystal L , Cao Yunhe , Dong Bing
Published: February 2024

A strain of Bacillus subtilis (MAFIC Y7) was isolated from the intestine of Tibetan pigs and was able to express high protease activity. The aim of this study was to characterize the proteases produced by MAFIC Y7, and to investigate the effects of protease addition on growth performance, ileal amino acid digestibility, and serum immunoglobulin and immune factors of broilers fed SBM-based diets, or on growth performance, carcass characteristics, and intestinal morphology of broilers fed CSM-based diets. B. subtilis (MAFIC Y7) expressed protease showed its optimal enzyme activity at 50 °C and pH 7.0. The coated crude enzyme (CCE) showed greater stability at pH 3.0 than its uncoated counterpart. Experiment 1 was conducted with six diets based on three levels of crude protein (CP)—CPlow, CPmedium, and CPhigh—with or without CCE. In CPlow, CCE increased gain:feed (G:F) (days 1 to 21, days 1 to 42) by 8%, 3%, respectively, and enhanced apparent ileal digestibility (AID) of crude protein and lysine (on day 42) by 8.8%, 4.6%, respectively, compared with diets containing no CCE (P < 0.05). CCE increased G:F from days 1 to 21 from 0.63 to 0.68, improved G:F and average daily gain (ADG) during days 1 to 42, and enhanced AID of crude protein, lysine, cysteine, and isoleucine on day 42 compared with the unsupplemented treatments (in CPmedium, P < 0.05). CCE increased serum IgA (on day 21), serum IgA and IgG and increased serum IL-10 (on day 42), but decreased serum tumor necrosis factor-α (TNF-α; on day 21), and serum IL-8 and TNF-α (on day 42) compared with unsupplemented treatments. At CPhigh, CCE decreased serum levels of IL-6 and TNF-α (on day 21), and IL-8 and TNF-α (on day 42) compared with unsupplemented treatments (in CPhigh, P < 0.05). In experiment 2, CSM-based diets with two lysine-to-protein ratios (5.2% or 5.5%) with or without CCE. In the high Lys diet (5.5% Lys:protein), CCE increased ADG and G:F, increased carcass, but decreased abdominal fat compared with the unsupplemented treatment (P < 0.05). In the 5.2% Lys:protein dietary treatment, CCE improved duodenal villus height compared with the unsupplemented treatment (P < 0.05). Supplementation of protease produced by MAFIC Y7 was associated with lower inflammatory responses in SBM diets (CPmedium or CPhigh) and improved ADG in broilers fed CPmedium or CPhigh. The proteases improved ADG and the efficiency of CSM use when the ratio of Lys to protein was 5.5%.
‘Take the Money and Run’: if there is copyright there is art (in Denmark)?
Authors: Teilmann-Lock Stina , Kohli Vishv Priya
Published: February 2024

The case concerned copyright and breach of contract in a piece of performative art and the implications of aesthetic neutrality in copyright law for the evaluation of contemporary art.
Earliest records of the Asian longhorned tick (Acari: Ixodidae) in Staten Island, New York, and subsequent population establishment, with a review of its potential medical and veterinary importance in the United States
Authors: Bajwa Waheed , Kennedy Ashley , Vincent Zachary , Heck Garrett , Riaj Shamim , Shah Zahir , Tsynman Leonid , Casal Cory , Haynes Scott , Cornman Hannah , Egizi Andrea , Stromdahl Ellen , Nadolny Robyn
Published: February 2024

Three Asian longhorned ticks (Haemaphysalis longicornis) were collected on Staten Island, Richmond County, New York, in 2014–2015 as part of a tick-borne disease surveillance program conducted by the New York City Department of Health and Mental Hygiene and the Defense Centers of Public Health – Aberdeen Tick-Borne Disease Laboratory. These records mark the earliest known occurrence of H. longicornis in New York State outside of quarantine areas, predating previously reported detections by several years. Robust populations of H. longicornis were collected in subsequent years at the Staten Island site where these few ticks were found, demonstrating that small infestations have the potential to proliferate quickly. Haemaphysalis longicornis is a 3-host ixodid tick native to eastern Asia but now established in the United States, as well as Australasia and several Pacific islands. Although H. longicornis has not yet been associated with human disease transmission in the United States, it warrants attention as a potential vector, as it is demonstrated to harbor various pathogens of medical and veterinary interest across its native and introduced range.
Disentangling semantic and prosodic features of English poetry
Authors: Shang Wenyi , Underwood Ted
Published: February 2024

The distinction between genre and form is still contested in literary studies. While scholars associated with the New Formalism are criticized for perceiving everything as a form, digital humanists tend to argue that everything is a genre. In this research, we employed machine learning models to classify 36,635 English poems in the Chadwyck-Healey Literature Collections into twenty-seven categories, focusing on their semantic features (lexicons) and prosodic features (meters and rhymes) independently. Our findings reveal that different categories of poetry are distinguished by different groups of characteristics, without a clear-cut division between those driven predominantly by semantic features and those driven predominantly by prosodic features. Instead, poetry categories manifest a combination of semantic and prosodic elements, spanning a spectrum of different strengths in both domains. These findings suggest that the colloquial distinction between “genre” and “form” is based on real differences between poetic categories, although those differences may not be quite as crisply binary as the vocabulary implies.
Detecting anomalous proteins using deep representations
Authors: Michael-Pitschaze Tomer , Cohen Niv , Ofer Dan , Hoshen Yedid , Linial Michal
Published: February 2024

Many advances in biomedicine can be attributed to identifying unusual proteins and genes. Many of these proteins’ unique properties were discovered by manual inspection, which is becoming infeasible at the scale of modern protein datasets. Here, we propose to tackle this challenge using anomaly detection methods that automatically identify unexpected properties. We adopt a state-of-the-art anomaly detection paradigm from computer vision, to highlight unusual proteins. We generate meaningful representations without labeled inputs, using pretrained deep neural network models. We apply these protein language models (pLM) to detect anomalies in function, phylogenetic families, and segmentation tasks. We compute protein anomaly scores to highlight human prion-like proteins, distinguish viral proteins from their host proteome, and mark non-classical ion/metal binding proteins and enzymes. Other tasks concern segmentation of protein sequences into folded and unstructured regions. We provide candidates for rare functionality (e.g. prion proteins). Additionally, we show the anomaly score is useful in 3D folding-related segmentation. Our novel method shows improved performance over strong baselines and has objectively high performance across a variety of tasks. We conclude that the combination of pLM and anomaly detection techniques is a valid method for discovering a range of global and local protein characteristics.
Integrative omics analysis elucidates the genetic basis underlying seed weight and oil content in soybean
Authors: Yuan Xiaobo , Jiang Xinyu , Zhang Mengzhu , Wang Longfei , Jiao Wu , Chen Huatao , Mao Junrong , Ye Wenxue , Song Qingxin
Published: February 2024

Synergistic optimization of key agronomic traits by traditional breeding has dramatically enhanced crop productivity in the past decades. However, the genetic basis underlying coordinated regulation of yield- and quality-related traits remains poorly understood. Here, we dissected the genetic architectures of seed weight and oil content by combining genome-wide association studies (GWAS) and transcriptome-wide association studies (TWAS) using 421 soybean (Glycine max) accessions. We identified 26 and 33 genetic loci significantly associated with seed weight and oil content by GWAS, respectively, and detected 5,276 expression quantitative trait loci (eQTLs) regulating expression of 3,347 genes based on population transcriptomes. Interestingly, a gene module (IC79), regulated by two eQTL hotspots, exhibited significant correlation with both seed weigh and oil content. Twenty-two candidate causal genes for seed traits were further prioritized by TWAS, including Regulator of Weight and Oil of Seed 1 (GmRWOS1), which encodes a sodium pump protein. GmRWOS1 was verified to pleiotropically regulate seed weight and oil content by gene knockout and overexpression. Notably, allelic variations of GmRWOS1 were strongly selected during domestication of soybean. This study uncovers the genetic basis and network underlying regulation of seed weight and oil content in soybean and provides a valuable resource for improving soybean yield and quality by molecular breeding.
Arabidopsis as a model for translational research
Authors: Yaschenko Anna E , Alonso Jose M , Stepanova Anna N
Published: February 2024

Arabidopsis thaliana is currently the most-studied plant species on earth, with an unprecedented number of genetic, genomic, and molecular resources having been generated in this plant model. In the era of translating foundational discoveries to crops and beyond, we aimed to highlight the utility and challenges of using Arabidopsis as a reference for applied plant biology research, agricultural innovation, biotechnology, and medicine. We hope that this review will inspire the next generation of plant biologists to continue leveraging Arabidopsis as a robust and convenient experimental system to address fundamental and applied questions in biology. We aim to encourage laboratory and field scientists alike to take advantage of the vast Arabidopsis datasets, annotations, germplasm, constructs, methods, and molecular and computational tools in our pursuit to advance understanding of plant biology and help feed the world's growing population. We envision that the power of Arabidopsis-inspired biotechnologies and foundational discoveries will continue to fuel the development of resilient, high-yielding, nutritious plants for the betterment of plant and animal health and greater environmental sustainability.
Nationwide estimation of daily ambient PM2.5 from 2008 to 2020 at 1 km2 in India using an ensemble approach
Authors: Mandal Siddhartha , Rajiva Ajit , Kloog Itai , Menon Jyothi S , Lane Kevin J , Amini Heresh , Walia Gagandeep K , Dixit Shweta , Nori-Sarma Amruta , Dutta Anubrati , Sharma Praggya , Jaganathan Suganthi , Madhipatla Kishore K , Wellenius Gregory A , de Bont Jeroen , Venkataraman Chandra , Prabhakaran Dorairaj , Prabhakaran Poornima , Ljungman Petter , Schwartz Joel
Published: February 2024

High-resolution assessment of historical levels is essential for assessing the health effects of ambient air pollution in the large Indian population. The diversity of geography, weather patterns, and progressive urbanization, combined with a sparse ground monitoring network makes it challenging to accurately capture the spatiotemporal patterns of ambient fine particulate matter (PM2.5) pollution in India. We developed a model for daily average ambient PM2.5 between 2008 and 2020 based on monitoring data, meteorology, land use, satellite observations, and emissions inventories. Daily average predictions at each 1 km × 1 km grid from each learner were ensembled using a Gaussian process regression with anisotropic smoothing over spatial coordinates, and regression calibration was used to account for exposure error. Cross-validating by leaving monitors out, the ensemble model had an R2 of 0.86 at the daily level in the validation data and outperformed each component learner (by 5–18%). Annual average levels in different zones ranged between 39.7 μg/m3 (interquartile range: 29.8–46.8) in 2008 and 30.4 μg/m3 (interquartile range: 22.7–37.2) in 2020, with a cross-validated (CV)-R2 of 0.94 at the annual level. Overall mean absolute daily errors (MAE) across the 13 years were between 14.4 and 25.4 μg/m3. We obtained high spatial accuracy with spatial R2 greater than 90% and spatial MAE ranging between 7.3–16.5 μg/m3 with relatively better performance in urban areas at low and moderate elevation. We have developed an important validated resource for studying PM2.5 at a very fine spatiotemporal resolution, which allows us to study the health effects of PM2.5 across India and to identify areas with exceedingly high levels.
The Temporality of Intimate Partner Violence – How an Understanding of Time and Gendered Threats Can Foster Protection-Positive Outcomes
Authors: Aitchison Sharelle
Published: February 2024

This article brings together temporality and gender in the refugee process and examines how refugee determination bodies and courts have interpreted gendered threats, as a specific form of intimate partner violence. A case law review of jurisdictions (that include Australia, Canada, New Zealand, and the UK) is conducted, revealing a flawed temporal phenomenon where decision-makers have focused primarily on the exogenous aspect of threats, namely, whether there is a real chance of a threat being actuated in the future, and have largely failed to assess the endogenous, psychological dimension of the threat, that encompasses past, present, and future aspects of time. The practice of treating threats of violence as a potential future harm rather than an already occurring harm exhibits an obvious privileging of the future over the present that is not rooted in the empirical evidence on intimate partner violence. Further, the predominant focus by decision-makers on isolated future events as harm fails to accommodate the broad temporal dimensions of systemic intimate partner violence, best suited to a predicament-based model of being persecuted. This article explores the temporal shortcomings and gendered interpretations that underpin this erroneous practice in case law, finding that the temporal governance of refugee law is still largely shaped by the male gaze and conceptualisations of masculinity and femininity, which contributes to the limited recognition of threats as a form of harm in themselves.
Updates on interstitial lung disease and other selected extra-articular manifestations of rheumatoid arthritis
Authors: Myasoedova Elena , Matteson Eric L.
Published: February 2024

Purpose of review

To discuss changes in epidemiology, recent advances in understanding of the pathogenesis and management of selected extraarticular manifestations of rheumatoid arthritis (ExRA).

Recent findings

The incidence of ExRA overall and subcutaneous rheumatoid nodules in particular is declining after 2000. These trends reflect improved RA disease activity with early effective immunosuppressive treatments; changing environmental risk factors can be contributing. ExRA continues to carry a two-fold increased mortality risk. RA-associated interstitial lung disease (RA-ILD) is a major contributor to mortality, with no decline in incidence and scant therapeutic options. Individualized risk stratification for RA-ILD based on patient-level risk factors and biomarker profile is evolving with MUC5B as a major genetic risk factor. Clinical trials are underway to evaluate the benefits of novel antifibrotic therapies and targeted therapies for RA-ILD. The risk of cardiovascular disease in RA is generally amendable to treatment with disease-modifying antirheumatic drugs, although cardiovascular risk associated with JAK inhibition is not fully understood.

Despite reduction in incidence of ExRA overall, the incidence of RA-ILD shows no significant decline and remains a major therapeutic challenge. The use of novel antifibrotics and immunosuppressive drugs shows promise in slowing the progression of RA-ILD.
Intraoperative Epiphyseal Perfusion Monitoring Does Not Reliably Predict Osteonecrosis Following Treatment of Unstable SCFE
Authors: Ellsworth Bridget K. , Lee Julianna Y. , Batley Morgan G. , Sankar Wudbhav N.
Published: February 2024

Background:

Avascular necrosis (AVN) remains the most dreaded complication of unstable slipped capital femoral epiphysis (SCFE) treatment. Newer closed reduction techniques (with perfusion monitoring) have emerged as a technically straightforward means to address residual SCFE deformity while still minimizing the risk of osteonecrosis. However, limited data exists regarding the reliability of intraoperative epiphyseal perfusion monitoring to predict the development of AVN. The purpose of this study was to evaluate its reliability.

Methods:

We retrospectively reviewed all patients with unstable SCFE who underwent closed or open reduction with epiphyseal perfusion monitoring using an intracranial pressure (ICP) probe from 2015 to 2023 at a single institution with a minimum 6-month radiographic follow-up. Demographic, clinical, and radiographic data were recorded, including duration of symptoms, type of reduction, capsulotomy performed, presence of a waveform on ICP monitoring after epiphyseal fixation, and development of AVN on follow-up radiographs.

Results:

Our cohort included 33 hips (32 patients), of which 60.6% (n=20) were male. The average age was 12.5±1.8 years, with a median follow-up of 15.8 months. Eleven hips were treated with open reduction using the modified Dunn technique (10 hips) or anterior approach (1 hip), and 22 hips were treated with inadvertent (5 hips) or purposeful closed reduction using the Leadbetter technique (17 hips). Overall, 8 of the 33 hips in our series (24.2%) developed AVN, 6 of which (20%) had a pulsatile waveform on intraoperative epiphyseal perfusion monitoring. The overall rate of AVN after closed reductions was 31.8% (7 of 22 hips); the incidence of AVN after closed reduction with a detectable waveform was 30% (6 of 20 hips). There was no significant association between time to surgery (P=0.416) or type of reduction (P=0.218) and the incidence of AVN.

Conclusions:

In this series, intraoperative epiphyseal perfusion monitoring did not reliably predict the development of osteonecrosis. To our knowledge, this is the first study to report AVN after demonstrable intraoperative epiphyseal perfusion following closed reduction of unstable slips.

Level of Evidence:

Level IV: case series—therapeutic study.