bluuebunny/crossref_metadata_2025 huggingface dataset:
TapA acts as specific chaperone in TasA filament formation by strand complementation
Authors: Roske Yvette , Lindemann Florian , Diehl Anne , Cremer Nils , Higman Victoria A. , Schlegel Brigitte , Leidert Martina , Driller Kristina , Turgay Kürşad , Schmieder Peter , Heinemann Udo , Oschkinat Hartmut
Published: April 2023

Studying mechanisms of bacterial biofilm generation is of vital importance to understanding bacterial cell–cell communication, multicellular cohabitation principles, and the higher resilience of microorganisms in a biofilm against antibiotics. Biofilms of the nonpathogenic, gram-positive soil bacterium
Bacillus subtilis
serve as a model system with biotechnological potential toward plant protection. Its major extracellular matrix protein components are TasA and TapA. The nature of TasA filaments has been of debate, and several forms, amyloidic and non-Thioflavin T-stainable have been observed. Here, we present the three-dimensional structure of TapA and uncover the mechanism of TapA-supported growth of nonamyloidic TasA filaments. By analytical ultracentrifugation and NMR, we demonstrate TapA-dependent acceleration of filament formation from solutions of folded TasA. Solid-state NMR revealed intercalation of the N-terminal TasA peptide segment into subsequent protomers to form a filament composed of β-sandwich subunits. The secondary structure around the intercalated N-terminal strand β0 is conserved between filamentous TasA and the Fim and Pap proteins, which form bacterial type I pili, demonstrating such construction principles in a gram-positive organism. Analogous to the chaperones of the chaperone-usher pathway, the role of TapA is in donating its N terminus to serve for TasA folding into an Ig domain-similar filament structure by donor-strand complementation. According to NMR and since the V-set Ig fold of TapA is already complete, its participation within a filament beyond initiation is unlikely. Intriguingly, the most conserved residues in TasA-like proteins (camelysines) of
Bacillaceae
are located within the protomer interface.
Observation-derived 2010-2019 trends in methane emissions and intensities from US oil and gas fields tied to activity metrics
Authors: Lu Xiao , Jacob Daniel J. , Zhang Yuzhong , Shen Lu , Sulprizio Melissa P. , Maasakkers Joannes D. , Varon Daniel J. , Qu Zhen , Chen Zichong , Hmiel Benjamin , Parker Robert J. , Boesch Hartmut , Wang Haolin , He Cheng , Fan Shaojia
Published: April 2023

The United States is the world’s largest oil/gas methane emitter according to current national reports. Reducing these emissions is a top priority in the US government’s climate action plan. Here, we use a 2010 to 2019 high-resolution inversion of surface and satellite observations of atmospheric methane to quantify emission trends for individual oil/gas production regions in North America and relate them to production and infrastructure. We estimate a mean US oil/gas methane emission of 14.8 (12.4 to 16.5) Tg a−1for 2010 to 2019, 70% higher than reported by the US Environmental Protection Agency. While emissions in Canada and Mexico decreased over the period, US emissions increased from 2010 to 2014, decreased until 2017, and rose again afterward. Increases were driven by the largest production regions (Permian, Anadarko, Marcellus), while emissions in the smaller production regions generally decreased. Much of the year-to-year emission variability can be explained by oil/gas production rates, active well counts, and new wells drilled, with the 2014 to 2017 decrease driven by reduction in new wells and the 2017 to 2019 surge driven by upswing of production. We find a steady decrease in the oil/gas methane intensity (emission per unit methane gas production) for almost all major US production regions. The mean US methane intensity decreased from 3.7% in 2010 to 2.5% in 2019. If the methane intensity for the oil/gas supply chain continues to decrease at this pace, we may expect a 32% decrease in US oil/gas emissions by 2030 despite projected increases in production.
Merged magnetic resonance and light sheet microscopy of the whole mouse brain
Authors: Johnson G. Allan , Tian Yuqi , Ashbrook David G. , Cofer Gary P. , Cook James J. , Gee James C. , Hall Adam , Hornburg Kathryn , Kaczorowski Catherine C. , Qi Yi , Yeh Fang-Cheng , Wang Nian , White Leonard E. , Williams Robert W.
Published: April 2023

We have developed workflows to align 3D magnetic resonance histology (MRH) of the mouse brain with light sheet microscopy (LSM) and 3D delineations of the same specimen. We start with MRH of the brain in the skull with gradient echo and diffusion tensor imaging (DTI) at 15 μm isotropic resolution which is ~
1,000 times
higher than that of most preclinical MRI. Connectomes are generated with superresolution tract density images of ~5 μm. Brains are cleared, stained for selected proteins, and imaged by LSM at 1.8 μm/pixel. LSM data are registered into the reference MRH space with labels derived from the ABA common coordinate framework. The result is a 
hi
gh-
d
imensional 
i
ntegrated 
v
olum
e
 with 
r
egistration (
HiDiver
) with alignment precision better than 50 µm. Throughput is sufficiently high that HiDiver is being used in quantitative studies of the impact of gene variants and aging on mouse brain cytoarchitecture and connectomics.
Spatiotemporally distributed frontotemporal networks for sentence reading
Authors: Woolnough Oscar , Donos Cristian , Murphy Elliot , Rollo Patrick S. , Roccaforte Zachary J. , Dehaene Stanislas , Tandon Nitin
Published: April 2023

Reading a sentence entails integrating the meanings of individual words to infer more complex, higher-order meaning. This highly rapid and complex human behavior is known to engage the inferior frontal gyrus (IFG) and middle temporal gyrus (MTG) in the language-dominant hemisphere, yet whether there are distinct contributions of these regions to sentence reading is still unclear. To probe these neural spatiotemporal dynamics, we used direct intracranial recordings to measure neural activity while reading sentences, meaning-deficient Jabberwocky sentences, and lists of words or pseudowords. We isolated two functionally and spatiotemporally distinct frontotemporal networks, each sensitive to distinct aspects of word and sentence composition. The first distributed network engages the IFG and MTG, with IFG activity preceding MTG. Activity in this network ramps up over the duration of a sentence and is reduced or absent during Jabberwocky and word lists, implying its role in the derivation of sentence-level meaning. The second network engages the superior temporal gyrus and the IFG, with temporal responses leading those in frontal lobe, and shows greater activation for each word in a list than those in sentences, suggesting that sentential context enables greater efficiency in the lexical and/or phonological processing of individual words. These adjacent, yet spatiotemporally dissociable neural mechanisms for word- and sentence-level processes shed light on the richly layered semantic networks that enable us to fluently read. These results imply distributed, dynamic computation across the frontotemporal language network rather than a clear dichotomy between the contributions of frontal and temporal structures.
Predicting and optimising the surface roughness of additive manufactured parts using an artificial neural network model and genetic algorithm
Authors: Ulkir Osman , Akgun Gazi
Published: April 2023

The selection of parameters affects the surface roughness in the additive manufacturing process. This study aims to determine the optimal combination of input parameters for predicting and minimising the surface roughness of samples produced by Fused Deposition Modelling on a 3D printer using a cascade-forward neural network (CFNN) and genetic algorithm. Box–Behnken Design with four independent printing parameters at three levels is used, and 25 parts are fabricated with a 3D printer. Roughness tests are performed on the fabricated parts. Models generated by the hybrid algorithm achieve the best results for predicting and optimising surface roughness in 3D-printed parts. The surface roughness prediction accuracy of the trained CFNN with optimised parameters is more accurate compared to previous random test results.
The outdoor nature, indoors: relationship between contact with nature, life satisfaction and affect during a COVID-19 pandemic lockdown (La naturaleza al aire libre, en el interior: relación entre contacto con la naturaleza, satisfacción vital y afectividad durante el confinamiento por la pandemia COVID-19)
Authors: Almeida Inês , Lopes Carla , Pedroso Rita , Gaspar Rui
Published: April 2023

The COVID-19 pandemic led to national lockdown measures, implying individuals’ household confinement, constraining active contact with outdoor nature, with potential associated mental health consequences. Hence, this cross-sectional correlational design study with 310 participants examined the relationship between self-reported measures of variety and intensity of indoor/outdoor activities involving contact with nature, life satisfaction and affect during the first nationwide lockdown in Portugal in 2020. Results showed a positive weak association between indoor activity intensity and positive affect, and between reported indoor mental recreation of contact with nature and negative affect. Actual indoor contact with nature was positively associated with life satisfaction and positive affect. Individuals without a variety of contact with indoor nature reported lower life satisfaction than those with high variety. Indoor contact with nature seemed particularly important for well-being during lockdown. During prolonged household confinement, mental health and well-being could be promoted through outdoor contact but indoor alternatives should also be considered.
Stochastic mirror descent method for linear ill-posed problems in Banach spaces
Authors: Jin Qinian , Lu Xiliang , Zhang Liuying
Published: April 2023

Consider linear ill-posed problems governed by the system

A
i

x
=

y
i

for

i
=
1
,
…
,
p

, where each A

i
is a bounded linear operator from a Banach space X to a Hilbert space Y

i
. In case p is huge, solving the problem by an iterative regularization method using the whole information at each iteration step can be very expensive, due to the huge amount of memory and excessive computational load per iteration. To solve such large-scale ill-posed systems efficiently, we develop in this paper a stochastic mirror descent method which uses only a small portion of randomly selected equations at each iteration step and incorporates convex regularization terms into the algorithm design. Therefore, our method scales very well with the problem size and has the capability of capturing features of sought solutions. The convergence property of the method depends crucially on the choice of step-sizes. We consider various rules for choosing step-sizes and obtain convergence results under a priori early stopping rules. In particular, by incorporating the spirit of the discrepancy principle we propose a choice rule of step-sizes which can efficiently suppress the oscillations in iterates and reduce the effect of semi-convergence. Furthermore, we establish an order optimal convergence rate result when the sought solution satisfies a benchmark source condition. Various numerical simulations are reported to test the performance of the method.
Expectation–maximization machine learning model for micromechanical evaluation of thermally-cycled solder joints in a semiconductor
Authors: Chen Tzu-Chia
Published: April 2023

This paper aims to study the microstructural and micromechanical variations of solder joints in a semiconductor under the evolution of thermal-cycling loading. For this purpose, a model was developed on the basis of expectation–maximization machine learning (ML) and nanoindentation mapping. Using this model, it is possible to predict and interpret the microstructural features of solder joints through the micromechanical variations (i.e. elastic modulus) of interconnection. According to the results, the classification of Sn-based matrix, intermetallic compounds (IMCs) and the grain boundaries with specified elastic-modulus ranges was successfully performed through the ML model. However, it was detected some overestimations in regression process when the interfacial regions got thickened in the microstructure. The ML outcomes also revealed that the thermal-cycling evolution was accompanied with stiffening and growth of IMCs; while the spatial portion of Sn-based matrix decreased in the microstructure. It was also figured out that the stiffness gradient becomes intensified in the treated samples, which is consistent with this fact that the thermal cycling increases the mechanical mismatch between the matrix and the IMCs.
Effects of metallic electrodes on the thermoelectric properties of zigzag graphene nanoribbons with periodic vacancies
Authors: Kuo David M T
Published: April 2023

We theoretically analyze the thermoelectric properties of graphene quantum dot arrays (GQDAs) with line- or surface-contacted metal electrodes. Such GQDAs are realized as zigzag graphene nanoribbons (ZGNRs) with periodic vacancies. Gaps and minibands are formed in these GQDAs, which can have metallic and semiconducting phases. The electronic states of the first conduction (valence) miniband with nonlinear dispersion may have long coherent lengths along the zigzag edge direction. With line-contacted metal electrodes, the GQDAs have the characteristics of serially coupled quantum dots (SCQDs) if the armchair edge atoms of the ZGNRs are coupled to the electrodes. By contrast, the GQDAs have the characteristics of parallel quantum dots if the zigzag edge atoms are coupled to the electrodes. The maximum thermoelectric power factors of SCQDs with line-contacted electrodes of Cu, Au, Pt, Pd, or Ti at room temperature were similar or greater than 0.186 nW K−1; their figures of merit were greater than three. GQDAs with line-contacted metal electrodes have much better thermoelectric performance than surface contacted metal electrodes.
Localized magnetic moment induced by boron adatoms chemisorbed on graphene
Authors: Li Chong , Wang Fei , Cui Bin , Pan Zhifeng , Jia Yu
Published: April 2023

Inducing local spin-polarization in pristine graphene is highly desirable and recent experiment shows that boron adatom chemical attachment to graphene exhibits local high spin state. Using hybrid exchange-correlation functional, we show that boron (B) monomer chemisorbed on the bridge site of graphene is energically favorable, and indeed induces a weak local spin-polarization ∼0.56 μB. The localized magnetic moment can be attributed to the charge transfer from boron atom to graphene, resulting in local spin charge dominantly surrounding to the adsorbed B and neighboring carbon (C) atoms. We also surprisingly find that boron dimer can even much more stable upright anchor the same site of graphene, giving rise to sizable spin magnetic moment 2.00 μB. Although the apparent spin state remains mainly contributed by B p and C p orbitals as the case of boron monomer, the delicate and substantial charge transfer of the intra-dimer plays a fundamental role in producing such sizable local spin-polarization. We employed various van der Waals corrections to check and confirm the validity of appeared local spin-polarization. In terms of the almost identical simulated scanning tunneling microscope between boron monomer and dimer, we might tend to support the fact that boron dimer can also be chemisorbed on graphene with much larger and stable localized spin magnetic moment.
Randomized channel subsampling method for efficient ultrafast ultrasound imaging
Authors: Yu Junjin , Guo Xingyi , Yan Shaoyuan , Le Qiumin , Hingot Vincent , Ta Dean , Couture Olivier , Xu Kailiang
Published: April 2023

Emerging as a novel modality with high spatiotemporal sensitivity, ultrafast ultrasound imaging has been well established and incorporated into clinical apparatus. However, such a mode typically requires large data acquisitions, with more than thousands of frames per second within a relatively long period, which poses high demands on real-time storage and processing hardware. Herein, an image reconstruction approach based on randomized channel subsampling is presented, which significantly reduces the amount of data acquisition while maintaining imaging performance. In vivo datasets from rats were used to evaluate the performance of the proposed method in B-mode imaging, ultrafast Doppler imaging, and super-resolution ultrasound localization microscopy (ULM) under different subsampling conditions. Following a thorough comparison of the contrast-to-noise ratio, signal-to-noise ratio, and visibility of the ultrafast Doppler based small-vessel imaging, the resolution and saturation of ULM imaging were also investigated under different subsampling conditions. The feasibility of the proposed method was demonstrated in task-based functional ultrasound (fUS) imaging with whisker stimulation. A comparison between the results of fUS based on introduced randomized channel subsampling and conventional fUS was also conducted to evaluate the subsampling effects on reconstruction accuracy and cerebral change detection sensitivity.
Tritium-titanium target degradation due to deuterium irradiation for DT neutron production
Authors: Rajput M. , Swami H.L. , Vala S. , Abhangi M. , Kumar Ratnesh , Kumar R.
Published: April 2023

In the present article, we have investigated tritium removal from tritium-titanium targets during fusion neutron production and the impact of tritium degradation on neutron production. The removal of tritium from the target is predicted for deuterium ion irradiation with the SDTrimSp code. We adopt the binary collision approximation method to simulate the recoils and projectile trajectories and concentration of constituents in the target. We have modelled four phenomena in our simulations; ion exchange, sputtering, outgassing of tritium, and thermal diffusion of hydrogen isotopes in the target caused by deuterium irradiation. Insignificant contributors such as burn-up of tritium in neutron production and loss of tritium due to radioactive decay are not included in our model. This tritium removal results in the nonuniform distribution of tritium in the target. A Python-based script is developed to investigate the effects of tritium removal on neutron production with these pristine and irradiated targets. This script uses the layered composition of the constituents’ atoms, DT reaction cross-section, and stopping power of deuterium ions in the target. The script is validated with the NeuSdesc code for the pristine target. Using the layered composition of tritium atoms in the target obtained from the SDTrimSp simulations, the script predicts the degradation in neutron production for different irradiation scenarios.
A quasi-isodynamic configuration with good confinement of fast ions at low plasma β
Authors: Sánchez E. , Velasco J.L. , Calvo I. , Mulas S.
Published: April 2023

A new quasi-isodynamic (QI) stellarator configuration optimized for the confinement of energetic ions at low plasma β is obtained. The numerical optimization is carried out using the STELLOPT suite of codes. New proxies to measure closeness to quasi-isodynamicity and quality of fast ion confinement have been included. The new configuration has poloidally closed contours of magnetic field strength, low magnetic shear and a rotational transform profile allowing an island divertor. It shows ideal and ballooning magnetohydrodynamic stability up to

β
=
5
%

, reduced effective ripple, with

ϵ

e
f
f

<
0.5
%

in the plasma core. Even at low β, the configuration approximately satisfies the maximum-J property, and the confinement of fast ions is good at

β
∼
1.5
%

and becomes excellent at reactor values,

β
∼
4
%

. An evaluation of the D
31 neoclassical mono-energetic coefficient supports the expectation of a reduced bootstrap current for plasmas confined in QI configurations. A set of filamentary coils that preserve the good confinement of fast ions in the core is presented.
Optimal scheduling strategy of the hydrogen-electric coupled system considering source-load uncertainty
Authors: Chen Jianhao , Xie Changjun , Ye Hao , Li Shenwei , Li Yingzhu
Published: April 2023

Hybrid energy storage systems are increasingly envisaged to be used in the construction of microgrids to alleviate the intermittency of renewable energy output and achieve large-scale penetration into the power grid. The hydrogen-electric coupled system (HECS) combines long-term hydrogen storage with short-term battery storage and realizes the conversion of multiple energy flows through power to gas and gas to power. However, the optimal scheduling of such a hybrid energy storage system is more complex than a single one. Faced with this issue, this paper proposed a HECS scheduling method based on the storage degradation cost to solve the power distribution problem. Furthermore, to reduce the impact of source-load uncertainty, the improved k-medoids method is used to extract representatively typical and extreme scenarios from the annual data to evaluate the economy and reliability of the system operation. According to the simulation result, we can conclude that the proposed method achieves cost-optimal scheduling by maximizing hydrogen production in the on-grid mode and reducing the battery cycle cost in the off-grid mode. Compared with the state machine control strategy, the proposed method has lowered the operation cost in all simulation scenarios and shows its effectiveness. Finally, the results show that the operation cost can be reduced by applying a demand response program, especially in the off-grid mode.
Application of Fast-Charging Graphite-Anode Lithium-Ion Batteries in Black Start
Authors: Chen Yixing , Zuo Jian , He Xiangzhen , Zhang Shuiping , Bao Bo
Published: April 2023

Industrial and commercial energy storage are widely used. Large industrial users can adjust the peak and valley power consumption during the summer peak power consumption to reduce the burden on transformers and to gain certain benefits from the peak and valley power difference. For users with important loads, the energy storage system is a alternative power supply to ensure the continuity of power supply for important loads. This paper systematically introduced the research progress based on the optimization of electrolyte and charging strategy in the field of improving the rapid charging of graphite anodes in recent years, which provided a reference for promoting the commercial application of rapid charging technology and the high-quality development of domestic energy storage technology. The high-power energy storage battery, in particular, can recover power supply as soon as possible after large-scale power system shutdown accidents or even power outages, reducing economic losses and social impact.
Quantum scrambling via accessible tripartite information
Authors: Lo Monaco Gabriele , Innocenti Luca , Cilluffo Dario , Chisholm Diana A , Lorenzo Salvatore , Palma G Massimo
Published: April 2023

Quantum information scrambling (QIS), from the perspective of quantum information theory, is generally understood as local non-retrievability of information evolved through some dynamical process, and is often quantified via entropic quantities such as the tripartite information. We argue that this approach comes with a number of issues, in large part due to its reliance on quantum mutual informations, which do not faithfully quantify correlations directly retrievable via measurements, and in part due to the specific methodology used to compute tripartite informations of the studied dynamics. We show that these issues can be overcome by using accessible mutual informations, defining corresponding ‘accessible tripartite informations’, and provide explicit examples of dynamics whose scrambling properties are not properly quantified by the standard tripartite information. Our results lay the groundwork for a more profound understanding of what QIS represents, and reveal a number of promising, as of yet unexplored, venues for further research.
A study of intention to recycle pesticide packaging among rural farmers in China based on the logistic model
Authors: Li Ye , Wang Ying , Han Xinran , Wang Haodong , Fu Jia
Published: April 2023

A consequence of the improvement in China’s agricultural production capacity has been increased production of pesticide packaging waste, which is a major obstacle to the sustainable development of rural areas. Although the Chinese government has made great efforts to control pollution by waste pesticide packaging, a unified recycling system has not yet been established. Therefore, determining whether farmers are willing to participate in recycling of pesticide packaging is of great relevance. This study conducted a random questionnaire survey in which 459 responses were obtained in rural areas in Liaoning, Henan, Guizhou, Anhui, Gansu, and Hunan provinces. The disorderly classification logistic model was used to analyze the individual characteristics of farmers, pesticide container sizes, perception of risk, conditions of local facilities, and awareness. The result showed that the individual characteristics of farmers and awareness had no influence of their willingness to participate in recycling, whereas container size, perception of risk, and condition of local facilities did have an influence. Container specifications have the strongest correlation with farmers’ willingness to recycle, and attempts can be made to promote pesticide packaging of about 500 ml; raising farmers’ awareness of environmental safety and possible health hazards, all of which can increase farmers’ participation in the work. Using these results, this study proposed suggestions for pesticide container waste disposal. Attempts can be made to establish a suitable recycling model and management mechanism through the establishment of additional recycling points. Refine pesticide packaging waste recycling, collection and storage, disposal and other measures to purify the environment of origin, to achieve green agricultural development, and promote the construction of ecological civilization.
Turkey: A Historical Overview
Authors: Brockett Gavin
Published: April 2023

That history reflects the moment in which it is written is no more apparent than in the case of Turkey. To write the history of Turkey at a time when the Middle East is roiling in the complex set of expectations and events associated with the Arab uprisings is to attempt to explain a country profoundly impacted by regional turmoil yet also engulfed in its own strife, the outcomes of which are far from clear. At first, Turkey appeared to escape the tumult that began in 2011, and its prime minister—now president—Recep Tayyip Erdoğan—even trumpeted Turkey as the paragon of political stability among countries seeking to integrate a Muslim population and democratic political order. However, in 2013 the alliance of forces that had brought about Erdoğan’s decade-long dominance and apparent Turkish economic prosperity began to unravel. The government became enmeshed not only in its own internal struggle, but also in an intensifying civil war with Kurdish groups in the southeast and in the catastrophic war in Syria. Then, on July 15, 2016, the country—and the world—was startled by a failed, but nonetheless violent, military coup. Shocked by such drastic action, Turks across the country flocked to Erdoğan’s defense. Then, once he had secured his position as president, he declared a state of emergency and embarked on a countrywide purge, arresting and/or firing from public employment tens of thousands of suspected opponents, not the least of whom were academics, some of whom had publicly challenged his growing authoritarianism and erratic rule.

Erdoğan is accused by his critics variously of either attempting to establish his own revived Ottoman “sultanate” or seeking to replicate the power and prestige once claimed by Turkey’s founding president, Mustafa Kemal Atatürk. He is president of a Turkey undergoing only the latest in successive waves of dramatic change and transformation that have been ongoing for more than a century. Formally established in 1923, Turkey’s history is that of a country whose ties with its immediate past are debated and defined according to competing ideologies and agendas of the moment. Turkey came into a paradoxical world, one defined according to the ideal of independent nation-states, while in fact the pressure to integrate and conform to transnational systems leading to increasing interdependence, lately as a result of globalization, has been enormous. While capitalist economics and democratic, representative politics indeed emerged dominant in the world in the late 20th century, their force no longer seems unassailable or certain. For almost a century, Turkey has had a conflicted relationship with the countries of “the West” that tirelessly promoted this system. Now that the authenticity of this system itself faces increasingly intense scrutiny in Europe and North America, Turkey seeks to redefine itself politically and to assert its role both regionally and globally, even as it deals with deepening crises at home.
Janatha Vimukthi Peramuna and Youth Militancy in Southern Sri Lanka
Authors: Dewasiri Nirmal Ranjith
Published: April 2023

Two insurgencies in the southern parts of Sri Lanka in 1971 and 1987 to 1989 were highly significant political events in the postcolonial period of Sri Lanka. Both these insurgencies were organized by the political organization that came to be known as Janatha Vimukthi Peramuna (JVP). The social basis of the two insurgencies was the discontent of the youth of the rural lower and middle classes. This was an outcome of a serious structural problem in the social organization, and the inability to meet the social and economic expectations of a growing young population was at the center of this structural problem. The radicalization of the discontented youth was facilitated by the dynamics of vibrant Marxist leftist politics in Sri Lanka. While the first insurgency which began in April 1971 with poorly armed men and women’s attacks on police stations and some other locations of the state machinery across ethnic Sinhalese areas, the second insurgency was much more organized. The impact of the second insurgency was much more serious for three reasons. First, unlike 1971 insurgency, the second one lasted more than two years. Second, tactics that the JVP utilized were much more ruthless compared to 1971. Individual terrorism was a main feature. Political opponents as well as ordinary people who were reluctant to carry out its orders were killed. Third, counterinsurgency measures were also much more brutal.
Impedance-Induced Beam Instabilities
Authors: Migliorati Mauro
Published: April 2023

Modern particle accelerators require ever higher currents to meet user demands, both for high-energy physics experiments and for medical and industrial applications. These high currents, interacting with the accelerators’ environment, produce strong self-induced electromagnetic fields that perturb the external fields that guide and accelerate the charged particles.

Under certain conditions, these perturbations can be so large as to limit the accelerators’ performance, giving rise to unwanted effects such as uncontrolled beam oscillations or instabilities. The self-induced fields are described in terms of the so-called wakefields and beam coupling impedances, two quantities that are used to evaluate their impact on beam dynamics and instabilities’ thresholds.

The determination of wakefields and beam coupling impedances generated by the interaction of the beam with the different machine devices, and of the corresponding induced instabilities, is therefore very important, particularly for high currents. This is carried out with analytical approaches, through the use of simplified models, or, more rigorously and realistically, through simulation codes. The first step in this study is generally represented by a complete electromagnetic characterization of the different accelerator devices and the search for possible minimization of wakefields and beam coupling impedances. Once these quantities are known, their effect on beam dynamics can be evaluated, with both simulations and analytical methods, and a proper machine working point, far away from any impedance-induced beam instabilities, can be determined.

As machine performance is pushed increasingly higher, new effects, produced by wakefields and beam coupling impedances, are found that are related, in many cases, to the coupling with other mechanisms (e.g., with beam–beam). All these effects can no longer be studied separately. Finally, mitigation solutions, such as beam coupling impedance optimization, feedback systems, the use of nonlinearities, and other techniques, must also be investigated so that different tools will be available to counteract unwanted beam-induced instabilities.
Dimensions, Ratios, Volumes, and Weights of the Fatty Parts of the Vulva (Mons Pubis and Labia Majora)
Authors: Seleem Mostafa , Osman Omneya M , Kashmar Sanaa G , Lotfy Rehab
Published: April 2023

Background

The anatomy of the fatty parts of the vulva, specifically the mons pubis and labia majora, has not been extensively studied.

Objectives

This study aimed to provide a comprehensive 3-dimensional picture of the mons pubis and labia majora by defining and measuring their dimensions. Furthermore, the study sought to calculate the different ratios, volumes, and weights of these structures.

Methods

The study included 214 women, who were divided into 2 groups based on their BMI. The researchers defined 27 dimensions to describe the width, height, and length of the mons pubis and labia majora, and specified the measuring methodology.

Results

The height of the mons pubis was approximately three-quarters of its length and half its width. The labia majora were wider and taller anteriorly than posteriorly, and their ratios decreased as they went posteriorly, from 4 to 2. The ratio of monal height to maximum labial height and to labial length was 3 and 1, respectively, whereas the ratio of monal width to the sum of maximum labial widths was nearly 1.5. The calculated volumes and weights of the mons pubis and labium majus were 200 mL, 30 mL, 180 g, and 27 g in Group 1, and 300 mL, 40 mL, 270 g, and 36 g in Group 2, respectively.

Conclusions

The dimensions, ratios, weights, and volumes defined and measured in this study can serve as the basis for any aesthetic measures involving the mons pubis and labia majora. Moreover, BMI and the different ratios should be considered in such measures.
Transformer-based anti-noise models for CRISPR-Cas9 off-target activities prediction
Authors: Guan Zengrui , Jiang Zhenran
Published: April 2023

The off-target effect occurring in the CRISPR-Cas9 system has been a challenging problem for the practical application of this gene editing technology. In recent years, various prediction models have been proposed to predict potential off-target activities. However, most of the existing prediction methods do not fully exploit guide RNA (gRNA) and DNA sequence pair information effectively. In addition, available prediction methods usually ignore the noise effect in original off-target datasets. To address these issues, we design a novel coding scheme, which considers the key features of mismatch type, mismatch location and the gRNA-DNA sequence pair information. Furthermore, a transformer-based anti-noise model called CrisprDNT is developed to solve the noise problem that exists in the off-target data. Experimental results of eight existing datasets demonstrate that the method with the inclusion of the anti-noise loss functions is superior to available state-of-the-art prediction methods. CrisprDNT is available at https://github.com/gzrgzx/CrisprDNT.
SmartGate is a spatial metabolomics tool for resolving tissue structures
Authors: Xiao Kaixuan , Wang Yu , Dong Kangning , Zhang Shihua
Published: April 2023

Imaging mass spectrometry (IMS) is one of the powerful tools in spatial metabolomics for obtaining metabolite data and probing the internal microenvironment of organisms. It has dramatically advanced the understanding of the structure of biological tissues and the drug treatment of diseases. However, the complexity of IMS data hinders the further acquisition of biomarkers and the study of certain specific activities of organisms. To this end, we introduce an artificial intelligence tool, SmartGate, to enable automatic peak selection and spatial structure identification in an iterative manner. SmartGate selects discriminative m/z features from the previous iteration by differential analysis and employs a graph attention autoencoder model to perform spatial clustering for tissue segmentation using the selected features. We applied SmartGate to diverse IMS data at multicellular or subcellular spatial resolutions and compared it with four competing methods to demonstrate its effectiveness. SmartGate can significantly improve the accuracy of spatial segmentation and identify biomarker metabolites based on tissue structure–guided differential analysis. For multiple consecutive IMS data, SmartGate can effectively identify structures with spatial heterogeneity by introducing three-dimensional spatial neighbor information.
Potential of dissimilarity measure-based computation of protein thermal stability data for determining protein interactions
Authors: Teitz Joshua , Sander Joerg , Sarker Hassan , Fernandez-Patron Carlos
Published: April 2023

Determining the interacting proteins in multiprotein complexes can be technically challenging. An emerging biochemical approach to this end is based on the ‘thermal proximity co-aggregation’ (TPCA) phenomenon. Accordingly, when two or more proteins interact to form a complex, they tend to co-aggregate when subjected to heat-induced denaturation and thus exhibit similar melting curves. Here, we explore the potential of leveraging TPCA for determining protein interactions. We demonstrate that dissimilarity measure-based information retrieval applied to melting curves tends to rank a protein-of-interest’s interactors higher than its non-interactors, as shown in the context of pull-down assay results. Consequently, such rankings can reduce the number of confirmatory biochemical experiments needed to find bona fide protein–protein interactions. In general, rankings based on dissimilarity measures generated through metric learning further reduce the required number of experiments compared to those based on standard dissimilarity measures such as Euclidean distance. When a protein mixture’s melting curves are obtained in two conditions, we propose a scoring function that uses melting curve data to inform how likely a protein pair is to interact in one condition but not another. We show that ranking protein pairs by their scores is an effective approach for determining condition-specific protein–protein interactions. By contrast, clustering melting curve data generally does not inform about the interacting proteins in multiprotein complexes. In conclusion, we report improved methods for dissimilarity measure-based computation of melting curves data that can greatly enhance the determination of interacting proteins in multiprotein complexes.
Self-supervised semantic segmentation of retinal pigment epithelium cells in flatmount fluorescent microscopy images
Authors: Yu Hanyi , Wang Fusheng , Teodoro George , Chen Fan , Guo Xiaoyuan , Nickerson John M , Kong Jun
Published: April 2023

Motivation

Morphological analyses with flatmount fluorescent images are essential to retinal pigment epithelial (RPE) aging studies and thus require accurate RPE cell segmentation. Although rapid technology advances in deep learning semantic segmentation have achieved great success in many biomedical research, the performance of these supervised learning methods for RPE cell segmentation is still limited by inadequate training data with high-quality annotations.

Results

To address this problem, we develop a Self-Supervised Semantic Segmentation (S4) method that utilizes a self-supervised learning strategy to train a semantic segmentation network with an encoder–decoder architecture. We employ a reconstruction and a pairwise representation loss to make the encoder extract structural information, while we create a morphology loss to produce the segmentation map. In addition, we develop a novel image augmentation algorithm (AugCut) to produce multiple views for self-supervised learning and enhance the network training performance. To validate the efficacy of our method, we applied our developed S4 method for RPE cell segmentation to a large set of flatmount fluorescent microscopy images, we compare our developed method for RPE cell segmentation with other state-of-the-art deep learning approaches. Compared with other state-of-the-art deep learning approaches, our method demonstrates better performance in both qualitative and quantitative evaluations, suggesting its promising potential to support large-scale cell morphological analyses in RPE aging investigations.

Availability and implementation

The codes and the documentation are available at: https://github.com/jkonglab/S4_RPE.
POIROT: a powerful test for parent-of-origin effects in unrelated samples leveraging multiple phenotypes
Authors: Head S Taylor , Leslie Elizabeth J , Cutler David J , Epstein Michael P
Published: April 2023

Motivation

There is widespread interest in identifying genetic variants that exhibit parent-of-origin effects (POEs) wherein the effect of an allele on phenotype expression depends on its parental origin. POEs can arise from different phenomena including genomic imprinting and have been documented for many complex traits. Traditional tests for POEs require family data to determine parental origins of transmitted alleles. As most genome-wide association studies (GWAS) sample unrelated individuals (where allelic parental origin is unknown), the study of POEs in such datasets requires sophisticated statistical methods that exploit genetic patterns we anticipate observing when POEs exist. We propose a method to improve discovery of POE variants in large-scale GWAS samples that leverages potential pleiotropy among multiple correlated traits often collected in such studies. Our method compares the phenotypic covariance matrix of heterozygotes to homozygotes based on a Robust Omnibus Test. We refer to our method as the Parent of Origin Inference using Robust Omnibus Test (POIROT) of multiple quantitative traits.

Results

Through simulation studies, we compared POIROT to a competing univariate variance-based method which considers separate analysis of each phenotype. We observed POIROT to be well-calibrated with improved power to detect POEs compared to univariate methods. POIROT is robust to non-normality of phenotypes and can adjust for population stratification and other confounders. Finally, we applied POIROT to GWAS data from the UK Biobank using BMI and two cholesterol phenotypes. We identified 338 genome-wide significant loci for follow-up investigation.

Availability and implementation

The code for this method is available at https://github.com/staylorhead/POIROT-POE.
Building Capacity for Social Care Research—Individual-Level and Organisational Barriers Facing Practitioners
Authors: Pulman Andy , Fenge Lee-Ann
Published: April 2023

To achieve a growth in practice-focused research, social care requires a solid infrastructure including a skilled research workforce, funding and a framework of national, strategic priorities. This article concerns practitioner researchers and developing the skills and support to enable practitioners to become active researchers within social care practice. It reports on findings from a study to develop a better understanding of the challenges of building capacity to undertake social care research in the South of England and the opportunities for building research engagement and capacity within local authorities (LAs) to include practitioner-led research. A qualitative approach was undertaken. Participants were practitioners working in LA social service departments. Participants completed an online questionnaire (n = 22), with a subsample (n = 6) interviewed. A semi-structured interview schedule collected positive and negative views of research experiences and of using research evidence. Individual-level and organisational research barriers were extracted as themes from the data and are described. The authors then discuss areas where practical ground level initiatives could be focused that might assist in developing a more positive research environment within social care organisations employing social workers and other practitioners.
Thalamostriatal disconnection underpins long-term seizure freedom in frontal lobe epilepsy surgery
Authors: Giampiccolo Davide , Binding Lawrence P , Caciagli Lorenzo , Rodionov Roman , Foulon Chris , de Tisi Jane , Granados Alejandro , Finn Roisin , Dasgupta Debayan , Xiao Fenglai , Diehl Beate , Torzillo Emma , Van Dijk Jan , Taylor Peter N , Koepp Matthias , McEvoy Andrew W , Baxendale Sallie , Chowdhury Fahmida , Duncan John S , Miserocchi Anna
Published: April 2023

Around 50% of patients undergoing frontal lobe surgery for focal drug-resistant epilepsy become seizure free post-operatively; however, only about 30% of patients remain seizure free in the long-term. Early seizure recurrence is likely to be caused by partial resection of the epileptogenic lesion, whilst delayed seizure recurrence can occur even if the epileptogenic lesion has been completely excised. This suggests a coexistent epileptogenic network facilitating ictogenesis in close or distant dormant epileptic foci. As thalamic and striatal dysregulation can support epileptogenesis and disconnection of cortico-thalamostriatal pathways through hemispherotomy or neuromodulation can improve seizure outcome regardless of focality, we hypothesize that projections from the striatum and the thalamus to the cortex may contribute to this common epileptogenic network.

To this end, we retrospectively reviewed a series of 47 consecutive individuals who underwent surgery for drug-resistant frontal lobe epilepsy. We performed voxel-based and tractography disconnectome analyses to investigate shared patterns of disconnection associated with long-term seizure freedom. Seizure freedom after 3 and 5 years was independently associated with disconnection of the anterior thalamic radiation and anterior cortico-striatal projections. This was also confirmed in a subgroup of 29 patients with complete resections, suggesting these pathways may play a critical role in supporting the development of novel epileptic networks.

Our study indicates that network dysfunction in frontal lobe epilepsy may extend beyond the resection and putative epileptogenic zone. This may be critical in the pathogenesis of delayed seizure recurrence as thalamic and striatal networks may promote epileptogenesis and disconnection may underpin long-term seizure freedom.