bluuebunny/crossref_metadata_2025 huggingface dataset:
Accelerated versus Standard Rehabilitation after Meniscus Allograft Transplantation in the Knee
Authors: Rucinski Kylee , Stannard James P. , Crecelius Cory , Nuelle Clayton , Cook James L.
Published: February 2024

Meniscus allograft transplantation (MAT) is a proven treatment option for patients with symptomatic irreparable meniscus deficiency. When patients are adherent to prescribed postoperative restriction and rehabilitation protocols, outcomes after MAT are considered good to excellent. However, nonadherence to standard protocols is common and can be associated with undesirable outcomes and patient dissatisfaction. Based on demonstrated safety for early weight-bearing following MAT in conjunction with significant advances in graft preservation and surgical techniques, our joint preservation center implemented a shift in practice toward accelerated weight-bearing following MAT and designed this study to test the hypothesis that accelerated rehabilitation would be associated with superior adherence, patient-reported outcomes, and patient satisfaction, without diminishing patient safety, when compared with standard rehabilitation. Patients were included for analyses when they had undergone fresh or fresh-frozen MAT using a double bone plug technique for treatment of medial or lateral meniscus deficiency and had at least 1-year treatment outcomes recorded. The results of this study revealed that patients who were prescribed accelerated rehabilitation after MAT were significantly more adherent than patients who were prescribed standard rehabilitation and reported statistically significant and clinically meaningful improvements in knee pain and function for at least 1-year following MAT, whereas those in the standard cohort did not. While not statistically different, treatment failure rate was lower in the accelerated rehabilitation cohort when compared with the standard rehabilitation cohort (11 vs. 29%). Importantly, initial outcomes for revision MAT were associated with short-term success in all the patients who opted for this option in the study population. These data suggest that accelerated weight-bearing after MAT is safe, promotes patient adherence, and is associated with statistically significant and clinically meaningful improvements in patient-reported knee pain and function at early and mid-term follow-up.
Lupus Anticoagulant-Hypoprothrombinemia Syndrome: Literature Review and Description of Local Case in a 3-Year-Old Chinese Girl
Authors: Wang Bin , Tang Ning , Zhang Chi
Published: February 2024

Lupus anticoagulant-hypoprothrombinemia syndrome (LAHPS) is a rare, acquired coagulopathy syndrome. Here, we aim to summarize the clinical features of LAHPS to improve the understanding of the disease. The clinical data of 52 patients with LAHPS retrieved through PubMed from 2019 to 2023, supplemented with a local case of a child with LAHPS, were retrospectively analyzed, and the clinical characteristics were summarized. 56.6% of LAHPS patients were female, the median age at onset was 13.0 years (range, 1.2–85 years), and the median activity of factor II was 18.0% (range, 0.1–69%). 64.2% of LAHPS patients experienced hemorrhage, with 29.4% having multisite hemorrhage and 20.6% experiencing both nonsevere and severe hemorrhage. Most of the reported cases were secondary to autoimmune diseases (60.6%), followed by infections (33.3%). Corticosteroids were administered to 79.3% of patients with hemorrhage, and 90.6% of patients with LAHPS showed improvement. In conclusion, LAHPS is most commonly observed in female patients, particularly those under 18 years of age. LAHPS is characterized by hemorrhage, occurring at various sites and with varying degrees of severity, but the majority of patients improve with appropriate treatment and management.
Bloch oscillations, Landau–Zener transition, and topological phase evolution in an array of coupled pendula
Authors: Neder Izhar , Sirote-Katz Chaviva , Geva Meital , Lahini Yoav , Ilan Roni , Shokef Yair
Published: February 2024

We experimentally and theoretically study the dynamics of a one-dimensional array of pendula with a mild spatial gradient in their self-frequency and where neighboring pendula are connected with weak and alternating coupling. We map their dynamics to the topological Su–Schrieffer–Heeger model of charged quantum particles on a lattice with alternating hopping rates in an external electric field. By directly tracking the dynamics of a wave-packet in the bulk of the lattice, we observe Bloch oscillations, Landau–Zener transitions, and coupling between the isospin (i.e., the inner wave function distribution within the unit cell) and the spatial degrees of freedom (the distribution between unit cells). We then use Bloch oscillations in the bulk to directly measure the nontrivial global topological phase winding and local geometric phase of the band. We measure an overall evolution of 3.1

±

0.2 radians for the geometrical phase during the Bloch period, consistent with the expected Zak phase of

π

. Our results demonstrate the power of classical analogs of quantum models to directly observe the topological properties of the band structure and shed light on the similarities and the differences between quantum and classical topological effects.
The impact of Rashba spin-orbit coupling in charge-ordered systems
Authors: Fontenele Rodrigo A , dos Anjos Sousa Júnior Sebastião , Cysne Tarik P , Costa Natanael C
Published: February 2024

We study the impact of the Rashba spin–orbit coupling (RSOC) on the stability of charge-density wave (CDW) in systems with large electron-phonon coupling (EPC). Here, the EPC is considered in the framework of the Holstein model at the half-filled square lattice. We obtain the phase diagram of the Rashba–Holstein model using the Hartree–Fock mean-field theory, and identify the boundaries of the CDW and Rashba metal phases. We notice that the RSOC disfavors the CDW phase, driving the system to a correlated Rashba metal. Also, we employ a cluster perturbation theory (CPT) approach to investigate the phase diagram beyond the Hartree–Fock approximation. The quantum correlations captured by CPT indicate that the RSOC is even more detrimental to CDW than previously anticipated. That is, the Rashba metal region is observed to be expanded in comparison to the mean-field case. Additionally, we investigate pairing correlations, and the results further strengthen the identification of critical points.
A bearing RUL prediction approach of vibration fault signal denoise modeling with Gate-CNN and Conv-transformer encoder
Authors: Huang Peng , Wang Yuanjin , Gu Yingkui , Qiu Guangqi
Published: February 2024

The operating conditions of rolling bearings are complex and variable, and their vibration monitoring signals are filled with strong noise interference, resulting in a low accuracy in remaining useful life (RUL) prediction. For this issue, this paper proposes a denoising method with vibration fault signals modeling, and a novel RUL prediction method with Gate-convolutional neural networks (CNN) and Conv-Transformer encoder. Firstly, the theoretical fault signal is obtained through the vibration fault signal model, and the quality of the extracted features is improved by the wavelet threshold denoising algorithm in the process of feature extraction and selection. Moreover, the CNN is combined with the gating mechanism to construct a feature extractor with the feature evaluation function, and the convolution layers are introduced into the transformer to expand the encoder’s ability to explore local information in temporal data. By using fixed-time step temporal features as the input to the prediction module and minimizing the Huber function as the optimization objective, the relationship between temporal features and RUL is obtained. The comparison with the existing state-of-the-art RUL methods illustrates that the combination of gate control and convolutional structure proposed in this paper can not only reduce the prediction error of the model but also improve its generalization ability and robustness.
Machine learning classification of metallic objects using pulse induction electromagnetic data
Authors: Thomas Ryan , Salmon Brian , Holloway Damien , Olivier Jan
Published: February 2024

This paper presents the classification of metallic objects using total and scattered pulse induction electromagnetic data, with a classification accuracy greater than 90%. Machine learning classification is applied to raw electromagnetic induction (EMI) data without the use of a physics-based model. The EMI method is applied to 8 metallic objects placed at increasing distances from 10–55 mm to the EMI sensing system. The EMI sensing system consists of two RL circuits placed in close proximity. Metallic objects are classified using linear algorithms including a perceptron and multiclass logistic regression, and nonlinear algorithms including a neural network, a 1D and 2D convolutional neural network (CNN). EMI data was collected using an experiment in an electromagnetically shielded laboratory. Feature maps are presented that explain the salient components of the EMI data used by the 1D and 2D CNN.
Superficial white matter microstructural imaging method based on time-space fractional-order diffusion
Authors: He Jianglin , Wang Yuanjun
Published: February 2024

Objective. Microstructure imaging based on diffusion magnetic resonance signal is an advanced imaging technique that enables in vivo mapping of the brain’s microstructure. Superficial white matter (SWM) plays an important role in brain development, maturation, and aging, while fewer microstructure imaging methods address the SWM due to its complexity. Therefore, this study aims to develop a diffusion propagation model to investigate the microstructural characteristics of the SWM region. Approach. In this paper, we hypothesize that the effect of cell membrane permeability and the water exchange between soma and dendrites cannot be neglected for typical clinical diffusion times (20 ms < t < 80 ms). We then use SpinDoctor to simulate the diffusion magnetic resonance signals of real neurons and propose a time-space fractional-order diffusion model for SWM microstructure imaging. We evaluate the validity regime of our model using numerical simulations and compare the model parameters with several state-of-the-art methods. Main results. By analyzing the simulation signals of real neuronal cells as well as diffusion magnetic resonance data from the brains of fourteen healthy human subjects, we find that the time-space fractional-order diffusion model can be used to capture the structural complexity of the tissue, indirectly through the association of time fractional exponents with restricted diffusion and space fractional exponents with perfusion and membrane permeability. Significance. The results show that the diffusion propagation model can provide new insights into the tissue architecture of the SWM.
New optically stimulated luminescence dosimetry film optimized for energy dependence guided by Monte Carlo simulations
Authors: De Saint-Hubert Marijke , Caprioli Marco , de Freitas Nascimento Luana , Delombaerde Laurence , Himschoot Katleen , Vandenbroucke Dirk , Leblans Paul , Crijns Wouter
Published: February 2024

Optically stimulated luminescence (OSL) film dosimeters, based on BaFBr:Eu2+ phosphor material, have major dosimetric advantages such as dose linearity, high spatial resolution, film re-usability, and immediate film readout. However, they exhibit an energy-dependent over-response at low photon energies because they are not made of tissue-equivalent materials. In this work, the OSL energy-dependent response was optimized by lowering the phosphor grain size and seeking an optimal choice of phosphor concentration and film thickness to achieve sufficient signal sensitivity. This optimization process combines measurement-based assessments of energy response in narrow x-ray beams with various energy response calculation methods applied to different film metrics. Theoretical approaches and MC dose simulations were used for homogeneous phosphor distributions and for isolated phosphor grains of different dimensions, where the dose in the phosphor grain was calculated. In total 8 OSL films were manufactured with different BaFBr:Eu2+ median particle diameters (D50): 3.2 μm, 1.5 μm and 230 nm and different phosphor concentrations (1.6%, 5.3% and 21.3 %) and thicknesses (from 5.2 to 49 μm). Films were irradiated in narrow x-ray spectra (N60, N80, N-150 and N-300) and the signal intensity relative to the nominal dose-to-water value was normalized to Co-60. Finally, we experimentally tested the response of several films in Varian 6MV TrueBeam STx linear accelerator using the following settings: 10 × 10 cm2 field, 0deggantry angle, 90 cm SSD, 10 cm depth. The x-ray irradiation experiment reported a reduced energy response for the smallest grain size with an inverse correlation between response and grain size. The N-60 irradiation showed a 43% reduction in the energy over-response when going from 3 μm to 230 nm grain size for the 5% phosphor concentration. Energy response calculation using a homogeneous dispersion of the phosphor underestimated the experimental response and was not able to obtain the experimental correlation between grain size and energy response. Isolated grain size modeling combined with MC dose simulations allowed to establish a good agreement with experimental data, and enabled steering the production of optimized OSL-films. The clinical 6 MV beam test confirmed a reduction in energy dependence, which is visible in small-grain films where a decrease in out-of-field over-response was observed.
Micro-discharge in tortuous pores: ‘splitting-quenching’ of primary ionization wave and the role of pre-ionization
Authors: Peng Dingyuan , Duan Jialu , Li Lan , Zhang Ruobing
Published: February 2024

Porous discharge has been widely studied recent years, however the discharge development inside the pores with complicated structure was little involved. In this paper, the discharge developments in vertical and tortuous pore are studied using a 2D fluid model in Cartesian coordinate system established by COMSOL Multiphysics. The discharge develops symmetrically and bilaterally in vertical pore, and along the higher potential sidewall in tortuous pore, respectively. For tortuous pore, there are two pre-ionization process with negative and positive polarity successively, the latter one splits off from the former one and is in the form of multiple ionizing heads propagating simultaneously in string. The negative one can induce the primary discharge to deflect at the channel elbow joint in a ‘splitting-quenching’ way or directly deflect it by bridging with it. For the positive one, the multiple ionizing heads can distort the electric field and short cut the potential and thus accelerate the primary discharge. Furthermore, the discharge can be enhanced deep inside the tortuous pore by the large number of seed electrons provided by pre-ionization. The influence of the dielectric constant is also studied, with the dielectric constant increases, the discharge can maintain bilateral morphology in tortuous pores for a deeper development distance.
Efficiency of the non-maximally entangled quantum Otto engine
Authors: Sukamto Heru , Yuwana Lila , Purwanto Agus , Muniandy Sithi V
Published: February 2024

We generalized the maximally entangled Hamiltonian of the isotropic Heisenberg XX model with two spin-1/2 particles to the case of non-maximal entanglement parametrized by the degree of non-maximality 0 < n < 1. The thermal concurrence as the function of the degree of non-maximality in the entanglement at different values of the exchange parameter is calculated. We analyzed the efficiency of the quantum Otto engine for different scenarios of exchange parameter regimes and the degree of maximal entanglement between the spin states. We showed that it is possible to run the quantum Otto engine using non-maximally entangled states and achieve higher efficiencies by controlling the exchange parameter value with respect to a critical value J

c
and this feature also depends on the degree of non-maximal entanglement n ≠ 1. This result may be useful for harnessing the non-maximal entanglement in quantum heat engine for optimizing the operation of quantum devices interacting with heat bath or environment.
Various nonlinear characteristics of breather/rogue waves and controllable interaction phenomena for a new KdV equation with variable coeffcients
Authors: Lv Na , Yue Yichao , Zhang Runfa , Yuan Xuegang , Sun Jiaping
Published: February 2024

In this paper, we investigate and analyze various nonlinear phenomena of a new (2+1)-dimensional KdV equation with variable coefficients, and successfully obtain breather/rogue wave solutions and interaction solutions of the KdV equation by using the bilinear neural network method and symmetry transformation. Subsequently, we analyze the dynamical characteristics and evolution process of these obtained solutions through the 3-D animations, and find a series of interesting nonlinear phenomena concerning breather/rogue waves, such as fission, regeneration, annihilation, collision, and controllable interaction phenomena on nonzero backgrounds. This paper provides a more intuitive understanding for the nonlinear phenomena of these obtained solutions, and these nonlinear phenomena have potential application value in fluid dynamics, elastic mechanics and other fields of nonlinear science.
Lossless Compression Method for the Magnetic and Helioseismic Imager (MHI) Payload
Authors: Tong Li-Yue , Lin Jia-Ben , Deng Yuan-Yong , Ji Kai-Fan , Hou Jun-Feng , Wang Quan , Yang Xiao
Published: February 2024

The Solar Polar-orbit Observatory (SPO), proposed by Chinese scientists, is designed to observe the solar polar regions in an unprecedented way with a spacecraft traveling in a large solar inclination angle and a small ellipticity. However, one of the most significant challenges lies in ultra-long-distance data transmission, particularly for the Magnetic and Helioseismic Imager (MHI), which is the most important payload and generates the largest volume of data in SPO. In this paper, we propose a tailored lossless data compression method based on the measurement mode and characteristics of MHI data. The background out of the solar disk is removed to decrease the pixel number of an image under compression. Multiple predictive coding methods are combined to eliminate the redundancy utilizing the correlation (space, spectrum, and polarization) in data set, improving the compression ratio. Experimental results demonstrate that our method achieves an average compression ratio of 3.67. The compression time is also less than the general observation period. The method exhibits strong feasibility and can be easily adapted to MHI.
Investigating the role of edge neutrals in exciting tearing mode activity and achieving flat temperature profiles in LTX-β
Authors: Banerjee Santanu , Boyle D.P. , Maan A. , Ferraro N. , Wilkie G. , Majeski R. , Podesta M. , Bell R. , Hansen C. , Capecchi W. , Elliott D.
Published: February 2024

We present observations, numerical simulations, and analysis from experiments in the Lithium Tokamak Experiment-Beta (LTX-β) in which the electron temperature profile (Te
(r)) shifts from flat to peaked and a tearing mode is also destabilized when the average density (ne
ave
) exceeds ∼1019 m−3. Flat Te
(r) is obtained routinely in LTX-β, with a lithium coated, low-recycling first wall, once the external fueling is stopped and density decays [Boyle et al 2023 Nucl. Fusion 63 056020]. In the present experiment, flat Te
profiles can be sustained while maintaining constant ne
ave
below a line averaged density threshold (ne
ave
th
) of ∼1019 m−3. Above ne
ave
th, Te
(r) shifts from flat to peaked and a tearing mode is destabilized. Due to low recycling, the achieved ne
ave
can be controlled precisely by external fueling and hence, a certain threshold of the edge neutral inventory from the external fueling is experimentally manifested through ne
ave
th
. The goal of the present work is to investigate the role of edge neutrals in determining Te
(r) and MHD stability in the unique low-recycling regime of LTX-β. Our hypothesis is that the peaking of Te
(r) beyond ne
ave
th
is due ultimately to the edge cooling by the cold neutrals beyond a critical fueling flux. At lower fueling flux, flat Te
(r) results in broader pressure profile and lower resistivity, which in turn stabilizes the tearing mode. This hypothesis is supported by edge neutral density estimation by DEGAS 2 code. Mode analysis by singular value decomposition confirms the tearing mode structure to be m/n = 2/1 (m and n being the poloidal and toroidal mode numbers). Linear tearing stability analysis with M3D-C1 predicts that plasmas with ne
ave
> 1019 are highly susceptible to a n = 1 tearing mode. ORBIT simulations, however, confirmed that the tearing modes do not contribute to the loss of fast ions from neutral beam injection. This study shows for the first time that the neutral inventory at the edge could be one of the deciding factors for the achievability of the unique operation regime of flat Te
(r) and the excitation of tearing activity that could be disruptive for the plasmas.
Effect of resonant magnetic perturbation on edge–core turbulence spreading in a tokamak plasma
Authors: Ren Guangzhi , Wei Lai , Li Jiquan , Wang Zheng-Xiong
Published: February 2024

Turbulence spreading from the edge to the core region of a tokamak with a resonant magnetic perturbation (RMP) is investigated using an electromagnetic Landau-fluid model in a toroidal geometry. As a RMP field with an appropriate amplitude is applied, long-wavelength fluctuations around the resonance surface can be excited due to forced magnetic reconnection. Strong shear flow at the magnetic island separatrix is observed, which can break the radially elongated vortex structures of the turbulent fluctuation. Inward turbulence spreading can be blocked by this shear flow, and the saturation level of turbulence intensity in the core region declines.
Accelerating optical phased array calibration with improved SPGD algorithm
Authors: Shi Tao , Cheng Yu , Chen Jinhua , Du Xudong , Ji Chen
Published: February 2024

As a new type of beam pointing control technology, optical phased array has broad application prospects in the fields of laser radar and beam synthesis. However, the phase error in practical application brings great difficulties to beam detection and deflection, which must be calibrated. In this paper, a SPGD algorithm combined with Adam algorithm (ASPGD) is proposed and compared with the traditional optimization algorithm. The results show that the improved SPGD algorithm can double the convergence speed and increase the cosine similarity value by about 10%.
Correction of uneven illumination in microscopic image through robust brightness distribution estimation and deviation rectification
Authors: Ding Tao , Wu Kaijie , Cheng Hao , Gu Chaocheng
Published: February 2024

For diagnostic purposes, the automatic microscopic scanning system can scan and stitch multiple slide images together to produce a Whole Slide Image. This process provides a clear, high-resolution picture of the slide sample under the high-power objective lens of the microscope, enabling accurate diagnosis and analysis. However, uneven illumination affects every image acquired by a microscope, resulting in the existence of artifacts. In this paper, a novel retrospective approach based on robust brightness distribution estimation and deviation rectification is proposed. Least squares estimation and Cauchy estimation with a smooth regularization term are used to obtain the accurate estimation of background illumination distribution. Then the deviation map is given based on the deviation function of the two directions for illumination correction. This method leverages the statistical properties of image sequences to enhance stability and robustness against biological image artifacts. Through experimental validation, this approach successfully eliminates visible edge artifacts that commonly appear between neighboring tiles and exhibits superior performance when compared to other methods.
Improved monte Carlo ray-tracing algorithm based on importance sampling
Authors: Zhang Ningxuan , Huang Nuo , Gong Chen
Published: February 2024

This paper proposes an improved ray-tracing algorithm with importance sampling (IS) to reduce the computational complexity. For multiple receiver situation, we provide improved IS including adaptive and weighted optimization.
Prototype measurement results in a 65 nm technology and TCAD simulations towards more radiation tolerant monolithic pixel sensors
Authors: Lemoine C. , Aglieri Rinella G. , Baudot J. , Borghello G. , Carnesecchi F. , Hillemanns H. , Kluge A. , Kucharska G. , Leitao P.V. , Mager M. , Musa L. , Piro F. , Sanna I. , Snoeys W. , Šuljić M.
Published: February 2024

Early measurements on monolithic pixel sensor prototypes in the TPSCo 65 nm technology indicate a different response and radiation tolerance (up to
5×1015 1 MeV neq cm) for different sensor layout and process variants, illustrating the importance of layout and process in the path towards increased sensor radiation tolerance. Using these measurement results, TCAD simulations provide more insight to link the macroscopic behaviour of specific sensor variants to the details of its structure. With this insight we can propose a new variant combining the advantages of several measured variants as a path to even better radiation tolerance for the next iteration.
Prototype design of a Monolithic Active Pixel Sensor for the Electron-ion collider in China
Authors: He R. , Huang J. , Yin R. , Zhou W. , Niu X. , Han W. , Wang Q. , Yang H. , Yuan H. , Zou C. , Tian Y. , Liao S. , Zhang H. , Li X. , Liao J. , Zhao C.
Published: February 2024

The Nupix-R1 is a prototype Monolithic Active Pixel Sensor designed for the Electron-ion collider in China. It consists of 128 rows × 128 columns of square pixels with a pitch of 26.3 µm. Since it is implemented in a 130 nm commercial triple-well process, the in-pixel circuit contains only NMOS transistors. The Nupix-R1 can simultaneously measure the energy, arrival time and position of particle hits. In addition, it can also record only the hit positions with a novel zero-compression scheme to increase the readout speed and reduce the data volume. This paper will discuss the design of the Nupix-R1 sensor.
First measurements with a new β-electron detector for spectral shape studies
Authors: Guadilla V. , Algora A. , Estienne M. , Fallot M. , Gelletly W. , Porta A. , Rigalleau L.-M. , Stutzmann J.-S.
Published: February 2024

The shape of the electron spectrum emitted in β decay
carries a wealth of information about nuclear structure and
fundamental physics. In spite of that, few dedicated measurements
have been made of β-spectrum shapes. In this work we present a
newly developed detector for β electrons based on a telescope
concept. A thick plastic scintillator is employed in coincidence
with a thin silicon detector. The first measurements employing this
detector have been carried out with mono-energetic electrons from
the high-energy resolution electron-beam spectrometer at
Bordeaux. Here we report on the good reproduction of the
experimental spectra of mono-energetic electrons using Monte Carlo
simulations. This is a crucial step for future experiments, where a
detailed Monte Carlo characterization of the detector is needed to
determine the shape of the β-electron spectra by deconvolution
of the measured spectra with the response function of the
detector. A chamber to contain two telescope assemblies has been
designed for future β-decay experiments at the Ion Guide
Isotope Separator On-Line facility in Jyväskylä, aimed at
improving our understanding of reactor antineutrino spectra.
Characterisation of a high granularity multi-channel prompt γ-ray detection system prototype for proton range verification based on the PETsys TOFPET2 ASIC
Authors: Novgorodova O. , Glatte A. , Hentges R. , Kögler T. , Lutz B. , Roemer K. , Teichmann T. , Weinberger D. , Straessner A.
Published: February 2024

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

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

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

G

(
2
)

correlation times

τ
c

∼
10
−
30

fs and pair generation rates in the range

10
4

−

10

10

s

−
1

m
W

−
1

m
m

−
1

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

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

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

Background

Sleep, sedentary behavior, and physical activity have fundamental impacts on health and well-being. Little is known about how these behaviors vary across the year.

Purpose

To investigate how movement-related behaviors change across days of the week and seasons, and describe movement patterns across a full year and around specific temporal events.

Methods

This cohort study included 368 adults (mean age = 40.2 years [SD = 5.9]) who wore Fitbit activity trackers for 12 months to collect minute-by-minute data on sleep, sedentary behavior, light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA). Data were analyzed descriptively, as well as through multilevel mixed-effects linear regression to explore associations with specific temporal cycles (day-of-the-week, season) and events.

Results

Movement patterns varied significantly by day-of-the-week and season, as well as during annual events like Christmas-New Year and daylight saving time (DST) transitions. For example, sleep was longer on weekends (+32 min/day), during autumn and winter relative to summer (+4 and +11 min/day), and over Christmas-New Year (+24 min/day). Sedentary behavior was longer on weekdays, during winter, after Christmas-New Year, and after DST ended (+45, +7, +12, and +8 min/day, respectively). LPA was shorter in autumn, winter, and during and after Christmas-New Year (−6, −15, −17, and −31 min/day, respectively). Finally, there was less MVPA on weekdays and during winter (−5 min/day and −2 min/day, respectively).

Conclusions

Across the year, there were notable variations in movement behaviors. Identifying high-risk periods for unfavorable behavior changes may inform time-targeted interventions and health messaging.
Pharmacist perspectives on emerging T cell–engaging bispecific therapies in cancer therapeutics
Authors: Moore Donald C , Digiantonio Naomi , Oxencis Carolyn J , Taucher Kate D
Published: February 2024

Purpose

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

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

Conclusion

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

Objective

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

Methods

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

Results

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

Conclusions

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

Motivation

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

Results

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

Availability

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

Contact

dengmh@pku.edu.cn

Supplementary information

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

Proteins play an important role in life activities and are the basic units for performing functions. Accurately annotating functions to proteins is crucial for understanding the intricate mechanisms of life and developing effective treatments for complex diseases. Traditional biological experiments struggle to keep pace with the growing number of known proteins. With the development of high-throughput sequencing technology, a wide variety of biological data provides the possibility to accurately predict protein functions by computational methods. Consequently, many computational methods have been proposed. Due to the diversity of application scenarios, it is necessary to conduct a comprehensive evaluation of these computational methods to determine the suitability of each algorithm for specific cases. In this study, we present a comprehensive benchmark, BeProf, to process data and evaluate representative computational methods. We first collect the latest datasets and analyze the data characteristics. Then, we investigate and summarize 17 state-of-the-art computational methods. Finally, we propose a novel comprehensive evaluation metric, design eight application scenarios and evaluate the performance of existing methods on these scenarios. Based on the evaluation, we provide practical recommendations for different scenarios, enabling users to select the most suitable method for their specific needs. All of these servers can be obtained from https://csuligroup.com/BEPROF and https://github.com/CSUBioGroup/BEPROF.