bluuebunny/crossref_metadata_2025 huggingface dataset:
5 Diagnostic radiography and reach back capability in the remotely deployed environment; a summary from op newcombe rotation 3
Authors:   Sgt Jessica Bailey
Published: May 2023

Diagnostics remains to be an important and vital capability of any deployed field hospital or surgical team, particularly for teams that find themselves deployed in the most remote locations, such as Mali. The DRGo gives the British military a portable radiography solution. Completely digital, it provides an instantaneous X-ray for clinicians to review. A 6-month period between Dec 21 and Jun 22 saw 29 full X-ray examinations completed with a 50% split between those patients being referred for imaging in the firm base and those referred whilst out on patrol. With no deployed radiologists on the ground, the ability to obtain radiologist reports is pivotal to the patients’ subsequent treatment pathway. X-rays and CT scans were uploaded back to the Royal Centre for Defence Medicine for reporting through the help of Project Lara. Project Lara brings together several separate innovation capabilities to deliver a better improved telemedicine solution. It gives Defence Medical Services personnel the ability to request support or transfer medical information whilst deployed in the field via secure communication systems. The project utilises a SATCUBE satellite terminal, essentially a portable WiFi hotspot. When setup, it allows for a high-speed broadband connection of around 10mbps in less than a minute. Used in conjunction with the secure messaging app, Pando, complete radiologist reports were received back from the UK often in less than one hour of uploading the initial X-rays. A natural fit, the deployed Radiographer took on the role of the communications lead and demonstrated how well the two roles could combine in future remote Operations.
Four-point functions of gravitons and conserved currents of CFT in momentum space: testing the nonlocal action with the TTJJ
Authors: Corianò Claudio , Maglio Matteo Maria , Tommasi Riccardo
Published: May 2023

We present an analysis of the perturbative realization of the TTJJ correlator, with two stress energy tensors and two conserved currents, using free field theory, integrating out conformal sectors in the quantum corrections. This allows to define, around flat space, an exact perturbative expansion of the complete anomaly effective action – up to 4-point functions – whose predictions can be compared against those of the anomaly induced action. The latter is a variational solution of the conformal anomaly constraint at $$d=4$$

d
=
4

in the form of a nonlocal Wess–Zumino action. The renormalization procedure and the degeneracies of the tensor structures of this correlator are discussed, valid for a generic conformal field theory, deriving its anomalous trace Ward identities (WIs). In this application, we also illustrate a general procedure that identifies the minimal number of tensorial structures and corresponding form factors for the TTJJ and any 4-point function. The approach is implemented for three, four and five dimensions, addressing the tensor degeneracies of the expansion in momentum space. We show that the renormalized TTJJ can be split into two contributions, a non anomalous and an anomalous part, each separately conserved. The first satisfies ordinary trace WIs, while the second satisfies anomalous trace WIs. The result of the direct computation is compared against the expression of the same 4-point function derived from the nonlocal anomaly induced action. We show that the prediction for the anomalous part of the TTJJ derived from such action, evaluated in two different conformal decompositions, the Riegert and Fradkin–Vilkovisky (FV) choices, differ from the anomaly part identified in the perturbative TTJJ, in the flat spacetime limit. The anomaly part of the correlator computed with the Riegert choice is affected by double poles, while the one computed with the FV choice does not satisfy the conservation WIs. We present the correct form of the expansion of the anomaly induced action at the second order in the metric perturbations around flat space that reproduces the perturbative result.
Nonlinearity effect on Joule–Thomson expansion of Einstein–Power–Yang–Mills AdS black hole
Authors: Du Yun-Zhi , Liu Xiao-Yang , Zhang Yang , Zhao Li , Gu Qiang
Published: May 2023

Considering the nonlinearity of the Yang Mills charge, we investigate the Joule–Thomson expansion for the Einstein–Power–Yang–Mills AdS black holes in the context of the gauge-gravity duality. Under this framework, we calculate the Joule–Thomson coefficient, describe all relevant inversion and isenthalpic curves in the temperature-pressure plane that determining in this manner the corresponding cooling and heating regions. Finally we analyze the effect of the charge nonlinearity on the Joule–Thomson expansion.
Sterile neutrino portal dark matter in $$\nu $$THDM
Authors: Liu Ang , Shao Feng-Lan , Han Zhi-Long , Jin Yi , Li Honglei
Published: May 2023

In this paper, we propose the sterile neutrino portal dark matter in $$\nu $$
ν
THDM. This model can naturally generate tiny neutrino mass with the neutrinophilic scalar doublet $$\Phi _{\nu }$$

Φ
ν

and sterile neutrinos N around TeV scale. Charged under a $$Z_2$$

Z
2

symmetry, one Dirac fermion singlet $$\chi $$
χ
and one scalar singlet $$\phi $$
ϕ
are further introduced in the dark sector. The sterile neutrinos N are the mediators between the DM and SM. Depending on the coupling strength, the DM can be either WIMP or FIMP. For the WIMP scenario, pair annihilation of DM into NN is the key channel to satisfy various bounds, which could be tested at indirect detection experiments. For the FIMP scenario, besides the direct production of DM from freeze-in mechanism, contributions from late decay of NLOP is also important. When sterile neutrinos are heavier than the dark sector, NLOP is long-lived due to tiny mixing angle between sterile and light neutrinos. Constrains from free-streaming length, CMB, BBN and neutrino experiments are considered.
Reflecting the past, imag(in)ing the past: macro-reflection imaging of painting materials by fast MIR hyperspectral analysis
Authors: Botticelli Michela , Risdonne Valentina , Visser Tess , Young Christina , Smith Margaret J. , Charsley Jake M. , Rutkauskas Marius , Altmann Yoann , Reid Derryck T.
Published: May 2023

Imaging spectroscopy has been developed in the last two decades in the visible and infrared spectral range for detecting pigments and binders on paintings. The near-infrared (NIR) region has been proved effective for the discrimination of lipids and proteinaceous binders. More recently, the mid-infrared (MIR) range has also been tested on paintings. Reflection imaging prototypes already developed could be further optimized for cultural heritage analysis, for example by: enhancing the instrument configuration and performance; adopting compressive strategies to increase data processing speeds; using data validation to confirm that the processed image reflects the composition of a painted surface; and lowering price to enable more cost-effective analysis of large surface areas. Here, we demonstrate a novel hyperspectral Fourier transform spectrometer (HS FTS), which enables an imaging strategy that provides a significant improvement in acquisition rate compared to other state-of-the-art techniques. We demonstrate hyperspectral imaging across the 1400–700 cm−1region in reflection mode with test samples and the painting ‘Uplands in Lorne’ (Acc. No.: GLAHA43427) by D.Y. Cameron (1865–1945). A post-processing analysis of the resulting hyperspectral images, after validation of reference samples by conventional Fourier transform infrared spectroscopy, shows the potential of the method for efficient non-destructive classification of different materials found on painted cultural heritage. This research demonstrates that the HS FTS is a convenient and compact tool for non-invasive analysis of painted cultural heritage objects at spatio-spectral acquisition rates potentially higher than current FTS imaging techniques. Ultimately, when combined with fast graphics processing unit-based reconstruction, the HS FTS may enable fast, large area imaging.

Graphical abstract
INVESTIGATION OF THE FRACTIONAL KdV–ZAKHAROV–KUZNETSOV EQUATION ARISING IN PLASMA PHYSICS
Authors: WANG KANG-LE
Published: May 2023

The KdV–Zakharov–Kuznetsov equation is an important and interesting mathematical model in plasma physics, which is used to describe the effect of magnetic field on weak nonlinear ion-acoustic waves. A fractional KdV–Zakharov–Kuznetsov equation in the [Formula: see text]-truncated derivative sense is investigated. By taking into account the fractional [Formula: see text] method and fractional [Formula: see text]–[Formula: see text] method, larger numbers of a new type of solitary wave solutions are obtained. The dynamic characteristics of these new solitary wave solutions are elaborated by sketching some three-dimensional (3D) and two-dimensional (2D) figures. The study reveals that the proposed two methods are very powerful to solve fractional evolution equations.
β-Pyrrole functionalized push-pull BODIPYs: Synthesis, photophysical, electrochemical, thermal and computational studies
Authors: Yadav Indresh Singh , Misra Rajneesh
Published: May 2023

A series of [Formula: see text]-pyrrole functionalized push-pull BODIPYs BDP 1-06 were designed and synthesized via Palladium-catalyzed Suzuki cross-coupling reaction and by increasing the oxidation state of the sulfur atom in the thiazine ring. The effect of various donor entities on the photophysical, electrochemical, thermal, and computational studies of the BODIPY was investigated. The absorption spectra of the push-pull BODIPY BDP 2 show a red shift compared to the rest of the BDPs, due to strong donor-acceptor interaction. The phenothiazine-5,5-dioxide functionalized BODIPY BDP 6 exhibit a blue shift in the UV-vis region compared to the phenothiazine substituted BODIPY BDP 5 due to the weak donor ability of the phenothiazine-5,5-dioxide unit. The electrochemical studies were performed for the push-pull BODIPYs BDP 1–6 to analyze the effect of different donor groups on the redox properties of the BODIPY. The thermogravimetric analysis of the BODIPYs BDP 1–6 shows that BDP 2 exhibits excellent thermal stability compared to BDP 1, 3, 4, 5, and 6. The theoretical studies reveal that the phenothiazine-5,5-dioxide substituted BODIPY BDP 6 exhibits a large HOMO–LUMO gap compared to phenothiazine functionalized BODIPY BDP 5 due to the low donor ability of the phenothiazine-5,5-dioxide unit. The theoretical calculations were consistent with the experimental observations.
Synthesis, dark and photoinduced cytotoxicity of a deuteroporphyrin IX derivative with two galactose fragments on the macrocycle periphery
Authors: Rocheva Tatyana K. , Belykh Elena S. , Mal’shakova Marina V. , Pylina Yana I. , Belykh Dmitry V.
Published: May 2023

A deuteroporphyrin IX derivative with two D-galactose fragments with an ester bond between macrocycle and carbohydrate fragments was synthesized. The synthesis was done by esterifying both ester groups of deuteroporphyrin IX with diacetone-D-galactose using 2-chloro-1-methylpyridinium iodide (Mukayama reagent) followed by the removal of the isopropylidene protection of carbohydrate fragments by the action of aqueous trifluoroacetic acid to form the target derivative. The study of dark toxicity of the deuteroporphyrin IX derivative synthesized against HeLa cells allows us to conclude that galactose fragment introduction resulted in the cytotoxicity decrease as compared with the parent deuteroporphyrin IX but photoinduced cytotoxicity of the deuteroporphyrin IX derivative with two D-galactose fragments had increased in contrast to the deuteroporphyrin IX. It has been shown that oxidative stress due to ROS induction causes the photoinduced toxicity of the porphyrins studied.
Faster optimal ate pairings for cyclotomic sparse families of pairing-friendly elliptic curves with embedding degrees k = 5,7
Authors: Nyamsi Senegue Gomez , Fouotsa Emmanuel , Tcheka Calvin
Published: May 2023

Nowadays, pairing-based cryptography researchers are looking for new parameters for standard security levels against the new number field sieve tower number field sieve algorithm. Recently, they have suggested new parameters for well-studied pairing-friendly curves with odd embedding degrees five and seven resistant to this attack. In this paper, we define optimal ate pairing on curves using sparse families with embedding degrees five and seven. We also provide details to perform the miller loop and the final exponentiation using addition chain process. Our theoretical results costs indicate that these families of curves offer the best performance in the computation of the optimal ate pairing at the 128-bit security level compared to Cocks–Pinch curves of embedding degrees five and seven. The improvement is about [Formula: see text] and [Formula: see text] faster than the optimal ate pairing previously computed on Cocks–Pinch curves of embedding degrees five and seven, respectively.
Combined use of multiple external and internal standards in LA-ICP-MS analysis of bulk geological samples using lithium borate fused glass
Authors: Conrey Richard M. , Bailey David G. , Singer Jared W. , Wagoner Laureen J. , Parfitt Benjamin , Hay John , Keh Oliver , Chang Zhaoshan , Huang Shiqiang
Published: May 2023

We describe a method for laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) elemental analysis of geological materials using low-dilution Li-borate fused glass wavelength dispersive X-ray fluorescence (WDXRF) pellets, with samples, drift monitor and 18 reference materials (RMs) identically prepared. After analysis for 46 elements by WDXRF, LA-ICP-MS intensities from samples and RMs are collected, and background corrected with
Iolite
software.
HALite
, a new software application, was developed to derive the elemental compositions from the LA-ICP-MS net signals. In
HALite
, elements are drift-corrected using polynomial functions, and flux-fused RM element sensitivities are calculated from known mass fractions. Multiple internal standard (IS) elements are used to model each sample's laser response. Analyte mass fractions in unknowns are determined using the calibrated sensitivity correlation models for multiple IS elements. Either the WDXRF mass fractions or the initial round of calculated LA-ICP-MS mass fractions are used to calculate weighted mean sensitivities. Validation experiments with flux-fused RMs run as unknowns yield results with less than 5–10% total relative uncertainty for most analytes. We derive equations which allow calculation of the precision and total uncertainty as a function of mass fraction for each analyte element.

Supplementary material
: Table 1 - RMs used; Table 2 - Operating parameters; Table 3 - Model v. accepted mass fractions; Table 4 - NIST 610 v. multiple IS models; Table 5 - Fitting parameters; Appendix 1 - HALite description; Appendix A - Summary calibration graphs; Appendix B - Validation results; Appendix C - WDXRF comparisons; Appendix D - Repeatability uncertainties; Appendix E - RM uncertainties; and Appendix F - Total uncertainties for this article are available at
https://doi.org/10.6084/m9.figshare.c.6639885
POMACS V7, N2, June 2023 Editorial
Authors: Avrachenkov Konstantin , Gill Phillipa , Urgaonkar Bhuvan
Published: May 2023

The Proceedings of the ACM on Measurement and Analysis of Computing Systems (POMACS) focuses on the measurement and performance evaluation of computer systems and operates in close collaboration with the ACM Special Interest Group SIGMETRICS. All papers in this issue of POMACS will be presented at the ACM SIGMETRICS 2023 conference on June 19-23, 2023, in Orlando, Florida, USA. These papers have been selected during the winter submission round by the 91 members of the ACM SIGMETRICS 2023 program committee via a rigorous review process. Each paper was conditionally accepted (and shepherded), allowed a "one-shot" revision (to be resubmitted to one of the subsequent three SIGMETRICS deadlines), or rejected (with re-submission allowed after a year). For this issue, which represents the winter deadline, POMACS is publishing 11 papers out of 130 submissions. All submissions received at least 3 reviews and borderline cases were extensively discussed during the online program committee meeting.

Based on the indicated track(s), roughly 28% of the submissions were in the Theory track, 44% were in the Measurement & Applied Modeling track, 43% were in the Systems track, and 22% were in the Learning track. Many individuals contributed to the success of this issue of POMACS. First, we would like to thank the authors, who submitted their best work to SIGMETRICS/POMACS. Second, we would like to thank the program committee members who provided constructive feedback in their reviews to authors and participated in the online discussions and program committee meeting. We also thank the several external reviewers who provided their expert opinion on specific submissions that required additional input. We are also grateful to the SIGMETRICS Board Chair, Giuliano Casale, and to past program committee Chairs, Niklas Carlsson, Edith Cohen, and Philippe Robert, who provided a wealth of information and guidance. Finally, we are grateful to the Organization Committee and to the SIGMETRICS Board for their ongoing efforts and initiatives for creating an exciting program for ACM SIGMETRICS 2023.
Overcoming the Long Horizon Barrier for Sample-Efficient Reinforcement Learning with Latent Low-Rank Structure
Authors: Sam Tyler , Chen Yudong , Yu Christina Lee
Published: May 2023

The practicality of reinforcement learning algorithms has been limited due to poor scaling with respect to the problem size, as the sample complexity of learning an ε-optimal policy is Ω(|S||A|H/ ε2) over worst case instances of an MDP with state space S, action space A, and horizon H. We consider a class of MDPs for which the associated optimal Q* function is low rank, where the latent features are unknown. While one would hope to achieve linear sample complexity in |S| and |A| due to the low rank structure, we show that without imposing further assumptions beyond low rank of Q*, if one is constrained to estimate the Q function using only observations from a subset of entries, there is a worst case instance in which one must incur a sample complexity exponential in the horizon H to learn a near optimal policy. We subsequently show that under stronger low rank structural assumptions, given access to a generative model, Low Rank Monte Carlo Policy Iteration (LR-MCPI) and Low Rank Empirical Value Iteration (LR-EVI) achieve the desired sample complexity of Õ((|S|+|A|)poly (d,H)/ε2) for a rank d setting, which is minimax optimal with respect to the scaling of |S|, |A|, and ε. In contrast to literature on linear and low-rank MDPs, we do not require a known feature mapping, our algorithm is computationally simple, and our results hold for long time horizons. Our results provide insights on the minimal low-rank structural assumptions required on the MDP with respect to the transition kernel versus the optimal action-value function.
CoBF: Coordinated Beamforming in Dense mmWave Networks
Authors: Zhang Ding , Santhalingam Panneer Selvam , Pathak Parth , Zheng Zizhan
Published: May 2023

With MIMO and enhanced beamforming features, IEEE 802.11ay is poised to create the next generation of mmWave WLANs that can provide over 100 Gbps data rate. However, beamforming between densely deployed APs and clients incurs unacceptable overhead. On the other hand, the absence of up-to-date beamforming information restricts the diversity gains available through MIMO and multi-users, reducing the overall network capacity. This paper presents a novel approach of "coordinated beamforming" (called CoBF) where only a small subset of APs are selected for beamforming in the 802.11ay mmWave WLANs. Based on the concept of uncertainty, CoBF predicts the APs whose beamforming information is likely outdated and needs updating. The proposed approach complements the existing per-link beamforming solutions and extends their effectiveness from link-level to network-level. Furthermore, CoBF leverages the AP uncertainty to create MU-MIMO groups through interference-aware scheduling in 802.11ay WLANs. With extensive experimentation and simulations, we show that CoBF can significantly reduce beamforming overhead and improve network capacity for 802.11ay WLANs.
Towards Accelerating Data Intensive Application's Shuffle Process Using SmartNICs
Authors: Lin Jiaxin , Ji Tao , Hao Xiangpeng , Cha Hokeun , Le Yanfang , Yu Xiangyao , Akella Aditya
Published: May 2023

The wide adoption of the emerging SmartNIC technology creates new opportunities to offload application-level computation into the networking layer, which frees the burden of host CPUs, leading to performance improvement. Shuffle, the all-to-all data exchange process, is a critical building block for network communication in distributed data-intensive applications and can potentially benefit from SmartNICs.

In this paper, we develop SmartShuffle, which accelerates the data-intensive application's shuffle process by offloading various computation tasks into the SmartNIC devices. SmartShuffle supports offloading both low-level network functions, including data partitioning and network transport, and high-level computation tasks, including filtering, aggregation, and sorting. SmartShuffle adopts a coordinated offload architecture to make sender-side and receiver-side SmartNICs jointly contribute to the benefits of shuffle computation offload. SmartShuffle carefully manages the tight and time-varying computation and memory constraints on the device. We propose a liquid offloading approach, which dynamically migrates operators between the host CPU and the SmartNIC at runtime such that resources in both devices are fully utilized.

We prototype SmartShuffle on the Stingray SoC SmartNICs and plug it into Spark. Our evaluation shows that SmartShuffle improves host CPU efficiency and I/O efficiency with lower job completion time. SmartShuffle outperforms Spark, and Spark RDMA by up to 40% on TPC-H.
An FPGA Accelerator for Genome Variant Calling
Authors: Xu Tiancheng , Rixner Scott , Cox Alan L.
Published: May 2023

In genome analysis, it is often important to identify variants from a reference genome. However, identifying variants that occur with low frequency can be challenging, as it is computationally intensive to do so accurately. LoFreq is a widely used program that is adept at identifying low-frequency variants. This article presents a design framework for an FPGA-based accelerator for LoFreq. In particular, this accelerator is targeted at virus analysis, which is particularly challenging, compared to human genome analysis, as the characteristics of the data to be analyzed are fundamentally different. Across the design space, this accelerator can achieve up to 120× speedups on the core computation of LoFreq and speedups of up to 51.7× across the entire program.
How Many Crowd Workers Do I Need? On Statistical Power when Crowdsourcing Relevance Judgments
Authors: Roitero Kevin , Barbera David La , Soprano Michael , Demartini Gianluca , Mizzaro Stefano , Sakai Tetsuya
Published: May 2023

To scale the size of Information Retrieval collections, crowdsourcing has become a common way to collect relevance judgments at scale. Crowdsourcing experiments usually employ 100–10,000 workers, but such a number is often decided in a heuristic way. The downside is that the resulting dataset does not have any guarantee of meeting predefined statistical requirements as, for example, have enough statistical power to be able to distinguish in a statistically significant way between the relevance of two documents.

We propose a methodology adapted from literature on sound topic set size design, based on t-test and ANOVA, which aims at guaranteeing the resulting dataset to meet a predefined set of statistical requirements. We validate our approach on several public datasets.

Our results show that we can reliably estimate the recommended number of workers needed to achieve statistical power, and that such estimation is dependent on the topic, while the effect of the relevance scale is limited. Furthermore, we found that such estimation is dependent on worker features such as agreement. Finally, we describe a set of practical estimation strategies that can be used to estimate the worker set size, and we also provide results on the estimation of document set sizes.
Semantic-Enriched Code Knowledge Graph to Reveal Unknowns in Smart Contract Code Reuse
Authors: Huang Qing , Liao Dianshu , Xing Zhenchang , Zuo Zhengkang , Wang Changjing , Xia Xin
Published: May 2023

Programmers who work with smart contract development often encounter challenges in reusing code from repositories. This is due to the presence of two unknowns that can lead to non-functional and functional failures. These unknowns are implicit collaborations between functions and subtle differences among similar functions. Current code mining methods can extract syntax and semantic knowledge (known knowledge), but they cannot uncover these unknowns due to a significant gap between the known and the unknown. To address this issue, we formulate knowledge acquisition as a knowledge deduction task and propose an analytic flow that uses the function clone as a bridge to gradually deduce the known knowledge into the problem-solving knowledge that can reveal the unknowns. This flow comprises five methods: clone detection, co-occurrence probability calculation, function usage frequency accumulation, description propagation, and control flow graph annotation. This provides a systematic and coherent approach to knowledge deduction. We then structure all of the knowledge into a semantic-enriched code Knowledge Graph (KG) and integrate this KG into two software engineering tasks: code recommendation and crowd-scaled coding practice checking. As a proof of concept, we apply our approach to 5,140 smart contract files available on Etherscan.io and confirm high accuracy of our KG construction steps. In our experiments, our code KG effectively improved code recommendation accuracy by 6% to 45%, increased diversity by 61% to 102%, and enhanced NDCG by 1% to 21%. Furthermore, compared to traditional analysis tools and the debugging-with-the-crowd method, our KG improved time efficiency by 30 to 380 seconds, vulnerability determination accuracy by 20% to 33%, and vulnerability fixing accuracy by 24% to 40% for novice developers who identified and fixed vulnerable smart contract functions.
CodeEditor
: Learning to Edit Source Code with Pre-trained Models
Authors: Li Jia , Li Ge , Li Zhuo , Jin Zhi , Hu Xing , Zhang Kechi , Fu Zhiyi
Published: May 2023

Developers often perform repetitive code editing activities (up to 70%) for various reasons (e.g., code refactoring) during software development. Many deep learning (DL) models have been proposed to automate code editing by learning from the code editing history. Among DL-based models, pre-trained code editing models have achieved the state-of-the-art (SOTA) results. Pre-trained models are first pre-trained with pre-training tasks and fine-tuned with the code editing task. Existing pre-training tasks mainly are code infilling tasks (e.g., masked language modeling), which are derived from the natural language processing field and are not designed for automatic code editing.

In this article, we propose a novel pre-training task specialized in code editing and present an effective pre-trained code editing model named
CodeEditor
. Compared to previous code infilling tasks, our pre-training task further improves the performance and generalization ability of code editing models. Specifically, we collect lots of real-world code snippets as the ground truth and use a powerful generator to rewrite them into mutated versions. Then, we pre-train our
CodeEditor
to edit mutated versions into the corresponding ground truth, to learn edit patterns. We conduct experiments on four code editing datasets and evaluate the pre-trained
CodeEditor
in three settings (i.e., fine-tuning, few-shot, and zero-shot). (1) In the fine-tuning setting, we train the pre-trained
CodeEditor
with four datasets and evaluate it on the test data.
CodeEditor
outperforms the SOTA baselines by 15%, 25.5%, 9.4%, and 26.6% on four datasets. (2) In the few-shot setting, we train the pre-trained
CodeEditor
with limited data and evaluate it on the test data.
CodeEditor
substantially performs better than all baselines, even outperforming baselines that are fine-tuned with all data. (3) In the zero-shot setting, we evaluate the pre-trained
CodeEditor
on the test data without training.
CodeEditor
correctly edits 1,113 programs, while the SOTA baselines cannot work. The results show that the superiority of our pre-training task and the pre-trained
CodeEditor
is more effective in automatic code editing.
VIPS: Real-Time Perception Fusion for Infrastructure-Assisted Autonomous Driving
Authors: Shi Shuyao , Cui Jiahe , Jiang Zhehao , Yan Zhenyu , Xing Guoliang , Jianwei Niu , Zhenchao Ouyang
Published: May 2023

Infrastructure-assisted autonomous driving is an emerging paradigm that expects to significantly improve the driving safety of autonomous vehicles. The key enabling technology for this vision is to fuse LiDAR results from the roadside infrastructure and the vehicle to improve the vehicle's perception in real time. In this work, we propose VIPS, a novel lightweight system that can achieve decimeter-level and real-time (up to 100ms) perception fusion between driving vehicles and roadside infrastructure. The key idea of VIPS is to exploit highly efficient matching of graph structures that encode objects' lean representations as well as their relationships, such as locations, semantics, sizes, and spatial distribution. Moreover, by leveraging the tracked motion trajectories, VIPS can maintain the spatial and temporal consistency of the scene, which effectively mitigates the impact of asynchronous data frames and unpredictable communication/ compute delays.
Electrochemical Oxide Growth on Nickel and Commercial Nickel Alloys: Influence of Chromium and Molybdenum
Authors: Kretzmer Isaac , Stuve Eric M.
Published: May 2023

Nickel-chromium-molybdenum (NiCrMo) alloys are well-known for having exceptional corrosion resistance, but their electrocatalytic properties have not been extensively studied. In this paper, the development of electro-active nickel-oxyhydroxide (NiOOH) phases and kinetics of the oxygen evolution reaction (OER) have been examined on alloys G35, B3, and C276 in alkaline electrolyte at 25 °C. Reproducible oxide layers were grown by potential cycling between 0.85 and 1.52 V vs RHE up to 600 cycles, and the transition between Ni(OH)2 and NiOOH was monitored by cyclic voltammetry throughout. Onset potentials, Tafel slopes, and turnover frequencies (TOF) were measured at OER overpotentials between 270 and 390 mV. Alloys with dissimilar Cr:Mo ratios had significantly higher electrochemical surface area and increased γ-NiOOH formation, suggesting higher metal dissolution rates. The equal Cr:Mo concentration alloy and pure Ni developed a primarily β-NiOOH surface, and had 1.8–2.0 times larger TOF values than those containing significant γ-NiOOH. The NiCrMo alloys required smaller overpotentials (54–80 mV) to produce 10 mA cm−2 of OER current, and had comparable Tafel slopes to pure Ni. The findings here indicate a β-NiOOH-developed surface to be more OER-active than a γ-NiOOH-developed surface, and suggest certain NiCrMo alloys have promise as OER electrocatalysts.
Electrodeposition of Niobium Coatings on the Cryogyroscope Rotor
Authors: Okunev M. A. , Dubrovskii A. R. , Kuznetsov S. A.
Published: May 2023

The discharge process of Nb(IV) complexes to Nb was studied by cyclic voltammetry. A galvanostatic electrolysis with the cathodic current density of 1.5·10−2 A cm−2 in the NaCl–KCl–NaF–K2NbF7 melt in contact with Nb anode was used for deposition of niobium coatings on the cryogyroscope rotor at temperature 1023 K, and time of process from 8 to 12 h. The coatings were continuous and smooth due to the special design of the cathode. The rotation speed of the stirrer was set to 35 rpm and did not change in all experiments. Such conditions made it possible to obtain coatings with the thickness up to 150 μm. The main characteristics of the niobium coatings such as purity, roughness, nonsphericity, and superconductivity were investigated.
Surface-Densified Non-Fluorinated Proton Exchange Membrane Used for Direct Methanol Fuel Cell
Authors: Li Zhen , Hao Xiaofeng , Xiao Min , Huang Sheng , Han Dongmei , Wang Shuanjin , Meng Yuezhong
Published: May 2023

Novel bifunctional polyhedral oligomeric silsesquioxane (Vi-POSS-SO3Na) and a surface densification method to fabricate the composite membrane based on sulfonated poly (fluorenyl etherketone) (SPFEK) was firstly reported for the application in direct methanol fuel cells (DMFCs). Firstly, the synthetic Vi-POSS-SO3Na implants on the SPFEK surface by swelling-filling process. Afterward, the vinyl groups on POSS are cross-linked to form a dense X-POSS layer on the membrane surface by a simply thermal treatment which is called surface densification. The crosslinked dense X-POSS with sulfonated groups on the composite membrane surface can effectively prevent the permeation of methanol and enhance the oxidative stability without the sacrificing proton conductivity. The SPFEK/POSS-0.09 membrane with an area loading of 0.09 mg cm−2 POSS exhibits enhanced oxidative stability and the lowest methanol permeability (2.12 × 10−8 cm2 s−1). Direct methanol fuel cell was assembled and its performance was evaluated. The peak power density using SPFEK/POSS-0.03 membrane reaches 65.1 mW cm−2 that is much higher than the one (24.8 mW cm−2) using pristine SPFEK membrane at 80 °C. The results demonstrate that the surface densification is an effective method to suppress methanol crossover and surface-densified SPFEK/POSS proton exchange membrane with X-POSS layer has improved the comprehensive performance of composite membrane.
Loss of hepatic PPARα in mice causes hypertension and cardiovascular disease
Authors: Badmus Olufunto O. , Kipp Zachary A. , Bates Evelyn A. , da Silva Alexandre A. , Taylor Lucy C. , Martinez Genesee J. , Lee Wang-Hsin , Creeden Justin F. , Hinds Terry D. , Stec David E.
Published: May 2023

The leading cause of death in patients with nonalcoholic fatty liver disease (NAFLD) is cardiovascular disease (CVD). However, the mechanisms are unknown. Mice deficient in hepatocyte proliferator-activated receptor-α (PPARα) ( PparaHepKO) exhibit hepatic steatosis on a regular chow diet, making them prone to manifesting NAFLD. We hypothesized that the PparaHepKO mice might be predisposed to poorer cardiovascular phenotypes due to increased liver fat content. Therefore, we used PparaHepKO and littermate control mice fed a regular chow diet to avoid complications with a high-fat diet, such as insulin resistance and increased adiposity. After 30 wk on a standard diet, male PparaHepKO mice exhibited elevated hepatic fat content compared with littermates as measured by Echo MRI (11.95 ± 1.4 vs. 3.74 ± 1.4%, P < 0.05), hepatic triglycerides (1.4 ± 0.10 vs. 0.3 ± 0.01 mM, P < 0.05), and Oil Red O staining, despite body weight, fasting blood glucose, and insulin levels being the same as controls. The PparaHepKO mice also displayed elevated mean arterial blood pressure (121 ± 4 vs. 108 ± 2 mmHg, P < 0.05), impaired diastolic function, cardiac remodeling, and enhanced vascular stiffness. To determine mechanisms controlling the increase in stiffness in the aorta, we used state-of-the-art PamGene technology to measure kinase activity in this tissue. Our data suggest that the loss of hepatic PPARα induces alterations in the aortas that reduce the kinase activity of tropomyosin receptor kinases and p70S6K kinase, which might contribute to the pathogenesis of NAFLD-induced CVD. These data indicate that hepatic PPARα protects the cardiovascular system through some as-of-yet undefined mechanism.
Facile Solvothermal Synthesis of NiO/g-C3N4 Nanocomposite for Enhanced Supercapacitor Application
Authors: Pai Shri Hari S. , Sasmal Ananta , Nayak Arpan Kumar , Han HyukSu
Published: May 2023

There is a desperate demand for efficient energy storage systems to fulfill future energy demands. Herein, we exemplify a facile solvothermal approach followed by heat treatment to synthesize NiO/g-C3N4 nanocomposites for enhanced supercapacitor applications. The molar ratio of g-C3N4 is varied to achieve numerous nanostructures like nanoparticles and nanorods with optimum specific capacitance. Further, all as-prepared electrode materials are examined for supercapacitor application. The electrochemical behavior of prepared NiO/g-C3N4 nanocomposites is carried out under cyclic voltammetry (CV), galvanostatic charge-discharge (GCD), and electrochemical impedance spectroscopy (EIS) in a three-electrode cell under different electrolytes such as aqueous sodium sulphate electrolyte (1.0 M Na2SO4) and potassium hydroxide electrolyte (3.0 M KOH). Among all the electrode materials, NO-4 (1 : 2) shows the highest specific capacitance of 338.68 F/g at a scan rate of 2 mV/s and 161.3 F/g at a current density of 1 A/g in 1.0 M Na2SO4 electrolyte. Also, this electrode material shows 95.22 F/g at a scan rate of 2 mV/s in 3.0 M KOH electrolyte. The excessive specific capacitance of this electrode material is due to retarded charge transfer resistance in the interface at the electrode and electrolyte and a increased number of active sites. The investigation of the electrokinetics of all the prepared electrodes was also carried out, and it revealed the charge storage contribution of capacitive and diffusive parts which levitates the higher specific capacitance. The two-electrode study for evaluating supercapacitor performance is studied. The NO-4//NO-4 SSD in 1.0 M Na2SO4 electrolyte shows 18.23 F/g at a specific capacitance of 1 A/g with a corresponding energy density of 10.13 Wh/kg and a power density of 1.01 kW/kg, respectively.
New-Onset Crohn’s Disease following Initiation of Secukinumab: A Case Report and Review of the Role of IL-17 in the Pathogenesis of Crohn’s Disease
Authors: Khouri Anas , Moreno Cesar , Niland Benjamin
Published: May 2023

Patients with autoimmune conditions show a high expression of proinflammatory cytokines including interleukin (IL)-17. While IL-17 inhibitors have demonstrated efficacy in managing autoimmune disorders, rare instances of de novo or exacerbated inflammatory bowel disease (IBD) have been reported. The factors that affect the onset and severity remain unclear. Here, we present a case of a 38-year-old female who developed manifestations of Crohn’s disease within 1 month of initiating secukinumab treatment for psoriatic arthritis, in addition to a review of the role of IL-17 in the pathophysiology of Crohn’s disease.
Blockchain for Credibility in Educational Development: Key Technology, Application Potential, and Performance Evaluation
Authors: Wang Yan , Cong Xin , Zi Lingling , Xiang Qiuyan
Published: May 2023

Blockchain proposes many innovative technologies to establish credible mechanisms in an open environment and therefore, it becomes a promising solution to the problem of credibility in educational development. To better understand the role of the blockchain, we aim to provide an extensive survey focusing on its key technology, application potential, and performance evaluation. First, from the perspective of blockchain characteristics, we summarize its application architecture in educational credibility. Next, we extensively discuss application potential of the blockchain, such as data storage, data sharing, achievement certification, and activity evaluation. Moreover, we investigate the performance evaluation, including basic performance metrics and specialized metrics for credibility. Finally, we analyze the challenges and research trends of blockchain in educational credibility and provide useful insights for future research.
An Emerging Issue of Human-Leopard Conflict in the Human-Dominated Landscape of Mid-Hills: A Case Study from Tanahun District of Nepal
Authors: Kandel Shalik Ram , Neupane Bijaya , Miya Mahamad Sayab , Sadadev Bipana Maiya , Khatri Namrata Devi , Dhami Bijaya
Published: May 2023

Information on the spatial and temporal patterns of losses caused by leopard (Panthera pardus) in terms of human attacks and livestock depredation in the human-dominated landscape of the mid-hills of Nepal is essential in formulating and implementing effective mitigation measures. This study aimed to assess the spatial and temporal patterns of leopard attacks on humans and livestock and the economic losses incurred by livestock depredation between 2015 and 2019 in the Bhanu municipality of Tanahun District. We adopted a household survey (N = 110), key informant (N = 10), and focus group discussion (N = 4) for this study. We purposively chose two conflict wards: 2 and 4, based on the severity of the attacks by the leopard. Within each ward, we selected the households randomly and conducted a semistructured questionnaire survey in September 2020. A total of 8 incidents of human attacks and 142 incidents of livestock depredation were recorded, with six human casualties in ward 2 and 1.45 incidents of livestock depredation per household in ward 4. The maximum attack was observed during 2019 both on humans (n = 6) and livestock (n = 67). Leopards mostly attacked children below 9 years, living within 200 m of the nearest forest edge, with the highest attack during the autumn months (62.5%). During the five years, leopard killed goats that represent 83.1% of total livestock loss categories. A significant difference was found in the frequency of attacks on livestock over the years (χ2 = 87.60, df = 4, and

P
≤
0.01

), months (χ2 = 16.53, df = 11, and

P
=
0.12

), and time of day (χ2 = 48.47, df = 3, and

P
≤
0.001

) with the highest attack during the year 2019 (47.18%), July (14.08%), and daytime (42.96%), respectively. Households living nearer to the forest edge (<200 m) lost more livestock (72.54%). The monetary value of a total of 8142 USD (74 USD per household) was lost due to livestock depredation, with major monetary loss at a distance >400 m from the forest edge. We suggest adopting mitigation measures like predator-proof livestock corals while stall feeding and strengthening conscientious livestock herding practices during grazing, encouraging livestock insurance schemes, educating local communities about leopard behavior, caring for and protecting children intensively in the leopard attack sites, improving the prey base in the wild, and timely management of man-eater leopard to reduce the conflict in the study area and the country.
Metabolite Comparison between Spleen‐Deficiency and Healthy Children
Authors: Liang Zhiyi , Fu Qianzeng , Li Haiman , Xu Xuan , Ding Panting , Tang Wei , Ye Yong , Shao Xiangning , Tan Xiaowen , Wang Xiaojun , Luo Xun , Wang Jun , Wang Dejun , Zhong Huan , Liu Mi
Published: May 2023

Objective. From the perspective of metabolomics, this study compares the metabolomics characteristics of feces and urine between children with spleen‐deficiency and healthy children to explain the scientific connotation of children with spleen‐deficiency susceptibility to digestive system diseases from the metabolic level and provide a scientific basis for further research. Methods. This study included 20 children with spleen‐deficiencies and 17 healthy children. Children’s symptom scores, height, and weight were recorded in groups, and feces and urine samples were collected. The samples were detected using ultrahigh‐performance liquid chromatography‐mass spectrometry. The data were analyzed using multivariate statistical analysis such as principal component analysis (PCA) and partial least squares discriminant analysis (PLS‐DA). Related differential metabolites were identified through database comparisons between two groups based on the MS and KEGG. Results. Compared to healthy children, the metabolites glucuronic acid, xanthine, and indole‐3‐acetaldehyde tend to be reduced in children with spleen‐deficiency. Moreover, these children showed an increase in metabolites such as quinic acid, adenine, 4‐methyl‐5‐thiazole‐ethanol, 3‐formyl indole, and 5‐hydroxy indole‐3‐acetic acid. The condition affected many of the critical metabolic pathways, including the metabolism of tryptophan, cysteine, methionine, and pentose phosphate. Conclusion. The children with spleen‐deficiency had disorders at the metabolic level, which might be due to factors such as diet, personal preferences, and genes, leading to various symptoms, making spleen‐deficiency children more prone to suffer from digestive diseases than healthy children. The results set a basis for the research on children’s TCM constitution, which can be a reference to further studies to deal with the spleen‐deficiency.
Chaotic Dynamics and Control of a Discrete‐Time Chen System
Authors: Rana Sarker Md. Sohel , Uddin Md. Jasim , Santra P. K. , Mahapatra G. S.
Published: May 2023

We investigate a discrete‐time Chen system. First, we give the topological classifications of the fixed points of this system. Then, we analytically show that the discrete Chen system underlies a Neimark–Sacker (NS) bifurcation and period doubling (PD) under specific parametric circumstances. We confirm the existence of a PD and NS bifurcation via the explicit PD‐NS bifurcation criterion and determine the direction of both bifurcations with the help of center manifold theory. We performed numerical simulations to confirm our analytical results. Furthermore, we use the 0‐1 chaos test to quantify whether there is chaos in the system or not. At the end, the hybrid control strategy and the OGY (Ott, Grebogi, and Yorke) method are applied to eliminate chaotic trajectories of the system.
Predicting Mortality in Hospitalized COVID-19 Patients in Zambia: An Application of Machine Learning
Authors: Mulenga Clyde , Kaonga Patrick , Hamoonga Raymond , Mazaba Mazyanga Lucy , Chabala Freeman , Musonda Patrick
Published: May 2023

The coronavirus disease 2019 (COVID-19) has wreaked havoc globally, resulting in millions of cases and deaths. The objective of this study was to predict mortality in hospitalized COVID-19 patients in Zambia using machine learning (ML) methods based on factors that have been shown to be predictive of mortality and thereby improve pandemic preparedness. This research employed seven powerful ML models that included decision tree (DT), random forest (RF), support vector machines (SVM), logistic regression (LR), Naïve Bayes (NB), gradient boosting (GB), and XGBoost (XGB). These classifiers were trained on 1,433 hospitalized COVID-19 patients from various health facilities in Zambia. The performances achieved by these models were checked using accuracy, recall, F1-Score, area under the receiver operating characteristic curve (ROC_AUC), area under the precision-recall curve (PRC_AUC), and other metrics. The best-performing model was the XGB which had an accuracy of 92.3%, recall of 94.2%, F1-Score of 92.4%, and ROC_AUC of 97.5%. The pairwise Mann–Whitney U-test analysis showed that the second-best model (GB) and the third-best model (RF) did not perform significantly worse than the best model (XGB) and had the following: GB had an accuracy of 91.7%, recall of 94.2%, F1-Score of 91.9%, and ROC_AUC of 97.1%. RF had an accuracy of 90.8%, recall of 93.6%, F1-Score of 91.0%, and ROC_AUC of 96.8%. Other models showed similar results for the same metrics checked. The study successfully derived and validated the selected ML models and predicted mortality effectively with reasonably high performance in the stated metrics. The feature importance analysis found that knowledge of underlying health conditions about patients’ hospital length of stay (LOS), white blood cell count, age, and other factors can help healthcare providers offer lifesaving services on time, improve pandemic preparedness, and decongest health facilities in Zambia and other countries with similar settings.