bluuebunny/crossref_metadata_2025 huggingface dataset:
Circulating tumor DNA (ctDNA) serial analysis during progression on PD-1 blockade and later CTLA-4 rescue in patients with mismatch repair deficient metastatic colorectal cancer
Authors: Kasi Pashtoon Murtaza , Budde Griffin , Krainock Michael , Aushev Vasily N , Koyen Malashevich Allyson , Malhotra Meenakshi , Olshan Perry , Billings Paul R , Aleshin Alexey
Published: January 2022

Immune checkpoint inhibitors have shown great promise in treating patients with mismatch repair deficient/microsatellite instability high (dMMR/MSI-H) colorectal cancer (CRC). Although single-agent pembrolizumab has been approved for first-line treatment of dMMR/MSI-H metastatic CRC, combination therapy with cytotoxic T-lymphocyte-associated protein-4 (CTLA-4) inhibition (ipilimumab/nivolumab) has reported higher response rates. It is unclear whether patients who progress on PD-1 inhibition will respond to CTLA-4 blockade. Here, we report a case series of three patients with dMMR/MSI-H mCRC, where a durable and ongoing response to nivolumab with ipilimumab was achieved after initial progression with pembrolizumab monotherapy. Blood-based biomarkers such as carcinoembryonic antigen and CA 19-9 were employed to assess treatment response and monitor disease progression along with circulating tumor DNA (ctDNA). Our findings indicate ctDNA’s potential to accurately monitor response to therapy and detect disease progression, as validated by standard imaging. This case series demonstrates that CTLA-4 rescue is worthy of additional investigation as a treatment strategy after progression on PD-1 blockade in patients with dMMR/MSI-high mCRC. Our data support the utilization and expansion of clinical studies with combination therapies and using ctDNA kinetics as early dynamic marker for therapy response assessment.
TSH-TSHR axis promotes tumor immune evasion
Authors: Wu Zhenghao , Xi Zihan , Xiao Yunxiao , Zhao Xiangwang , Li Jiexiao , Feng Nan , Hu Longqing , Zheng Renjing , Zhang Ning , Wang Shuntao , Huang Tao
Published: January 2022

Background

Hormones are identified as key biological variables in tumor immunity. However, previous researches mainly focused on the immune effect of steroid hormones, while the roles that thyroid-stimulating hormone (TSH) played in the antitumor response were far from clear.

Methods

The source of TSH was determined using single-cell transcriptomic, histologic, quantitative PCR, and ELISA analysis. The influence of TSH on tumor proliferation, invasion, and immune evasion was evaluated in multiple cell lines of thyroid cancer, glioma, and breast cancer. Then transcriptomic sequencing and cellular experiments were used to identify signaling pathways. TSH receptor (TSHR) inhibitor was injected into homograft mouse tumor models with or without anti-programmed cell death protein-1 antibody.

Results

Monocyte-derived dendritic cells (moDCs) highly expressed TSHα and TSHβ2 and were the primary source of TSH in the tumor microenvironment. TSH released by moDCs promoted proliferation and invasion of tumors with high TSHR expressions, such as thyroid cancers and glioma. TSH also induced tumor programmed death-ligand 1 (PD-L1) expression through the TSHR-AC-PKA-JNK-c-JUN pathway. TSHR inhibitors reversed tumor immune evasion by inhibiting PD-L1 expression in tumor and myeloid cells and enhancing Teff activation.

Conclusions

TSH–TSHR axis promotes tumor evasion in thyroid cancers and glioma. TSH suppression therapy is an effective therapeutic strategy for combination in immune checkpoint blockades.
African perspectives of moral status: a framework for evaluating global bioethical issues
Authors: Atuire Caesar Alimsinya
Published: January 2022

This paper offers an African perspective on moral status grounded on an understanding of personhood. These concepts are key to understanding the differences in emphasis and the values at play when global ethical issues are analysed within the African context. Drawing from African philosophical reflections on the descriptive and normative concepts of personhood, I propose a dual notion of subject and object moral status. I explain how object moral status, duties owed to persons, is differently grounded with respect to subject moral status, which refers to communally directed agency. This distinction influences the African way of conceptualising and addressing ethical issues, where, without ignoring rights of persons, moral consideration about the agency of right bearers is often factored into ethical deliberation. As a practical example, I look at the debate surrounding legal access to safe abortion on the African continent. I suggest a Gadamerian approach to diffuse the tensions that sometimes arise between universalist advocates of rights and cultural decolonisationists.
Association of coronary angiographic lesions and mortality in patients over 80 years with NSTEMI
Authors: Siddiqui Anwar J , Omerovic Elmir , Holzmann Martin J , Böhm Felix
Published: January 2022

Objective

Coronary angiography (CA) and percutaneous coronary intervention (PCI) is of great importance during non-ST-segment elevation myocardial infarction (NSTEMI) management. Coronary artery lesions and their association to mortality in elderly patients with NSTEMI was investigated.

Methods

Patients >80 years of age who underwent CA at index NSTEMI during 2011–2014 were included. Data were collected from the Swedish Coronary Angiography and Angioplasty Registry and Swedish Web-system for Enhancement and Development of Evidence-based care in Heart disease Evaluated According to Recommended Therapies registries. Coronary lesions were categorised into; one vessel disease (1VD), multi-vessel disease (MVD) and left main disease (LMD) and 0%–49% stenosis grade were considered as controls.

Cox regression was used to estimate HRs for all-cause mortality associated with coronary lesions. Survival benefit was determined after PCI and in relation to if revascularisation was complete or incomplete and any complications in the Cath lab was assessed.

Results

Five thousand seven hundred and seventy patients with history of CA and PCI were included, 10% had normal coronary arteries, 26% had 1VD, 50% MVD and 14% LMD. Mortality was higher in patients with 1VD, MVD and LMD: HR 1.8 (1.3–2.5), HR 2.2 (1.6–3.0) and HR 2.8 (2.1–3.9), respectively. PCI were treated in 84% of 1VD, 73% MVD, and 54% in LMD. Survival was higher with PCI HR 0.85 (0.73–0.99). MVD had lower adjusted mortality HR 0.71 (0.58–0.87) compared with patients with MVD who did not undergo PCI. Complications and mortality were higher in patients with LMD both during CA and PCI, HR 2.9 (1.1–7.6) and HR 4.5 (1.6–12.5).

Conclusion

Coronary lesions (>50% stenosis) are strong predictors of mortality in elderly patients with NSTEMI. MVD is common and PCI treatment is associated with increased survival.
In situ simulation training for a better interprofessional team performance in transferring critically ill patients with COVID-19: a prospective randomised control trial
Authors: Manggala Sidharta Kusuma , Tantri Aida Rosita , Sugiarto Adhrie , Sianipar Imelda Rosalyn , Prasetyono Theddeus Octavianus Hari
Published: January 2022

Background

Transferring critically ill patients with COVID-19 is a challenging task; therefore, well-trained medical team is needed. This study aimed to determine the role of in situ simulation training during pandemic by using high-fidelity manikin to improve interprofessional communication, skills and teamwork in transferring critically ill patients with COVID-19.

Methods

This single-blinded randomised control trial included 40 subjects allocated into standard low-fidelity simulator (LFS) and high-fidelity simulator (HFS) groups. Subjects, who were not members of multiprofessional team taking care of patients with COVID-19, in each group were assigned into small groups and joined an online interactive lecture session, two sessions of in-situ simulation and a debriefing session with strict health protocols. The first simulation aimed to teach participants the skills and steps needed. The second simulation aimed to assess transfer skills, communication and teamwork performance, that participants had learnt using a validated, comprehensive assessment tool. Data were analysed using unpaired t test or Mann-Whitney test.

Results

The HFS group showed significantly better overall transfer and communication skills than LFS group (89.70±4.65 vs 77.19±3.6, <0.05 and 100 vs 88.34 (63.33–100), p=0.022, respectively). The HFS group also demonstrated significantly better teamwork performance than the standard LFS group (90 (80–900) vs 80 (70–90), p=0.028).

Conclusion

In situ simulation training using HFS significantly showed better performance than the standard training using LFS in regards to overall transfer and communication skills as well as teamwork performance. The training using HFS may provide a valuable adjunct to improve interprofessional skills, communication and teamwork performance in transferring critically ill patients with COVID-19.

Trial registration number

NCT05113823.
Discrepancies between clinical and autopsy findings in patients who had an acute stroke
Authors: Hudák Lilla , Nagy Attila Csaba , Molnár Sarolta , Méhes Gábor , Nagy Katalin Erzsébet , Oláh László , Csiba László
Published: January 2022

Objectives

According to international observations, the incidence of clinical autopsies is declining worldwide, plummeting below 5% in the USA and many European countries. It is an unfavourable trend as, in 7%–12% of cases, recent clinicopathological studies found discrepancies that might have changed the therapy or the outcome if known premortem. As previous large-scale observations have examined varied patient populations, we aimed to focus on the differences between the clinical and pathological diagnostic findings in only patients who had a stroke.

Material and methods

We assessed the postmortem non-neuropathological and neuropathological findings of 534 consecutive patients who had a stroke who passed away. Systemic neoplasms, pneumonias, thromboembolisms and haemorrhagic transformations revealed only by autopsy were considered severe abnormalities; in addition, benign abnormalities important from an educational or scientific point of view were also recorded.

Results

In 26 of the 534 cases (4.9%), the presence of systemic neoplasms had already been confirmed in the clinical stage; however, 8 (1.5%) malignant tumours were only detected during autopsy. Also, 80 (15%) thromboembolic events, 73 (13.6%) pneumonias and 66 (18%) haemorrhagic transformations were only diagnosed at autopsy. Longer hospital stay (from admission to death) resulted in fewer discrepancies between clinical and autopsy diagnosis of thromboembolic events and pneumonias (p<0.01). In 169 cases, benign findings were detected.

Conclusions

While the type of acute stroke is reliably diagnosed with imaging techniques, postmortem autopsies are also important in patients who had a stroke as autopsies may reveal clinically silent diseases (eg, tumour), and contribute to knowing the actual incidence of stroke-related thromboembolic and pneumonia complications.
‘They have a right to participate as a stakeholder’: Article 5.3 implementation and government interactions with the tobacco industry in Ethiopia
Authors: Hirpa Selamawit , Ralston Rob , Deressa Wakgari , Collin Jeff
Published: January 2022

Introduction

This paper explores implementation of Article 5.3 of the WHO Framework Convention on Tobacco Control in Ethiopia. The analysis highlights how operationalising key requirements of Article 5.3, such as minimising policy engagement with the tobacco industry, has been mediated by path-dependent processes of stakeholder consultation and collaboration that have persisted following privatisation of Ethiopia’s state-owned tobacco monopoly.

Methods

We conducted semistructured interviews with key officials (n=21) working in tobacco control policy, with high levels of access secured across ministries and agencies beyond health.

Results

We found contrasting levels of awareness of Article 5.3 across government sectors, with extremely limited awareness in departments beyond health. The data also highlight competing ideas about conflict of interest, in which recognition of a fundamental conflict of interest with the tobacco industry is largely confined to health actors. Beyond limited cross-sectoral awareness and understanding of Article 5.3, gaps in implementation are exacerbated by assumptions and practices around stakeholder consultation, in which attempts to minimise policy interactions with the tobacco industry are mediated by institutionally embedded processes that presume active engagement. The results also highlight a continuation of the close relationship between the Ethiopian government and tobacco monopoly following its privatisation.

Conclusion

The Ethiopian government’s recent achievements in tobacco control legislation require that policymakers are actively supported in reconciling perceived tensions and requirements for stakeholder consultation. Effective tobacco control governance would be further enhanced by enabling government agencies to more clearly identify which interactions with the tobacco industry are strictly necessary under Article 5.3 guideline recommendations.
Seawater browning alters community composition and reduces nutritional quality of plankton in a subarctic marine ecosystem
Authors: Bandara Tharindu , Brugel Sonia , Andersson Agneta , Lau Danny Chun Pong
Published: January 2022

Inflows of coloured terrestrial organic matter cause seawater browning and reduced phytoplankton production in subarctic coastal ecosystems, potentially deteriorating the nutritional quality of marine food webs. We analyzed the fatty-acid (FA) compositions of seston and the zooplankton taxa Eurytemora affinis and cladocerans at three locations of the northern Baltic Sea. At the coastal and northerly locations, salinity and phosphorus concentrations were low, while concentrations of humic substances (i.e., terrestrial organic matter) were high. The southerly location showed the opposite trend. The ratio between alga-specific ω3 polyunsaturated FA and terrigenous monounsaturated FA (MUFA) in Eurytemora decreased from south to north, as did the ratio between the alga-specific docosahexaenoic acid (DHA) and terrigenous MUFA in cladocerans. With increasing humic substances, the biomass of DHA-rich phytoplankton decreased and the zooplankton MUFA content increased. Our results indicate that coloured terrestrial organic matter alters the phytoplankton composition, consequently affecting the zooplankton nutritional quality.
New hybrid photonic crystal fiber gas sensor with high sensitivity for ammonia gas detection
Authors: Abbaszadeh Aryan , Makouei Somayeh , Meshgini Saeed
Published: January 2022

A new hybrid photonic crystal fiber (PCF) with circular rings based microstructure core gas sensor has been proposed for detecting ammonia gas at the wavelength of 1.544 μm. The finite element method has been used for numerical investigation. According to the results, the relative sensitivity is obtained as high as 70.25% at a wavelength of 1.544 μm. Furthermore, high birefringence and effective area are acquired by orders of 1.24 × 10−3 and 13.35 μm2, respectively. Finally, a low confinement loss of 1.202 × 10−1 dB/m is gained at the same wavelength. The absorption spectroscopy system can be used for detecting ammonia gas for experimental work. The theoretical results show that the proposed PCF still exhibits high relative sensitivity for a low concentration of ammonia gas at the wavelength of 1.544 μm, which makes the sensors detect gas precisely and can be used for medical and industrial applications.
Comment on “Greybody radiation and quasinormal modes of Kerr-like black hole in Bumblebee gravity model”
Authors: Maluf R. V. , Muniz C. R.
Published: January 2022

It is shown that the paper “Greybody radiation and quasinormal modes of Kerr-like black hole in Bumblebee gravity model” (Kanzi and Sakallı in Eur Phys J C 81:501, 2021) recently published in this journal is based on an incorrect result obtained by Ding et al. (Eur Phys J C 80:178, 2020) for a Kerr-like black hole solution.
Defense Against Adversarial Attacks Based on Stochastic Descent Sign Activation Networks on Medical Images
Authors: Yang Yanan , Shih Frank Y. , Roshan Usman
Published: January 2022

Machine learning techniques in medical imaging systems are accurate, but minor perturbations in the data known as adversarial attacks can fool them. These attacks make the systems vulnerable to fraud and deception, and thus a significant challenge has been posed in practice. We present the gradient-free trained sign activation networks to detect and deter adversarial attacks on medical imaging AI systems. Experimental results show that a higher distortion value is required to attack our proposed model than the other existing state-of-the-art models on MRI, Chest X-ray, and Histopathology image datasets, where our model outperforms the best and is even twice superior. The average accuracy of our model in classifying the adversarial examples is 88.89%, whereas those for MLP and LeNet are 81.48%, and that of ResNet18 is 38.89%. It is concluded that the sign network is a solution to defend adversarial attacks due to high distortion and high accuracy on transferability. Our work is a significant step towards safe and secure medical AI systems.
Generic Method for SDN Controller Selection Using AHP and TOPSIS Methods
Authors: Durkadevi K. , Revathi T. , Shenbagalakshmi G.
Published: January 2022

The control plane plays an essential role in the implementation of Software Defined Network (SDN) architecture. Basically, the control plane is an isolated process and operates on control layer. The control layer encompasses controllers which provide a global view of the entire SDN. The Controller selection is more crucial for the network administrator to meet the specific use case. This research work mainly focuses on obtaining a better SDN controller. Initially, the SDN controllers are selected using integrated Analytic Hierarchy Process and Technique for Order Preference Similarity to Ideal Solution (AHP and TOPSIS) method. It facilitates to select minimal number of controllers based on their features in the SDN application. Finally, the performance evaluation is carried out using the CBENCH tool considering the best four ranked controllers obtained from the previous step. In addition, it is validated with the real-time internet topology such as Abilene and ERNET considering the delay factor. The result shows that the “Floodlight” controller responds better for latency and throughput. The selection of an optimum controller-Floodlight, using the real-world Internet topologies, outperforms in obtaining the path with a 28.57% decrease in delay in Abilene and 16.94% in ERNET. The proposed work can be applied in high traffic SDN applications.
Ten Ways to Specify a Gini Coefficient Using Entropy
Authors: Ryu Hang Keun , Slottje Daniel J.
Published: January 2022

Our friend and frequent collaborator Prof. Michael McAleer loved to enumerate lists and to give practical advice. Here, we present a review of 10 ways to derive the well-known Gini coefficient based on entropy measures. In fact, Mike was a collaborator on some of this work, as will be discussed in the paper. All are useful ways to combine two powerful tools, entropy measures and Gini coefficients to examine inequality in income distribution functions (IDFs) and can be applied to distributions of other random variables. Others have shown that a Gini coefficient can be derived from the first moment of an observed share function. Ryu and Slottje demonstrated that by projecting the observed share function with other moments and functions different approximated share functions can be derived. By doing so, more information can be conveyed about the underlying IDF that generated the observed Gini value. In the spirit of Prof. Michael McAleer, we present 10 different ways to utilize entropy functions to generate Gini coefficient measures.
THE EFFECTS OF U.S. MONETARY POLICY UNCERTAINTY SHOCK ON INTERNATIONAL EQUITY MARKETS
Authors: AOR RAYMOND L. , SALISU AFEES A. , OKPE ISAH J.
Published: January 2022

In this study, we quantify the propagation effects of the U.S. monetary policy uncertainty (MPU) shock on real equity prices of 33 advanced and emerging countries over the period 1980Q1 to 2019Q4. We employ a large-scale global vector autoregressive (GVAR) model which simultaneously accounts for country-specific macroeconomic conditions as well as regional and global trade and financial linkages among the countries. We show that the U.S. MPU shock spreads negative (but temporary) effects on the real equity prices, albeit with greater impacts on the advanced markets than their emerging counterparts owing to the greater connections of the former with the U.S. economy. Our results hold important implications for portfolio investors and policymakers.
EXPLORING THE IMPACT OF ICT DIFFUSION IN THE EUROPEAN BANKING INDUSTRY: EVIDENCE IN THE PRE- AND POST-COVID-19
Authors: CICCHIELLO ANTONELLA FRANCESCA , COTUGNO MATTEO , MONFERRÀ STEFANO , PERDICHIZZI SALVATORE
Published: January 2022

Based on daily data from Thomson Reuter’s Refinitiv, we investigate the effect of information and communication technology (ICT) on the profitability and risk of the European banking industry during the COVID-19 pandemic. Specifically, we empirically examine whether and how ICT diffusion affects banks’ stock return, credit default swaps (CDS) spreads and market volatility over the period spanning from January 1, 2020, to March 31, 2020. Our evidence demonstrates that ICT improves banks’ performance measures and reduces risks. These effects are more significant in the post-COVID-19 period.
Experimental and theoretical characterization of the interfacial adhesion of 2D heterogeneous materials: A review
Authors: Anwer Shoaib , Li Baosong , Luo Shaohong , Alkhidir Tamador , Mohamed Sharmarke , Chan Vincent , Liao Kin
Published: January 2022

Two-dimensional (2D) materials have been developed intensively over the last decade, and combining different 2D materials to form heterogeneous 2D materials is anticipated to be more attractive with broader applications. The precise evaluation and prediction of interfacial properties of 2D heterostructures are critical for designing more robust heterostructures and developing advanced, engineered molecular devices. Here, we present a brief review on experimental (namely, atomic force microscopy (AFM), in situ peel test, double cantilever beam, pressurized blister test and sheet-on-bead method) and theoretical techniques (namely, molecular dynamics and density functional theory) for probing the adhesion/interaction energy of the interface of 2D heterogeneous materials and paving the way for future applications.
The Forward Slice Core: A High-Performance, Yet Low-Complexity Microarchitecture
Authors: Lakshminarasimhan Kartik , Naithani Ajeya , Feliu Josué , Eeckhout Lieven
Published: January 2022

Superscalar out-of-order cores deliver high performance at the cost of increased complexity and power budget. In-order cores, in contrast, are less complex and have a smaller power budget, but offer low performance. A processor architecture should ideally provide high performance in a power- and cost-efficient manner. Recently proposed
slice-out-of-order (sOoO)
cores identify backward slices of memory operations which they execute out-of-order with respect to the rest of the dynamic instruction stream for increased instruction-level and memory-hierarchy parallelism. Unfortunately, constructing backward slices is imprecise and hardware-inefficient, leaving performance on the table.

In this article, we propose
Forward Slice Core (FSC
), a novel core microarchitecture that builds on a stall-on-use in-order core and extracts more instruction-level and memory-hierarchy parallelism than slice-out-of-order cores. FSC does so by identifying and steering forward slices (rather than backward slices) to dedicated in-order FIFO queues. Moreover, FSC puts load-consumers that depend on L1 D-cache misses on the side to enable younger independent load-consumers to execute faster. Finally, FSC eliminates the need for dynamic memory disambiguation by replicating store-address instructions across queues. Considering 3-wide pipeline configurations, we find that FSC improves performance by 27.1%, 21.1%, and 14.6% on average compared to Freeway, the state-of-the-art sOoO core, across SPEC CPU2017, GAP, and DaCapo, respectively, while at the same time incurring reduced hardware complexity. Compared to an OoO core, FSC reduces power consumption by 61.3% and chip area by 47%, providing a microarchitecture with high performance at low complexity.
Deep Reinforcement Learning for Black-box Testing of Android Apps
Authors: Romdhana Andrea , Merlo Alessio , Ceccato Mariano , Tonella Paolo
Published: January 2022

The state space of Android apps is huge, and its thorough exploration during testing remains a significant challenge. The best exploration strategy is highly dependent on the features of the app under test. Reinforcement Learning (RL) is a machine learning technique that learns the optimal strategy to solve a task by trial and error, guided by positive or negative reward, rather than explicit supervision. Deep RL is a recent extension of RL that takes advantage of the learning capabilities of neural networks. Such capabilities make Deep RL suitable for complex exploration spaces such as one of Android apps. However, state-of-the-art, publicly available tools only support basic, Tabular RL. We have developed ARES, a Deep RL approach for black-box testing of Android apps. Experimental results show that it achieves higher coverage and fault revelation than the baselines, including state-of-the-art tools, such as TimeMachine and Q-Testing. We also investigated the reasons behind such performance qualitatively, and we have identified the key features of Android apps that make Deep RL particularly effective on them to be the presence of chained and blocking activities. Moreover, we have developed FATE to fine-tune the hyperparameters of Deep RL algorithms on simulated apps, since it is computationally expensive to carry it out on real apps.
Predictive Models in Software Engineering: Challenges and Opportunities
Authors: Yang Yanming , Xia Xin , Lo David , Bi Tingting , Grundy John , Yang Xiaohu
Published: January 2022

Predictive models are one of the most important techniques that are widely applied in many areas of software engineering. There have been a large number of primary studies that apply predictive models and that present well-performed studies in various research domains, including software requirements, software design and development, testing and debugging, and software maintenance. This article is a first attempt to systematically organize knowledge in this area by surveying a body of 421 papers on predictive models published between 2009 and 2020. We describe the key models and approaches used, classify the different models, summarize the range of key application areas, and analyze research results. Based on our findings, we also propose a set of current challenges that still need to be addressed in future work and provide a proposed research road map for these opportunities.
Engineering In-place (Shared-memory) Sorting Algorithms
Authors: Axtmann Michael , Witt Sascha , Ferizovic Daniel , Sanders Peter
Published: January 2022

We present new sequential and parallel sorting algorithms that now represent the fastest known techniques for a wide range of input sizes, input distributions, data types, and machines. Somewhat surprisingly, part of the speed advantage is due to the additional feature of the algorithms to work in-place, i.e., they do not need a significant amount of space beyond the input array. Previously, the in-place feature often implied performance penalties. Our main algorithmic contribution is a blockwise approach to in-place data distribution that is provably cache-efficient. We also parallelize this approach taking dynamic load balancing and memory locality into account.

Our new comparison-based algorithm
In-place Parallel Super Scalar Samplesort (

IPS
4
o

)
, combines this technique with branchless decision trees. By taking cases with many equal elements into account and by adapting the distribution degree dynamically, we obtain a highly robust algorithm that outperforms the best previous in-place parallel comparison-based sorting algorithms by almost a factor of three. That algorithm also outperforms the best comparison-based competitors regardless of whether we consider in-place or not in-place, parallel or sequential settings.

Another surprising result is that

IPS
4
o

even outperforms the best (in-place or not in-place) integer sorting algorithms in a wide range of situations. In many of the remaining cases (often involving near-uniform input distributions, small keys, or a sequential setting), our new
In-place Parallel Super Scalar Radix Sort (

IPS
2
Ra

)
turns out to be the best algorithm.

Claims to have the – in some sense – “best” sorting algorithm can be found in many papers which cannot all be true. Therefore, we base our conclusions on an extensive experimental study involving a large part of the cross product of 21 state-of-the-art sorting codes, 6 data types, 10 input distributions, 4 machines, 4 memory allocation strategies, and input sizes varying over 7 orders of magnitude. This confirms the claims made about the robust performance of our algorithms while revealing major performance problems in many competitors outside the concrete set of measurements reported in the associated publications. This is particularly true for integer sorting algorithms giving one reason to prefer comparison-based algorithms for robust general-purpose sorting.
Bandwidth-Optimal Random Shuffling for GPUs
Authors: Mitchell Rory , Stokes Daniel , Frank Eibe , Holmes Geoffrey
Published: January 2022

Linear-time algorithms that are traditionally used to shuffle data on CPUs, such as the method of Fisher-Yates, are not well suited to implementation on GPUs due to inherent sequential dependencies, and existing parallel shuffling algorithms are unsuitable for GPU architectures because they incur a large number of read/write operations to high latency global memory. To address this, we provide a method of generating pseudo-random permutations in parallel by fusing suitable pseudo-random bijective functions with stream compaction operations. Our algorithm, termed “bijective shuffle” trades increased per-thread arithmetic operations for reduced global memory transactions. It is work-efficient, deterministic, and only requires a single global memory read and write per shuffle input, thus maximising use of global memory bandwidth. To empirically demonstrate the correctness of the algorithm, we develop a statistical test for the quality of pseudo-random permutations based on kernel space embeddings. Experimental results show that the bijective shuffle algorithm outperforms competing algorithms on GPUs, showing improvements of between one and two orders of magnitude and approaching peak device bandwidth.
Autonomous agents and multiagent systems
Authors: Endriss Ulle , Nowé Ann , Gini Maria , Lesser Victor , Luck Michael , Paiva Ana , Sichman Jaime
Published: January 2022

The 2021 edition of AAMAS, the International Conference on Autonomous Agents and Multiagent Systems, took place from the 3rd to 7th of May 2021 (aamas2021.soton.ac.uk). This year it was organized in the form of a virtual event and attracted over 1,000 registered participants. As every year, the conference featured an exciting programme of contributed talks, keynotes addresses, tutorials, affiliated workshops, a doctoral consortium, and more.
Towards Robustness of Deep Program Processing Models—Detection, Estimation, and Enhancement
Authors: Zhang Huangzhao , Fu Zhiyi , Li Ge , Ma Lei , Zhao Zhehao , Yang Hua’an , Sun Yizhe , Liu Yang , Jin Zhi
Published: January 2022

Deep learning (DL) has recently been widely applied to diverse source code processing tasks in the software engineering (SE) community, which achieves competitive performance (e.g., accuracy). However, the robustness, which requires the model to produce consistent decisions given minorly perturbed code inputs, still lacks systematic investigation as an important quality indicator. This article initiates an early step and proposes a framework CARROT for robustness detection, measurement, and enhancement of DL models for source code processing. We first propose an optimization-based attack technique CARROTAto generate valid adversarial source code examples effectively and efficiently. Based on this, we define the robustness metrics and propose robustness measurement toolkit CARROTM, which employs the worst-case performance approximation under the allowable perturbations. We further propose to improve the robustness of the DL models by adversarial training (CARROTT) with our proposed attack techniques. Our in-depth evaluations on three source code processing tasks (i.e., functionality classification, code clone detection, defect prediction) containing more than 3 million lines of code and the classic or SOTA DL models, including GRU, LSTM, ASTNN, LSCNN, TBCNN, CodeBERT, and CDLH, demonstrate the usefulness of our techniques for ❶ effective and efficient adversarial example detection, ❷ tight robustness estimation, and ❸ effective robustness enhancement.
Federated Data Science to Break Down Silos [Vision]
Authors: Mansour Essam , Srinivas Kavitha , Hose Katja
Published: January 2022

Similar to Open Data initiatives, data science as a community has launched initiatives for sharing not only data but entire pipelines, derivatives, artifacts, etc. (Open Data Science). However, the few efforts that exist focus on the technical part on how to facilitate sharing, conversion, etc. This vision paper goes a step further and proposes KEK, an open federated data science platform that does not only allow for sharing data science pipelines and their (meta)data but also provides methods for efficient search and, in the ideal case, even allows for combining and defining pipelines across platforms in a federated manner. In doing so, KEK addresses the so far neglected challenge of actually finding artifacts that are semantically related and that can be combined to achieve a certain goal.
Effect of Bubbles and Liquid Drops Fluid Dynamics on the Lithium Recombination inside a Lithium Electrolytic Cell with Diaphragm
Authors: Meléndez Juan Manuel , Désilets Martin , Lantagne Gaétan , Oliaii Elaheh
Published: January 2022

Metallic lithium, which is a critical and strategic metal for the world’s production of energy storage devices, is mainly produced from molten salt electrolysis. To increase the efficiency of the process, it is of utmost importance to prevent lithium recombination during the process to avoid energy waste. This research studies the behavior of the main variables involved in the reaction inside a

Li

-production experimental cell from the mass transfer, electrochemical and fluid dynamics standpoints. Simulations were done for a total electrolysis time interval of 600 s using a turbulent (k-ε) approach to solve the two-phase flow coupled to the lithium electrolysis process. To analyze the influence of cathode fluid dynamics in relation to the amount of recombined lithium, two configurations of the diaphragm were evaluated including the incorporation of a baffle at the bottom of the cell and the inclination of the diaphragm. The baffle reduced the amount of recombined lithium by

7
%
,

and the diaphragm with an inclination < 90° reduced the total recombined mass by

77
%
,

although it increased the energy consumption by

1
0
%

with respect to the base case of a vertical diaphragm.
(Invited) Phase Transformation and Chemomechanical Breakdown of Alkali Metal Ion Cathode Materials
Authors: Lin Feng
Published: January 2022

Chemical and mechanical properties interplay on the nanometric scale and collectively govern the functionalities of battery materials. Understanding the relationship between the two can inform the design of battery materials with optimal chemomechanical properties for long-life lithium and sodium batteries. We found that chemomechanical properties of cathode materials are associated with phase transformation behaviors and can promote the cathode–anode crosstalk in full cells. In this presentation, we will first discuss an integrative approach of mapping valence states and constructing chemical topographies to investigate the redox phase transformation in layered oxide cathode materials at the secondary particle level under thermal abuse conditions. We discover that, in addition to the three-dimensional heterogeneous phase transformation, there is a mesoscale dynamic evolution of local valence curvatures in valence state topographies. The relative probability of negative and positive local valence curvatures alternates during the phase transformation. Such a behavior is likely associated with local chemical environments (e.g., grain boundaries, compositional variation) and can determine chemomechanical properties and ionic transport in cathode materials. Then we will discuss a mechanism of nanoscale mechanical breakdown in layered oxide cathode materials, originating from oxygen release at high states of charge. We observe that the mechanical breakdown of charged cathode materials proceeds via a two-step pathway involving intergranular and intragranular crack formation. Owing to the oxygen release, sporadic phase transformations from the layered structure to the spinel and/or rocksalt structures introduce local stress, which initiates microcracks along grain boundaries and ultimately leads to the detachment of primary particles; i.e., intergranular crack formation. Furthermore, intragranular cracks (pores and exfoliations) form, likely due to the accumulation of oxygen vacancies and continuous phase transformations at the surfaces of primary particles. Finally, we will highlight some methods that we develop to overcome chemomechanical breakdown.
Estradiol-dependent gene expression profile in the amygdala of young ovariectomized spontaneously hypertensive rats
Authors: Pham Linh T. , Yamanaka Ko , Miyamoto Yasunori , Waki Hidefumi , Gouraud Sabine S. S.
Published: January 2022

Estrogen plays a role in cardiovascular functions, emotional health, and energy homeostasis via estrogen receptors expressed in the brain. The comorbid relationship between rising blood pressure, a decline in mood and motivation, and body weight gain after menopause, when estrogen levels drop, suggests that the same brain area(s) contributes to protection from all of these postmenopausal disorders. The amygdala, a major limbic system nuclear complex known to express high estrogen receptor levels, is involved in the regulation of such physiological and psychological responses. We hypothesized that elevated estrogen levels contribute to premenopausal characteristics by activating specific genes and pathways in the amygdala. We examined the effect of 1 mo of estradiol treatment on the gene expression profile in the amygdala of ovariectomized young adult female spontaneously hypertensive rats. Estradiol substitution significantly decreased blood pressure, prevented body weight gain, and enhanced the voluntary physical activity of ovariectomized rats. In the amygdala of ovariectomized rats, estradiol treatment downregulated the expression of genes associated with estrogen signaling, cholinergic synapse, dopaminergic synapse, and long-term depression pathways. These findings indicate that the transcriptomic characteristics of the amygdala may be involved in estrogen-dependent regulation of blood pressure, physical activity motivation, and body weight control in young adult female spontaneously hypertensive rats.
Identification of Visual Imagery by Electroencephalography Based on Empirical Mode Decomposition and an Autoregressive Model
Authors: Fu Yunfa , Li Zhaoyang , Gong Anmin , Qian Qian , Su Lei , Zhao Lei
Published: January 2022

The traditional imagery task for brain–computer interfaces (BCIs) consists of motor imagery (MI) in which subjects are instructed to imagine moving certain parts of their body. This kind of imagery task is difficult for subjects. In this study, we used a less studied yet more easily performed type of mental imagery—visual imagery (VI)—in which subjects are instructed to visualize a picture in their brain to implement a BCI. In this study, 18 subjects were recruited and instructed to observe one of two visual-cued pictures (one was static, while the other was moving) and then imagine the cued picture in each trial. Simultaneously, electroencephalography (EEG) signals were collected. Hilbert–Huang Transform (HHT), autoregressive (AR) models, and a combination of empirical mode decomposition (EMD) and AR were used to extract features, respectively. A support vector machine (SVM) was used to classify the two kinds of VI tasks. The average, highest, and lowest classification accuracies of HHT were 68.14 

±

 3.06%, 78.33%, and 53.3%, respectively. The values of the AR model were 56.29 

±

 2.73%, 71.67%, and 30%, respectively. The values obtained by the combination of the EMD and the AR model were 78.40 

±

 2.07%, 87%, and 48.33%, respectively. The results indicate that multiple VI tasks were separable based on EEG and that the combination of EMD and an AR model used in VI feature extraction was better than an HHT or AR model alone. Our work may provide ideas for the construction of a new online VI-BCI.
Government Low‐Carbon Policies Optimization for Smart Transportation Enterprises
Authors: Gao Kai , Guo Xin , Liu Tingting , Han Rui
Published: January 2022

As an important part of energy saving and carbon reduction, the low‐carbon development of the transportation industry is imperative. It is the responsibility of smart transportation enterprises to closely combine their own digital technology with the governments’ policies to achieve green innovation. In this study, we conducted an evolutionary game model of the interaction between the governments and smart transportation enterprises, which depended on innovation subsidies and punitive taxes. Besides, we derived the evolutionarily stable strategy of the governments and enterprises and used a simulation to analyze the impact of various policy tools on green innovation strategy. The results showed that the behavior of the governments relies on the benefits of supervision and the costs of supporting green technology innovation. The enterprises’ behavior depends on the benefits of green innovation and the loss of no green innovation. Moreover, different policy tools provided by the governments can accelerate the implementation of enterprises’ green innovation.
Network Security and Ideological Security Based on Wireless Communication and Big Data Analysis
Authors: Jiang Chunlan
Published: January 2022

The rapid development of information technology has caused unprecedented changes in society and life. People's dependence on information terminals represented by mobile communication devices has greatly increased. The average time spent on information terminals is more than three hours per day, especially for the younger generation. This figure will be even more exaggerated. The West takes the network as an important position for cultural penetration into China and pushes the cultural products of good and bad to China in large quantities. In this context, the study of the relationship between network culture and ideology has become an important node in the construction of ideological security defense. This study first makes a detailed analysis of the concept and research status of network ideology, then discusses the harm of Western ideological network penetration, and puts forward the corresponding countermeasures. According to the characteristics of the current stage, a network ideology big data platform is designed and the detection ability and running time of the platform are analyzed. The results show that the overall performance of the platform is very good and it is more suitable to work in parallel mode.
A Study on the Evaluation of the Effect of Exercise on the Treatment of Chronic Diseases Based on a Digital Human Movement Model
Authors: Guan Yu Meng , Pan Xiao Gui , Chen Ke , Xu Yang
Published: January 2022

The aim of this study was to summarise the therapeutic effects of exercise interventions for common chronic diseases and to analyse the scope of application and problems of various exercise treatment protocols, with a view to guiding clinical practice and providing references for subsequent research. To this end, this paper describes how to extract feature parameters for gait analysis based on a digital human motion model. In-depth descriptions of the extraction algorithms for spatiotemporal features, centre-of-mass movement features, joint mobility, and joint contact forces are presented, and the reliability of the knee contact force extraction algorithm is analysed in particular. To analyse the effect of exercise on the treatment of chronic diseases, 50 cases of elderly chronic disease patients collected from the community were selected and subjected to healthy exercise for 1 year, before and after the healthy exercise. After the exercise, the elderly chronic disease patients’ blood pressure, lipid, and blood glucose attainment rates, chronic diseases, and knowledge of nonpharmacological treatments were significantly higher, with statistically significant differences compared to the preexercise period (

P
<
0.05

).
Reaction Mechanisms Applied to Starch Modification for Biodegradable Plastics: Etherification and Esterification
Authors: Kim Yongeun , Jung Cheolsoo
Published: January 2022

Although many studies are being actively conducted to develop biodegradable plastic materials, most of these reports focused more on efficiency or performance improvement than on the reaction mechanism. This paper discussed the reaction mechanism applied to starch modification by etherification and esterification, which are the most studied in the field of biodegradable plastics. In the starch-reforming reaction by etherification, the effects of the reaction temperature, pH, solvent, and by-products on the chemical structure and physical properties of biodegradable plastics were discussed. In esterification, the structure of the substituents and the reaction solvents were examined. As a material that can replace plastics, the aim is to help derive new ideas on the design of reaction condition that can expand the use of starch.