bluuebunny/crossref_metadata_2025 huggingface dataset:
Eculizumab versus rituximab in generalised myasthenia gravis
Authors: Nelke Christopher , Schroeter Christina B , Stascheit Frauke , Pawlitzki Marc , Regner-Nelke Liesa , Huntemann Niklas , Arat Ercan , Öztürk Menekse , Melzer Nico , Mergenthaler Philipp , Gassa Asmae , Stetefeld Henning , Schroeter Michael , Berger Benjamin , Totzeck Andreas , Hagenacker Tim , Schreiber Stefanie , Vielhaber Stefan , Hartung Hans-Peter , Meisel Andreas , Wiendl Heinz , Meuth Sven G , Ruck Tobias
Published: March 2022

Objective

Myasthenia gravis (MG) is the most common autoimmune disorder affecting the neuromuscular junction. However, evidence shaping treatment decisions, particularly for treatment-refractory cases, is sparse. Both rituximab and eculizumab may be considered as therapeutic options for refractory MG after insufficient symptom control by standard immunosuppressive therapies.

Methods

In this retrospective observational study, we included 57 rituximab-treated and 20 eculizumab-treated patients with MG to compare the efficacy of treatment agents in generalised, therapy-refractory anti-acetylcholine receptor antibody (anti-AChR-ab)-mediated MG with an observation period of 24 months. Change in the quantitative myasthenia gravis (QMG) score was defined as the primary outcome parameter. Differences between groups were determined in an optimal full propensity score matching model.

Results

Both groups were comparable in terms of clinical and demographic characteristics. Eculizumab was associated with a better outcome compared with rituximab, as measured by the change of the QMG score at 12 and 24 months of treatment. Minimal manifestation of disease was more frequently achieved in eculizumab-treated patients than rituximab-treated patients at 12 and 24 months after baseline. However, the risk of myasthenic crisis (MC) was not ameliorated in either group.

Interpretation

This retrospective, observational study provides the first real-world evidence supporting the use of eculizumab for the treatment of refractory, anti-AChR-ab positive MG. Nonetheless, the risk of MC remained high and prompts the need for intensified monitoring and further research effort aimed at this vulnerable patient cohort.
Inflammatory markers in saliva and urine reflect disease activity in patients with systemic lupus erythematosus
Authors: Ruacho Guillermo , Lira-Junior Ronaldo , Gunnarsson Iva , Svenungsson Elisabet , Boström Elisabeth A
Published: March 2022

Background

Laboratory tests of blood and sometimes urine are used to diagnose and to monitor disease activity (DA) in SLE. Clinical practice would be simplified if non-invasive urine and salivary tests could be introduced as alternatives to blood samples. We therefore explored the levels of innate immunity-related biomarkers in matched serum, urine and saliva samples from patients with SLE.

Methods

A total of 84 patients with SLE selected to represent high and low general DA, and 21 controls were included. All participants underwent a thorough clinical examination. General DA and renal DA were measured. The levels of colony-stimulating factor (CSF)-1, interleukin (IL)-34, tumour necrosis factor (TNF)-α, interferon-γ-induced protein (IP)-10, monocyte chemoattractant protein (MCP)-1, calprotectin, macrophage inflammatory protein (MIP)-1α and MIP-1β were analysed by immunoassays and related to DA.

Results

CSF-1, TNF-α, IP-10 and MCP-1 in saliva, serum and urine, as well as calprotectin in saliva and urine were increased in patients with SLE as compared with controls (p<0.05). TNF-α, IP-10 and MCP-1 in saliva, serum and urine, and CSF-1 in saliva and serum distinguished patients with SLE from controls (area under the curve >0.659; p<0.05 for all). CSF-1 in serum and urine, and calprotectin in saliva and urine, as well as TNF- α, IP-10 and MCP-1 in urine correlated positively with measures of general DA (p<0.05). Patients with SLE with active renal disease presented elevated levels of TNF-α, IP-10 and MCP-1 in urine and CSF-1 and IP-10 in serum as compared with patients with SLE with non-active renal disease.

Conclusions

Our investigation demonstrates that saliva is a novel alternative body fluid, with potential for surveillance of general DA in patients with SLE, but urine is more informative in patients with SLE with predominantly renal DA.
Medication-taking for secondary prevention of acute myocardial infarction: a thematic meta-synthesis of patient experiences
Authors: Piekarz Hannah , Langran Catherine , Raza Amna , Donyai Parastou
Published: March 2022

Objective

To collate existing qualitative research examining patients’ medication-taking experiences in secondary prevention of acute myocardial infarction (AMI) and produce new knowledge, a systematic review and meta-synthesis of patient qualitative studies was conducted.

Method

A systematic review found nine reports suitable for inclusion. Themes found by the report authors and report characteristic data were extracted. Reports were assessed for quality. A meta-synthesis using thematic coding and constant comparison method produced higher order themes, and these were used to construct a statement organised by theme using specific examples from the included studies.

Results

All patients discussed their medication-taking in thematic categories of beliefs about medication and illness, personal ability and interpersonal factors. Themes differed between classes of medication and between patients, suggesting tailored interventions to medications and individual patients would be appropriate. Some themes overlapped with those discussed by the broader group of cardiovascular patients, but some themes were unique to this myocardial infarction patient group, again indicating that a tailored approach is appropriate for this patient group.

Conclusion

The themes of beliefs about medication and illness, personal ability and interpersonal support provide tangible starting points for addressing adherence issues. The concept of medication-taking had unique elements within the post-AMI group of patients, and between classes of medication. While these themes were grouped into more generalised higher-order constructs, there were differences between patients within the themed group, indicating that themes are useful as a guide, but individual-level patient support is appropriate.
Gender equity in academic rheumatology: is there a gender gap at European rheumatology conferences?
Authors: Hassan Neelam , van Mens Leonieke JJ , Kiltz Uta , Andreoli Laura , Delgado-Beltran Concha , Ovseiko Pavel V , Gossec Laure , Coates Laura C
Published: March 2022

Objectives

To obtain an overview of gender equity at European rheumatology conferences.

Methods

The proportion of women invited as either moderators or speakers to the European Alliance of Associations for Rheumatology (EULAR) annual congresses and national conferences in Europe was calculated from the published congress materials from EULAR annual congresses (2015–2019) and the 2019 national conferences of France, Germany, Italy, Spain and the UK. Data from EULAR congresses were further categorised by type of session. Significance testing was conducted using χ2 tests with the level of statistical significance set at p<0.05.

Results

The proportion of combined women moderators and speakers at EULAR varied from 40% to 43% between 2015 and 2019 with no obvious trend over time. There were higher proportions of women in the Health Professionals in Rheumatology and People with Arthritis and Rheumatism sessions (>50% consistently). However, these sessions represent <25% of EULAR congress invitations. Representation of women at the EULAR congress in 2019 (39.6%) was significantly higher than at the national congresses in France (28.6%) and Germany (29.6%) but similar to that observed in Italy (33.7%), Spain (41.7%) and the UK (42%).

Conclusion

Women account for less than half of invited moderators and speakers at the conferences reviewed. Compared with historical EULAR data in 2003 (16%) and in 2004 (19%), the gender gap at EULAR congresses has narrowed considerably, but there remains a need to monitor and improve women’s representation.
Using publicly available weather station data to investigate the effects of heat stress on milk production traits in Canadian Holstein cattle
Authors: Campos I.L. , Chud T.C.S , Oliveira H.R. , Baes C.F. , Cánovas A. , Schenkel F.S.
Published: March 2022

Heat stress imposes a challenge to the dairy industry, even in northern latitudes. In this study, publicly available weather station data were combined with test-day records for milk, fat, and protein yields to identify the temperature–humidity index (THI) thresholds at which heat load starts affecting milk production traits in Canadian Holstein cows. Production loss per THI unit above the threshold for each trait was estimated. Test-day records from 2010 to 2019 from 166,749 cows raised in Ontario and from 221,214 cows raised in Quebec were analyzed. Annual economic losses (EL) due to heat stress were estimated from the average losses of fat and protein yields based on the annual average of 156 d with THI exceeding the calculated thresholds. Average thresholds for the daily maximum (THImax) and daily average (THIavg) THI estimated across lactations in both provinces were THImax (THIavg) 68 (64), 57 (50), and 60 (58) for milk, fat, and protein yield, respectively, indicating that milk components are more sensitive to heat stress. An EL of about $34.5 million per year was estimated. Our findings contribute to an initial investigation into the impact of heat stress on the Canadian dairy industry and provide a basis for genetic studies on heat tolerance.
Structural chemistry at McGill
Authors: Bohle D. Scott , Wharf Ivor , Gaydon Quentin , Kapuku Benita , Bellamare Marie J. , Paul Mirna , Wynter Tamika , Karageorghis Philip J.
Published: March 2022

A brief description of some of the key individuals at McGill University and their contributions to the development of crystallography is given. This is followed by examples of recent structure determinations, which include organic heterocycles, natural products, inorganic salts, and organometallic complexes. Specifically, the bispyridinium adduct of protoporphyrin, the piperidinyl adduct of 3,7-dichloroquinine, trisbenzylmethylthiol, sodium methylarsonium (V), potassium hydroxylamine sulfonate, Vaska’s complex adduct from the oxidative addition of p-tolylmercaptan, and a bis isocyanoiminotriphenylphosphorane adduct of rutheniumdichloridetristriphenylphosphine are described.
Integrating corporate foresight with open innovation: enhancing competitiveness of equipment and technology suppliers to the US forest sector
Authors: Liu Ping , Hansen Eric
Published: March 2022

Equipment and technology suppliers to the United States (US) forest sector are confronting challenges and opportunities to respond to disruptive changes in an increasingly challenging business environment. Integrating corporate foresight (CF) with open innovation (OI) may contribute to enhanced competitiveness of these equipment and technology suppliers in today’s complex business context. Due to its collaborative and interdisciplinary nature, open innovation is crucial for success. Corporate foresight may enhance the ability of firms to implement open innovation, in turn enhancing innovation in the US forest sector through collaboration. This study uses data from a questionnaire-based study to investigate the current state of OI and CF activities that are applied by equipment and technology suppliers to the US forest sector. The results present strengths and weaknesses of OI and CF maturity among respondents and indicate that improved collaboration is necessary for OI management and a culture change must be facilitated for CF management.
Conceptualization of electromagnetic induction at various educational levels: a case study
Authors: Cavinato Michela , Giliberti Elia , Giliberti Marco
Published: March 2022

A vast amount of scientific literature in physics education documents a general widespread difficulty in dealing with electromagnetic induction (EMI) at various levels of instruction. However, to the best of our knowledge, there is a lack of research that compares difficulties with EMI at different educational levels. Here, we discuss a case study of Italian high school students', graduate students', and teachers' conceptualization of some aspects of EMI as a function of the sample instruction level. We analyzed the answers to a multiple choice written questionnaire, adapted from the literature and given to a total of 49 participants. Some difficulties that emerged during the exams of university students while discussing their final project concerning a didactical path about EMI for secondary school are also analyzed. We found that some deep misunderstandings are common at all levels of education and probably come from the very poor link, generally presented in teaching EMI, between Faraday's flux law and the Lorentz force.
AugerPrime - The upgrade of the Pierre Auger Observatory
Authors: Stasielak Jarosław
Published: March 2022

In this paper, ultra-high-energy cosmic rays (UHECRs) are studied with giant ground-based detector systems recording extensive air showers, induced by cosmic ray particles in the atmosphere. Research at the Pierre Auger Observatory — the largest of such detectors ever built — largely contributed to a number of breakthroughs and dramatically advanced our understanding of UHECRs. Nonetheless, the results so far are still inconclusive as neither have the sources of these most energetic particles known in the universe been determined, nor has the origin of the unambiguously established cosmic ray flux suppression above 40 EeV been fully understood. At the same time, precise measurements of the muon component of the extensive air showers on the ground show discrepancies with the predictions of hadronic interaction models. The explanation of these puzzles, which are closely related to each other, is one of the most important goals of modern astrophysics. The results obtained by the Pierre Auger Observatory indicate that further advances in understanding UHECRs require an improvement of the measuring capabilities of existing detectors, where the key feature is a superior separation of the muonic and electromagnetic components of air showers. AugerPrime, the ongoing upgrade of the Pierre Auger Observatory, has been designed for this task. The main objective of the AugerPrime is to enhance the sensitivity of our analyses to the masses of cosmic rays, which will help to elucidate the origin of the UHECRs. In this paper, we overview the main features of the AugerPrime design, its current status and discuss the goals and potential capabilities of the upgraded Observatory.
Correlation between microstructure and corrosion resistance of amorphous Ni–W–P coatings after low-temperature heat treatment
Authors: Zhao Guanlin , Liu Shushuai , Wu Dongting , Zou Yong
Published: March 2022

Amorphous Ni–W–P coatings were prepared by electroless plating and annealed at 250[Formula: see text]C for different times to obtain different microstructures. The local atomic structure of these amorphous coatings was analyzed by calculating the atomic pair distribution function from the XRD patterns. The type of crystals in coatings was obtained from the TEM image and corresponding selected area diffraction (SAED) pattern. The proportion of microscopic particles in the matrix was roughly estimated from the first DSC exothermic peak area. Corrosion resistance in 0.5-M sulfuric acid solution was investigated via electrochemical techniques. Experimental results showed that all annealed coatings still held amorphous structure, albeit the microstructure had been changed. The correlation radius and the atomic number of clusters had increased, especially when the annealed time extended to 12 h and 20 h. The number of microscopic particles in the amorphous matrix also increased with rise in heat treatment time. The type of crystals in these amorphous matrices increased from Ni/Ni (W) to Ni/Ni (W), Ni12P5 and Ni5P4. The decreasing corrosion resistance was in agreement with the increasing number of microscopic particles and higher-order clusters in annealed Ni–W–P coatings. These microscopic particles could form micro-galvanic cells in corrosion solution. The higher-order clusters increased the composition difference in the amorphous matrix, and this also promoted to form micro-galvanic cells in solution.
Baseline Correction Algorithm Based on Catastrophe Point Detection and Lipschitz Exponent’s Analysis
Authors: Tao Weiliang , Liu Yan
Published: March 2022

In order to quantitatively analyze the proportions of independent components in mixtures, it is necessary to extract line spectra corresponding to those components from the spectrum signal of some mixture and evaluate the amplitude of the spectral lines. Multiple factors cause the drift and tilt of a spectrum signal’s baseline, such as environment noises, instrument bias, and sample size, which affect the identification and quantitative analysis of the line spectra superimposed on the baseline. Therefore, the baseline of a spectrum signal should be removed before the line spectra are identified. A baseline correction algorithm based on Catastrophe Point detection and Lipschitz exponent’s analysis is proposed in this paper. With the algorithm, the strong spectral lines are identified and removed, and then the spectral baseline is evaluated without the interference of strong spectrum signals. First, catastrophe points are located based on the local modulus maxima theory of wavelet coefficients. Second, according to the Lipschitz exponent theory, the strong spectral peaks’ regions are identified and removed by a smoothing filter. Then the slowly varying spectrum is segmented adaptively and fitted by the least square fitting method. After the segments are attached and the boundaries are smoothed, the baseline of the spectrum is acquired and extracted finally. The algorithm is more accurate than classical ones because identifying the baseline is implemented after strong peaks are removed, so their influences to baseline extracting are eliminated. The results of experiments show that the algorithm is accurately performed for the spectrum signal of a gas mixture, [Formula: see text].
An Ultra-Fast Authenticated Encryption Scheme with Associated Data Using AES-OTR
Authors: Mancillas-López Cuauhtemoc , Ovilla-Martínez Brisbane
Published: March 2022

Applications relying on the Ethernet IEEE 802.3ba and IEEE802.3b standards require secure data encryption and authentication at extremely high speeds (at least 100 Gbit/s). The Galois/Counter Mode (GCM) is currently considered the de facto standard for hardware high-speed authenticated encryption, although other algorithms have been proposed in the literature such as the Offset Codebook Mode (OCB). The challenge in terms of providing security for high-speed applications is to achieve implementations that explore the parallelism of these algorithms; however, this translates into area cost. In this work, we propose an alternative to GCM and OCB. We show that a combination of the Offset Two-Round authenticated-encryption scheme with the AES block cipher (known as AES-OTR) is exceptionally well suited for exploiting fine-grained parallelism, and can therefore be used to achieve ultra-high-speed data encryption rates. The experiments reported in this paper show that our pipeline-parallel implementation of AES-OTR outperforms the GCM and OCB schemes in terms of throughput per area while using almost half of the logic resources. Our implementation used a Stratix 4 FPGA device as well as several devices from the Virtex family. Implementations of AES-OTR on Stratix 4 used 11kALMs and achieved a throughput of 143.65 Gbit/s. On the Virtex Ultrascale, our design used 31,859 LUTs with a throughput of 204.92 Gbit/s.
BONDING PROPERTIES OF Al/Al2O3 BULK COMPOSITES PRODUCED VIA COMBINED STIR CASTING AND ACCUMULATIVE PRESS BONDING
Authors: JASIM SAADE ABDALKAREEM , VINI M. HEYDARI , DANESHMAND S.
Published: March 2022

In this study, Al/Al2O3 composites have been fabricated by combined stir casting and accumulative press bonding (APB) processes. The effect of APB method on the bonding properties of bulk samples such as the number of APB process, Al2O3[Formula: see text]wt.% and the pressing temperature has been investigated by the peeling test. It is established that stronger bonding with a good quality can be obtained by increasing the pressing temperature and decreasing the Al2O3 particles[Formula: see text]wt.% as the reinforcement. Also, growing the step number of the APB method increases the bonding strength up to step#2 and then reduces the average peeling force due to the strain hardening result of the metallic matrix during the accumulative pressing. Finally, the effect of the APB method on the peeling surface of samples has been investigated using the scanning electron microscopy.
PLANT-LEVEL EVALUATION OF CHINA’S NATIONAL EMISSIONS TRADING SCHEME: BENCHMARK MATTERS
Authors: MA RONG , QIAN HAOQI
Published: March 2022

China’s national emission trading scheme (ETS) started operating in 2021 after four years of preparation. In the initial stage of national ETS, benchmarking approach is one of the hottest topics that have gained sufficient attention. For the reason that benchmarks will greatly affect the permits allocation results and thus affect the effectiveness of the carbon market. This paper attempts to investigate the impacts of the benchmark designs of China’s ETS by using plant-level data. Main results show that the current lax benchmark standards adopted by the national ETS will lead to excess surplus of permits. The whole carbon market will achieve market clearance only when the benchmark standards are set as high as the top 2% efficiency levels. If the carbon price is 200[Formula: see text]yuan/ton, the annual trading volume will be 16.4 billion yuan and 13.2 billion yuan in extra will be spent on carbon offsetting for compliance. If the auction mechanism is introduced, the total market size will significantly increase. The auction revenue will exceed 300 billion yuan when 50% of permits are allocated through auction and will exceed 600 billion yuan when all permits are auctioned. These revenues can provide sufficient funds to accelerate China’s low-carbon transformation as well as improve social welfare.
The Biden Administration’s Indo-Pacific Strategy and China-U.S. Strategic Competition
Authors: Wei Zongyou , Zhang Yunhan
Published: March 2022

The Biden administration has yet to announce its Indo-Pacific strategy, but the overall framework seems all clear: it views China as the main challenger, if not a direct threat, to its political, economic, and military influence in the region, and vows to take diplomatic, economic, and military actions to counterbalance China’s growing influence, preferably with its allies and partners. The Biden administration has taken a series of steps to unite its Asian and even European allies and partners, offered economic alternatives to China’s Belt and Road Initiative (BRI), revamped regional institutional architectures, and tried to shape the regional order to its advantage. As a result, China-U.S. relations have deteriorated further on Biden’s watch and is moving in the direction of confrontation.
Minimizing Latency for Data Aggregation in Wireless Sensor Networks: An Algorithm Approach
Authors: Pham Van-Trung , Nguyen Tu N. , Liu Bing-Hong , Thai My T. , Dumba Braulio , Lin Tong
Published: March 2022

In wireless sensor networks (WSNs), especially in underwater sensor networks, the problem of reporting data to the sink with minimum latency has been widely discussed in many research works. Many studies address using data aggregation to report the same type of data to the sink without data collision in a short period of time. However, due to the rapid development of sensor technology in recent years, a sensor is allowed to have multiple sensing capabilities, that is, it can generate and collect different types of data. Because different types of data have different meanings and required aggregation functions, only the data that belong to the same type are allowed to be aggregated. In addition, due to the interference of the environment or noise, the links in the WSNs are often not bidirectional. This motivates us to study the problem of using minimum latency scheduling to aggregate and report data to the sink without data collision in multiple-data-type WSNs having unidirectional links, which is shown to be NP-hard in the article. The Relative-Collision-Graph-Based Scheduling Algorithm (RCGBSA) is proposed accordingly. Simulations are conducted to demonstrate the performance of the RCGBSA.
Mechanisms for Precise Virtual Time Advancement in Network Emulation
Authors: Babu Vignesh , Nicol David
Published: March 2022

Network emulators enable rapid prototyping and testing of applications. In a typical emulation, the execution order and process execution burst lengths are managed by the host platform’s operating system, largely independent of the emulator. Timerbased mechanisms are typically used, but the imprecision of timer firings introduces imprecision in the advancement of time. This leads to statistical variation in behavior that is not due to the model.

This article describes an open-source tool called Kronos, which provides a set of mechanisms for precise instruction-level tracking of process execution and control over execution order of containers, thus improving the mapping of executed behavior to advancement in time. This, and control of execution and placement of emulated processes in virtual time make the behavior of the emulation independent of the CPU resources of the platform that hosts the emulation. Under Kronos each process has its own virtual clock that is advanced based on a count of the number of

\( \times \)

86 assembly instructions executed by its children. Two types of instruction counting techniques are discussed: (1) hardware-assisted mechanisms that are transparent to the executing application and (2) binary instrumentation-assisted mechanisms that modify the executing binary. We analyze the overheads associated with each approach and experimentally demonstrate the impact of Kronos’ time advancement precision by comparing it against emulations that, like Kronos, are embedded in virtual time, but unlike Kronos rely on Linux timers to control virtual machines and measure their progress in virtual time. We present two useful applications where Kronos aids in generating high-fidelity emulation results at low hardware costs: (1) analyzing protocol performance and (2) enabling analysis of cyber physical control systems. We also discuss limitations associated with simple linear conversions between instruction counts and ascribed virtual time and develop and evaluate more accurate virtual time conversion models.
Initial Responses to False Positives in AI-Supported Continuous Interactions: A Colonoscopy Case Study
Authors: van Berkel Niels , Opie Jeremy , Ahmad Omer F. , Lovat Laurence , Stoyanov Danail , Blandford Ann
Published: March 2022

The use of artificial intelligence (AI) in clinical support systems is increasing. In this article, we focus on AI support for continuous interaction scenarios. A thorough understanding of end-user behaviour during these continuous human-AI interactions, in which user input is sustained over time and during which AI suggestions can appear at any time, is still missing. We present a controlled lab study involving 21 endoscopists and an AI colonoscopy support system. Using a custom-developed application and an off-the-shelf videogame controller, we record participants’ navigation behaviour and clinical assessment across 14 endoscopic videos. Each video is manually annotated to mimic an AI recommendation, being either true positive or false positive in nature. We find that time between AI recommendation and clinical assessment is significantly longer for incorrect assessments. Further, the type of medical content displayed significantly affects decision time. Finally, we discover that the participant’s clinical role plays a large part in the perception of clinical AI support systems. Our study presents a realistic assessment of the effects of imperfect and continuous AI support in a clinical scenario.
Learning Adaptive Spatial-Temporal Context-Aware Correlation Filters for UAV Tracking
Authors: Yuan Di , Chang Xiaojun , Li Zhihui , He Zhenyu
Published: March 2022

Tracking in the unmanned aerial vehicle (UAV) scenarios is one of the main components of target-tracking tasks. Different from the target-tracking task in the general scenarios, the target-tracking task in the UAV scenarios is very challenging because of factors such as small scale and aerial view. Although the discriminative correlation filter (DCF)-based tracker has achieved good results in tracking tasks in general scenarios, the boundary effect caused by the dense sampling method will reduce the tracking accuracy, especially in UAV-tracking scenarios. In this work, we propose learning an adaptive spatial-temporal context-aware (ASTCA) model in the DCF-based tracking framework to improve the tracking accuracy and reduce the influence of boundary effect, thereby enabling our tracker to more appropriately handle UAV-tracking tasks. Specifically, our ASTCA model can learn a spatial-temporal context weight, which can precisely distinguish the target and background in the UAV-tracking scenarios. Besides, considering the small target scale and the aerial view in UAV-tracking scenarios, our ASTCA model incorporates spatial context information within the DCF-based tracker, which could effectively alleviate background interference. Extensive experiments demonstrate that our ASTCA method performs favorably against state-of-the-art tracking methods on some standard UAV datasets.
Recognizing Gaits Across Walking and Running Speeds
Authors: Yao Lingxiang , Kusakunniran Worapan , Wu Qiang , Xu Jingsong , Zhang Jian
Published: March 2022

For decades, very few methods were proposed for cross-mode (i.e., walking vs. running) gait recognition. Thus, it remains largely unexplored regarding how to recognize persons by the way they walk and run. Existing cross-mode methods handle the walking-versus-running problem in two ways, either by exploring the generic mapping relation between walking and running modes or by extracting gait features which are non-/less vulnerable to the changes across these two modes. However, for the first approach, a mapping relation fit for one person may not be applicable to another person. There is no generic mapping relation given that walking and running are two highly self-related motions. The second approach does not give more attention to the disparity between walking and running modes, since mode labels are not involved in their feature learning processes. Distinct from these existing cross-mode methods, in our method, mode labels are used in the feature learning process, and a mode-invariant gait descriptor is hybridized for cross-mode gait recognition to handle this walking-versus-running problem. Further research is organized in this article to investigate the disparity between walking and running. Running is different from walking not only in the speed variances but also, more significantly, in prominent gesture/motion changes. According to these rationales, in our proposed method, we give more attention to the differences between walking and running modes, and a robust gait descriptor is developed to hybridize the mode-invariant spatial and temporal features. Two multi-task learning-based networks are proposed in this method to explore these mode-invariant features. Spatial features describe the body parts non-/less affected by mode changes, and temporal features depict the instinct motion relation of each person. Mode labels are also adopted in the training phase to guide the network to give more attention to the disparity across walking and running modes. In addition, relevant experiments on OU-ISIR Treadmill Dataset A have affirmed the effectiveness and feasibility of the proposed method. A state-of-the-art result can be achieved by our proposed method on this dataset.
A Scalable Quantum Key Distribution Network Testbed Using Parallel Discrete-Event Simulation
Authors: Wu Xiaoliang , Zhang Bo , Chen Gong , Jin Dong
Published: March 2022

Quantum key distribution (QKD) has been promoted as a means for secure communications. Although QKD has been widely implemented in many urban fiber networks, the large-scale deployment of QKD remains challenging. Today, researchers extensively conduct simulation-based evaluations for their designs and applications of large-scale QKD networks for cost efficiency. However, the existing discrete-event simulators offer models for QKD hardware and protocols based on sequential event execution, which limits the scale of the experiments. In this work, we explore parallel simulation of QKD networks to address this issue. Our contributions lay in the exploration of QKD network characteristics to be leveraged for parallel simulation as well as the development of a parallel simulation framework for QKD networks. We also investigate three techniques to improve the simulation performance including (1) a ladder queue based event list, (2) memoization for computationally intensive quantum state transformation information, and (3) optimization of the network partition scheme for workload balance. The experimental results show that our parallel simulator is 10 times faster than a sequential simulator when simulating a 128-node QKD network. Our linear-regression-based network partition scheme can further accelerate the simulation experiments up to two times over using a randomized network partition scheme.
Hypernymy Detection for Low-resource Languages: A Study for Hindi, Bengali, and Amharic
Authors: Jana Abhik , Venkatesh Gopalakrishnan , Yimam Seid Muhie , Biemann Chris
Published: March 2022

Numerous attempts for hypernymy relation (e.g., dog “is-a” animal) detection have been made for resourceful languages like English, whereas efforts made for low-resource languages are scarce primarily due to lack of gold-standard datasets and suitable distributional models. Therefore, we introduce four gold-standard datasets for hypernymy detection for each of the two languages, namely, Hindi and Bengali, and two gold-standard datasets for Amharic. Another major contribution of this work is to prepare distributional thesaurus (DT) embeddings for all three languages using three different network embedding methods (DeepWalk, role2vec, and M-NMF) for the first time on these languages and to show their utility for hypernymy detection. Posing this problem as a binary classification task, we experiment with supervised classifiers like Support Vector Machine, Random Forest, and so on, and we show that these classifiers fed with DT embeddings can obtain promising results while evaluated against proposed gold-standard datasets, specifically in an experimental setup that counteracts lexical memorization. We further incorporate DT embeddings and pre-trained fastText embeddings together using two different hybrid approaches, both of which produce an excellent performance. Additionally, we validate our methodology on gold-standard English datasets as well, where we reach a comparable performance to state-of-the-art models for hypernymy detection.
Skeleton Sequence and RGB Frame Based Multi-Modality Feature Fusion Network for Action Recognition
Authors: Zhu Xiaoguang , Zhu Ye , Wang Haoyu , Wen Honglin , Yan Yan , Liu Peilin
Published: March 2022

Action recognition has been a heated topic in computer vision for its wide application in vision systems. Previous approaches achieve improvement by fusing the modalities of the skeleton sequence and RGB video. However, such methods pose a dilemma between the accuracy and efficiency for the high complexity of the RGB video network. To solve the problem, we propose a multi-modality feature fusion network to combine the modalities of the skeleton sequence and RGB frame instead of the RGB video, as the key information contained by the combination of the skeleton sequence and RGB frame is close to that of the skeleton sequence and RGB video. In this way, complementary information is retained while the complexity is reduced by a large margin. To better explore the correspondence of the two modalities, a two-stage fusion framework is introduced in the network. In the early fusion stage, we introduce a skeleton attention module that projects the skeleton sequence on the single RGB frame to help the RGB frame focus on the limb movement regions. In the late fusion stage, we propose a cross-attention module to fuse the skeleton feature and the RGB feature by exploiting the correlation. Experiments on two benchmarks, NTU RGB+D and SYSU, show that the proposed model achieves competitive performance compared with the state-of-the-art methods while reducing the complexity of the network.
Objective Object Segmentation Visual Quality Evaluation: Quality Measure and Pooling Method
Authors: Shi Ran , Ma Jing , Ngan King Ngi , Xiong Jian , Qiao Tong
Published: March 2022

Objective object segmentation visual quality evaluation is an emergent member of the visual quality assessment family. It aims to develop an objective measure instead of a subjective survey to evaluate the object segmentation quality in agreement with human visual perception. It is an important benchmark for assessing and comparing the performances of object segmentation methods in terms of visual quality. Despite its essential role, sufficient study compared with other visual quality evaluation studies is still lacking. In this article, we propose a novel full-reference objective measure that includes a two-level single object segmentation visual quality measure and a pooling method for multiple object segmentation overall visual quality. The single object segmentation visual quality measure combines a pixel-level sub-measure and a region-level sub-measure for evaluating the similarity of area, shape, and object completeness between the segmentation result and the ground truth in terms of human visual perception. For the proposed multiple object segmentation overall visual quality pooling method, the rank of each object’s segmentation quality as a novel factor is integrated into the weighted harmonic mean to evaluate the overall quality. To evaluate the performance of our proposed measure, we tested it on an object segmentation subjective visual quality assessment database. The experimental results demonstrate that our proposed two-level measure and pooling method with good robustness perform better in matching subjective assessments compared with other state-of-the-art objective measures.
Improving Crowd Density Estimation by Fusing Aerial Images and Radio Signals
Authors: Yang Kai-Wei , Huang Yen-Yun , Huang Jen-Wei , Hsu Ya-Rou , Wan Chang-Lin , Shuai Hong-Han , Wang Li-Chun , Cheng Wen-Huang
Published: March 2022

A recent line of research focuses on crowd density estimation from RGB images for a variety of applications, for example, surveillance and traffic flow control. The performance drops dramatically for low-quality images, such as occlusion, or poor light conditions. However, people are equipped with various wireless devices, allowing the received signals to be easily collected at the base station. As such, another line of research utilizes received signals for crowd counting. Nevertheless, received signals offer only information regarding the number of people, while an accurate density map cannot be derived. As unmanned aerial vehicles (UAVs) are now treated as flying base stations and equipped with cameras, we make the first attempt to leverage both RGB images and received signals for crowd density estimation on UAVs. Specifically, we propose a novel network to effectively fuse the RGB images and received signal strength (RSS) information. Moreover, we design a new loss function that considers the uncertainty from RSS and makes the prediction consistent with the received signals. Experimental results show that the proposed method successfully helps break the limit of traditional crowd density estimation methods and achieves state-of-the-art performance. The proposed dataset is released as a public download for future research.
Deep Illumination-Enhanced Face Super-Resolution Network for Low-Light Images
Authors: Guo Kehua , Hu Min , Ren Sheng , Li Fangfang , Zhang Jian , Guo Haifu , Kui Xiaoyan
Published: March 2022

Face images are typically a key component in the fields of security and criminal investigation. However, due to lighting and shooting angles, faces taken under low-light conditions are often difficult to recognize. Face super-resolution (FSR) technology can restore high-resolution faces based on low-resolution inputs. However, existing face super-resolution methods typically rely on prior knowledge of inaccurate faces estimated from low-resolution images. Faces restored by low-light inputs may suffer from problems such as low brightness and many missing details. In this article, we proposed an Illumination-Enhanced Face Super-Resolution (IEFSR) model that can progressively super-resolve low-light faces of 32 × 32 pixels by an upscaling factor of 8. While reconstructing the low-light low-resolution face into a clear and high-quality face, we introduce a coarse low-resolution (LR) restoration network to recover the LR face details hidden in the dark. In the generator, we use a series of style blocks with noise to make the generated faces appear to have a more realistic visual aesthetic. Additionally, we introduce spectrum normalization in the discriminator to improve training stability. Extensive experimental evaluations show that the proposed IEFSR yields visually and metrically more attractive results than existing state-of-the-art FSR methods.
Answer Questions with Right Image Regions: A Visual Attention Regularization Approach
Authors: Liu Yibing , Guo Yangyang , Yin Jianhua , Song Xuemeng , Liu Weifeng , Nie Liqiang , Zhang Min
Published: March 2022

Visual attention in Visual Question Answering (VQA) targets at locating the right image regions regarding the answer prediction, offering a powerful technique to promote multi-modal understanding. However, recent studies have pointed out that the highlighted image regions from the visual attention are often irrelevant to the given question and answer, leading to model confusion for correct visual reasoning. To tackle this problem, existing methods mostly resort to aligning the visual attention weights with human attentions. Nevertheless, gathering such human data is laborious and expensive, making it burdensome to adapt well-developed models across datasets. To address this issue, in this article, we devise a novel visual attention regularization approach, namely, AttReg, for better visual grounding in VQA. Specifically, AttReg first identifies the image regions that are essential for question answering yet unexpectedly ignored (i.e., assigned with low attention weights) by the backbone model. And then a mask-guided learning scheme is leveraged to regularize the visual attention to focus more on these ignored key regions. The proposed method is very flexible and model-agnostic, which can be integrated into most visual attention-based VQA models and require no human attention supervision. Extensive experiments over three benchmark datasets, i.e., VQA-CP v2, VQA-CP v1, and VQA v2, have been conducted to evaluate the effectiveness of AttReg. As a by-product, when incorporating AttReg into the strong baseline LMH, our approach can achieve a new state-of-the-art accuracy of 60.00% with an absolute performance gain of 7.01% on the VQA-CP v2 benchmark dataset. In addition to the effectiveness validation, we recognize that the faithfulness of the visual attention in VQA has not been well explored in literature. In the light of this, we propose to empirically validate such property of visual attention and compare it with the prevalent gradient-based approaches.
Decoupled Low-Light Image Enhancement
Authors: Hao Shijie , Han Xu , Guo Yanrong , Wang Meng
Published: March 2022

The visual quality of photographs taken under imperfect lightness conditions can be degenerated by multiple factors, e.g., low lightness, imaging noise, color distortion, and so on. Current low-light image enhancement models focus on the improvement of low lightness only, or simply deal with all the degeneration factors as a whole, therefore leading to sub-optimal results. In this article, we propose to decouple the enhancement model into two sequential stages. The first stage focuses on improving the scene visibility based on a pixel-wise non-linear mapping. The second stage focuses on improving the appearance fidelity by suppressing the rest degeneration factors. The decoupled model facilitates the enhancement in two aspects. On the one hand, the whole low-light enhancement can be divided into two easier subtasks. The first one only aims to enhance the visibility. It also helps to bridge the large intensity gap between the low-light and normal-light images. In this way, the second subtask can be described as the local appearance adjustment. On the other hand, since the parameter matrix learned from the first stage is aware of the lightness distribution and the scene structure, it can be incorporated into the second stage as the complementary information. In the experiments, our model demonstrates the state-of-the-art performance in both qualitative and quantitative comparisons, compared with other low-light image enhancement models. In addition, the ablation studies also validate the effectiveness of our model in multiple aspects, such as model structure and loss function.
Towards Integrating Image Encryption with Compression: A Survey
Authors: Singh Kedar Nath , Singh Amit Kumar
Published: March 2022

As digital images are consistently generated and transmitted online, the unauthorized utilization of these images is an increasing concern that has a significant impact on both security and privacy issues; additionally, the representation of digital images requires a large amount of data. In recent years, an image compression scheme has been widely considered; such a scheme saves on hardware storage space and lowers both the transmission time and bandwidth demand for various potential applications. In this article, we review the various approaches taken to consider joint encryption and compression, assessing both their merits and their limitations. In addition to the survey, we also briefly introduce the most interesting and most often utilized applications of image encryption and evaluation metrics, providing an overview of the various kinds of image encryption schemes available. The contribution made by these approaches is then summarized and compared, offering a consideration of the different technical perspectives. Lastly, we highlight the recent challenges and some potential research directions that could fill the gaps in these domains for both researchers and developers.