bluuebunny/crossref_metadata_2025 huggingface dataset:
Multicentre, randomised clinical trial comparing intravitreal aflibercept monotherapy versus aflibercept combined with reduced-fluence photodynamic therapy (RF-PDT) for the treatment of polypoidal choroidal vasculopathy
Authors: Vyas Chinmayi Himanshuroy , Cheung Chui Ming Gemmy , Tan Colin , Chee Caroline , Wong Kelly , Jordan-Yu Janice Marie N. , Wong Tien Yin , Tan Anna , Fenner Beau , Sim Shaun , Teo Kelvin Yi Chong
Published: July 2021

Purpose

To compare the efficacy and safety of intravitreal aflibercept (IVA) monotherapy versus aflibercept combined with reduced-fluence photodynamic therapy (RF-PDT) (IVA+RF-PDT) for the treatment of polypoidal choroidal vasculopathy (PCV).

Methods and analysis

Multicentred, double-masked, randomised controlled trial to compare the two treatment modalities. The primary outcome of the study is to compare the 52-week visual outcome of IVA versus IVA+RF PDT. One hundred and sixty treatment-naïve patients with macular PCV confirmed on indocyanine green angiography will be recruited from three centres in Singapore. Eligible patients will be randomised (1:1 ratio) into one of the following groups: IVA monotherapy group—aflibercept monotherapy with sham photodynamic therapy (n=80); combination group—aflibercept with RF-PDT (n=80). Following baseline visit, all patients will be monitored at 4 weekly intervals during which disease activity will be assessed based on best-corrected visual acuity (BCVA), ophthalmic examination findings, optical coherence tomography (OCT) and angiography where indicated. Eyes that meet protocol-specified retreatment criteria will receive IVA and sham/RF-PDT according to their randomisation group. Primary endpoint will be assessed as change in BCVA at week 52 from baseline. Secondary endpoints will include anatomical changes based on OCT and dye angiography as well as safety assessment. Additionally, we will be collecting optical coherence tomography angiography data prospectively for exploratory analysis.

Ethics and dissemination

This study will be conducted in accordance with the ethical principles that have their origin in the Declaration of Helsinki and that are consistent with the ICH E6 guidelines of Good Clinical Practice and the applicable regulatory requirements. Approval from the SingHealth Centralised Institutional Review Board has been sought prior to commencement of the study.

Trial registration number

NCT03941587.
Variation in treatment preferences of pulmonary exacerbations among Australian and New Zealand cystic fibrosis physicians
Authors: Currie Grace , Tai Anna , Snelling Tom , Schultz André
Published: July 2021

Background

Despite advances in cystic fibrosis (CF) management and survival, the optimal treatment of pulmonary exacerbations remains unclear. Understanding the variability in treatment approaches among physicians might help prioritise clinical uncertainties to address through clinical trials.

Methods

Physicians from Australia and New Zealand who care for people with CF were invited to participate in a web survey of treatment preferences for CF pulmonary exacerbations. Six typical clinical scenarios were presented; three to paediatric and another three to adult physicians. For each scenario, physicians were asked to choose treatment options and provide reasons for their choices.

Results

Forty-nine CF physicians (31 paediatric and 18 adult medicine) participated; more than half reported 10+ years of experience. There was considerable variation in primary antibiotic selection; none was preferred by more than half of respondents in any scenario. For secondary antibiotic therapy, respondents consistently preferred intravenous tobramycin and a third antibiotic was rarely prescribed, except in one scenario describing an adult patient. Hypertonic saline nebulisation and twice daily chest physiotherapy was preferred in most scenarios while dornase alfa use was more variable. Most CF physicians (>80%) preferred to change therapy if there was no early response. Professional opinion was the most common reason for antibiotic choice.

Conclusions

Variation exists among CF physicians in their preferred choice of primary antibiotic and use of dornase alfa. These preferences are driven by professional opinion, possibly reflecting a lack of evidence to base policy recommendations. Evidence from high-quality clinical trials is needed to inform physician decision making.
Recurrent syncope from parapharyngeal cancer
Authors: Howard Mark
Published: July 2021

The glossopharyngeal nerve is a cause of reflex bradycardia and syncope in patients with head and neck cancer. These clinical syndromes are rare but can be debilitating with variation in clinical presentation. The underlying mechanism is often incorrectly assumed to be carotid sinus hypersensitivity due to the cancerous lesion; however, examples in the literature also report the effect on the glossopharyngeal nerve or its branches by parapharyngeal lesions. We report two such cases known to a palliative care service. The symptomatic treatment options were limited due to patients’ frailty. Both patients experienced some reduction in their syncopal symptoms with anticholinergic agents.
Novel personalized cancer vaccine platform based on Bacillus Calmette-Guèrin
Authors: Ylösmäki Erkko , Fusciello Manlio , Martins Beatriz , Feola Sara , Hamdan Firas , Chiaro Jacopo , Ylösmäki Leena , Vaughan Matthew J , Viitala Tapani , Kulkarni Prasad S , Cerullo Vincenzo
Published: July 2021

Background

Intratumoral BCG therapy, one of the earliest immunotherapies, can lead to infiltration of immune cells into a treated tumor. However, an increase in the number of BCG-induced tumor-specific T cells in the tumor microenvironment could lead to enhanced therapeutic effects.

Methods

Here, we have developed a novel cancer vaccine platform based on BCG that can broaden BCG-induced immune responses to include tumor antigens. By physically attaching tumor-specific peptides onto the mycobacterial outer membrane, we were able to induce strong systemic and intratumoral T cell-specific immune responses toward the attached tumor antigens. These therapeutic peptides can be efficiently attached to the mycobacterial outer membrane using a poly-lysine sequence N-terminally fused to the tumor-specific peptides.

Results

Using two mouse models of melanoma and a mouse model of colorectal cancer, we observed that the antitumor immune responses of BCG could be improved by coating the BCG with tumor-specific peptides. In addition, by combining this novel cancer vaccine platform with anti-programmed death 1 (anti-PD-1) immune checkpoint inhibitor (ICI) therapy, the number of responders to anti-PD-1 immunotherapy was markedly increased.

Conclusions

This study shows that intratumoral BCG immunotherapy can be improved by coating the bacteria with modified tumor-specific peptides. In addition, this improved BCG immunotherapy can be combined with ICI therapy to obtain enhanced tumor growth control. These results warrant clinical testing of this novel cancer vaccine platform.
Identification of neoantigen-reactive T lymphocytes in the peripheral blood of a patient with glioblastoma
Authors: Leko Vid , Cafri Gal , Yossef Rami , Paria Biman , Hill Victoria , Gurusamy Devikala , Zheng Zhili , Gartner Jared J , Prickett Todd D , Goff Stephanie L , Robbins Paul , Lu Yong-Chen , Rosenberg Steven A
Published: July 2021

The adoptive transfer of naturally occurring T cells that recognize cancer neoantigens has led to durable tumor regressions in select patients with cancer. However, it remains unknown whether such T cells can be isolated from and used to treat patients with glioblastoma, a cancer that is refractory to currently available therapies. To answer this question, we stimulated patient blood-derived memory T cells in vitro using peptides and minigenes that represented point mutations unique to patients’ tumors (ie, candidate neoantigens) and then tested their ability to specifically recognize these mutations. In a cohort of five patients with glioblastoma, we found that circulating CD4+ memory T cells from one patient recognized a cancer neoantigen harboring a mutation in the EED gene (EEDH189N) that was unique to that patient’s tumor. This finding suggests that neoantigen-reactive T cells could indeed be isolated from patients with glioblastoma, thereby providing a rationale for further efforts to develop neoantigen-directed adoptive T cell therapy for this disease.
Ultrasound-guided genicular nerve blocks following total knee arthroplasty: a randomized, double-blind, placebo-controlled trial
Authors: Rambhia Milly , Chen An , Kumar Amanda H , Bullock W Michael , Bolognesi Michael , Gadsden Jeffrey
Published: July 2021

Introduction

Local anesthetic blockade of the genicular nerves, known targets of radiofrequency ablative techniques for knee pain, has not previously been studied in a randomized controlled trial evaluating acute pain after knee arthroplasty. We hypothesized that genicular nerve blockade added to an existing block regimen in total knee arthroplasty would result in a reduction in 24 hours opioid consumption.

Methods

Patients (American Society of Anesthesiologists 1–3, aged 18–85 years) undergoing primary total knee arthroplasty were randomized to receive single-injection nerve blocks of the superolateral, superomedial, and inferomedial genicular nerves with injectate (15 mL 0.25% bupivacaine and 2 mg dexamethasone or 15 mL saline placebo). All subjects received a standard oral analgesic regimen, spinal anesthetic with 12.5 mg isobaric bupivacaine, infiltration between the popliteal artery and capsule of the knee with 0.2% ropivacaine, and postoperative adductor canal perineural infusion with 0.2% ropivacaine. The primary outcome was 24 hours opioid consumption (measured in morphine milliequivalents).

Results

Forty (40) subjects were enrolled. Opioid consumption at 24 hours was significantly lower in the BLOCK group compared with the SHAM group (23±20 vs 58±35, p<0.001), and this difference remained significant at 48 hours (50±40 vs 98±56, p=0.004). Pain scores were reduced in the BLOCK group at time 6 hours (2.6±1.9 vs 4.3±2.2, p=0.012), but were otherwise similar at remaining time points. Patient satisfaction at 24 hours and 20 m walk test times were similar between groups.

Discussion

Genicular nerve blockade was associated with a reduction in opioid consumption at 24 hours in primary total knee arthroplasty patients.

Trial registration number

NCT03706313.
Modelling the impact of plain packaging of tobacco products on cardiovascular disease in Argentina
Authors: Salgado M. Victoria , Penko Joanne , Fernandez Alicia , Mejia Raul
Published: July 2021

Introduction

Tobacco packaging design is conceived to be attractive. Plain packaging of tobacco products reduces this attractiveness by standardising their shape, size, font and colours.

Methods

To evaluate the effect of applying plain packaging to tobacco products on cardiovascular events and mortality in Argentina, we used the Cardiovascular Disease Policy Model–Argentina, a local adaptation of a well-established computer simulation model that projects cardiovascular and mortality events for the population 35–94 years old using local demographic and consumption data, during the period 2015–2024. After a literature review, we estimated that the implementation of plain packaging of tobacco products would result in an absolute decrease in tobacco prevalence of 0.55% (base-case scenario) and performed a sensitivity analysis assuming a higher and lower decrease of 1.01% and 0.095%, respectively.

Results

Over the 2015–2024 period, the decrease in smoking prevalence associated with plain packaging (0.55%) is projected to avert 1880 myocardial infarctions (MI), 820 strokes and 4320 total deaths in Argentina. The higher estimate of smoking prevalence reduction (1.01%) would translate into 3450 fewer MIs, 1490 fewer strokes and 7920 fewer deaths, while the lower estimate of smoking prevalence reduction (0.095%) would result in 330 fewer MIs, 140 fewer strokes and 750 fewer deaths.

Conclusions

The implementation of plain packaging of tobacco products could reduce cardiovascular events in Argentina, even in the absence of other tobacco control measures. Actual health benefits are likely higher than those presented here, since plain packaging may be most impactful by preventing young people from initiating smoking.
Postoperative complications of endovascular blunt thoracic aortic injury repair
Authors: Abdou Hossam , Elansary Noha N , Darko Louisa , DuBose Joseph J , Scalea Thomas M , Morrison Jonathan J , Kundi Rishi
Published: July 2021

Background

Thoracic endovascular aortic repair (TEVAR) has become the standard of care for thoracic aortic aneurysms and increasingly for blunt thoracic aortic injury (BTAI). Postoperative complications, including spinal cord ischemia and paraplegia, have been shown to be less common with elective TEVAR than with open thoracic or thoracoabdominal repair. Although small cohort studies exist, the postoperative complications of endovascular repair of traumatic aortic injury have not been described through large data set analysis.

Methods

A retrospective cohort analysis was performed of the American College of Surgeons Trauma Quality Improvement Program registry spanning from 2007 to 2017. All patients with BTAI who underwent TEVAR, as indicated by the Abbreviated Injury Scale or the International Classification of Diseases (ICD-9 or ICD-10), were included. Categorical data were presented as proportions and continuous data as mean and SD. OR was calculated for each postoperative complication.

Results

2990 patients were identified as having undergone TEVAR for BTAI. The postoperative incidence of stroke was 2.8% (83), and 4.7% (140) of patients suffered acute kidney injury or renal failure. The incidence of spinal cord ischemia was 1.9% (58), whereas 0.2% (7) of patients suffered complete paraplegia. Renal events and stroke were found to occur significantly more frequently in those undergoing TEVAR (OR 1.758, 1.449–2.134 and OR 2.489, 1.917–3.232, respectively). Notably, there was no difference between TEVAR and non-operative BTAI incidences of spinal cord ischemia or paraplegia (OR 1.061, 0.799–1.409 and OR 1.698, 0.728–3.961, respectively).

Discussion

Postoperative intensive care unit care of patients after BTAI has historically focused on awareness of spinal cord ischemia. Our analysis suggests that after endovascular repair of blunt aortic trauma, care should involve vigilance primarily against postoperative cerebrovascular and renal events. Further study is warranted to develop guidelines for the intensivist managing patients after TEVAR for BTAI.

Level of evidence

Level III.
Response of lentil cultivars to Sclerotinia white mold and Botrytis grey mold infection under irrigated and dryland conditions
Authors: Kader Kazi A. , Erickson R. Scott , Bowness (Davidson) Robyne , Olson Mark , Chatterton Syama
Published: July 2021

Diseases such as Sclerotinia white mold (SWM), caused by the fungus Sclerotinia sclerotiorum (Lib.) de Bary, and Botrytis grey mold (BGM), caused by the fungus Botrytis cinerea Pers., may be limiting factors for lentil production in wetter areas of Alberta, Canada. Field trials were conducted at the Lethbridge Research and Development Centre from 2013 to 2015 to evaluate the response of lentil cultivars to SWM and BGM and yield impacts. Ten lentil cultivars from five market classes were evaluated under irrigated and dryland plots with two planting densities (120 and 160 plants·m−2). Year and irrigation had the largest effect on disease incidence, with highest SWM incidence occurring under irrigation in 2013, followed by 2014 and 2015. Conversely, BGM incidence under irrigation was highest in 2015 and lowest in 2013, but levels were lower than SWM. Significantly (P < 0.05) lower disease incidences were observed in dryland plots, which also produced higher yield than irrigated plots. Cultivars varied significantly in SWM incidence and yield under irrigated and dryland conditions, perhaps due to variable disease pressure, but there was no consistent trend in cultivar performance. BGM incidence was similar in cultivars, but differed among years. These findings indicate that SWM may be a limiting factor to lentil production in wetter areas, as the 10 cultivars from five market classes tested were all highly susceptible to SWM.
A soil health scoring framework for arable cropping systems in Saskatchewan, Canada
Authors: Wu Qianyi , Congreves Kate A.
Published: July 2021

Farmers are looking for appropriate tools for assessing and interpreting the health status of their soils; however, there is no standardized and prairie-based soil health scoring framework. Accordingly, we focused on developing one for arable cropping systems in Saskatchewan. In 2018, soil samples (0–15, 15–30, and 30–60 cm depths) were collected from 55 arable fields across Saskatchewan, along with native prairie samples. Various soil chemical, physical, and biological attributes were measured (23 attributes in total). Based on the data distribution for each attribute, we developed scoring functions. The results from multivariate analyses were used to determine the weighting factors needed to integrate the individual scores from each soil attribute into a single Saskatchewan Assessment of Soil Health score. Soil carbon (C) and nitrogen (N) indices (soil organic C, active C, total N, and soil protein) and total phosphorus produced the highest weighting factors. We also tested if there were linkages between the soil health and crop productivity by assessing the cereal yields for the past 10 years as reported from the same rural municipalities where the soil samples were collected. A positive relationship between soil health and yields was most apparent during dry years; thus, we recommend further research to explore this linkage at a finer scale. Overall, this research forms the foundation of a promising framework that can be built upon, and in due course, lead to the development of a tool for producers who are interested in tracking soil health and using the results to inform management.
Open quantum systems for quarkonia
Authors: Yao Xiaojun
Published: July 2021

I review recent applications of the open quantum system framework in the understanding of quarkonium suppression in heavy-ion collisions, which has been used as a probe of the quark–gluon plasma for decades. The derivation of the Lindblad equations for quarkonium in both the quantum Brownian motion and the quantum optical limits and their semiclassical counterparts is explained. The hierarchy of time scales assumed in the derivation is justified from the separation of energy scales in nonrelativistic effective field theories of QCD. Physical implications of the open quantum system approach are also discussed. Finally, I list some open questions for future studies.
Experimental prediction of internal defects according to defect area on NDI via water absorption behavior
Authors: Lee Kyo-Moon , Park Soo-Jeong , Yu Tianyu , Park Seong-Jae , Kim Yun-Hae
Published: July 2021

This study analyzed the relationship between the defect area identified through a C-scan and the void volume in CF-PEKK composite materials through the water absorption behavior to predict the void volume. The water absorption content varies with the defect area; however, the defect area identified through a C-scan and the water absorption content did not show a proportional relationship. This is because voids are distributed in the through-thickness. The results indicated that the absorption behavior could be used to predict the void volume. Irreversible absorption was found to be independent of the void volume. Further, no matrix degradation was seen with water immersion at [Formula: see text]C; however, some local swelling was seen.
Effect of indenter tip radius on indentation hardness by finite element analysis
Authors: Oda Kazuhiro , Tsutsumi Noriko , Morita Kohei , Tsutsumi Takahiro , Zhong Hou
Published: July 2021

In this study, the indentation hardness test is performed by elastic-plastic finite element (FE) analysis. In order to investigate the effect of the wear of indenter tip on the load-penetration depth curve ([Formula: see text] curve), indentation simulation is made by changing the indenter tip radius. The [Formula: see text] curve obtained by finite element method (FEM) is in good agreement with the experimental results. The calculation shows that the indentation plastic work [Formula: see text] corresponding to the area in the [Formula: see text] curve is hardly affected by the indenter tip radius.
Induction of floquet topological phases in honeycomb nanoribbon irradiated by circularly polarized laser field
Authors: Kang Chol Jun , Jo Mun Gwon
Published: July 2021

The stability of the existence of the topological properties even in non-equilibrium condition such as irradiation of external time-periodic perturbation paves the way for designing and controlling the properties of materials. We study the change in the structure of the quasi-energy spectrum under the influence of the circularly polarized laser field with various intensities. The system is two-dimensional honeycomb nanoribbon of having zig-zag edges. Two cases where the onsite energies are present and absent are considered. We find that the topological phase transitions occur at some critical intensities of the laser field in both cases, which are recognized by the gap closing, the appearance of two crossing edge states, and sudden raise of the first Chern number from 0 to 1. The critical laser intensity is raised when either the frequency increases or the width of the ribbon decreases. Furthermore, band folding is observed in low-frequency domain in the quasi-energy spectrum and becomes more pronounced for the lower frequencies.
Low-temperature thermodynamic properties of the Heisenberg antiferromagnetic chain with two easy-axis single-ion anisotropies
Authors: Chen Yuan , Liao Yun , Li Wenan
Published: July 2021

In this paper, the spin wave theory is applied to the one-dimensional Heisenberg antiferromagnet in the coexistence of two different anisotropies [Formula: see text] and [Formula: see text], which are separately the easy-axis single-ion anisotropies for sublattice A and sublattice B of the system. Both the ground-state and low-temperature properties of the system are strongly affected by the competition between these two anisotropies. Two kinds of the competition in terms of the deviation parameter [Formula: see text] are discussed for the uniform anisotropy taking the values of [Formula: see text] and [Formula: see text], respectively. The [Formula: see text]-dependent behaviors (such as the power, exponential and linear laws) are obtained for the total magnetization, the staggered magnetizations, the internal energy, the specific heat and the susceptibility. It is found that at zero-temperature, the interplay between these two anisotropies induces the antiferromagnetic-disorder phase transition in the small anisotropy region with [Formula: see text]. For the selected cases of [Formula: see text], our results for are in agreement with the findings obtained by the existing theories and the quantum Monte Carlo data.
Thermal aspects of Oldroyd-B nanofluid over accelerated surface with variable thermal conductivity and modified diffusion theories
Authors: Aziz Samaira , Ahmad Iftikhar , Khan Sami Ullah , Ali Nasir
Published: July 2021

The growing interest in emerging nanotechnologies has led the scientists towards to investigate the interaction of nanoparticles with fluids. Current continuation endeavors the rheological analysis for the Oldroyd-B nanomaterial across periodically accelerated and heated surface. The interesting features of thermophoresis and Brownian motions are presented by following famous Buongiorno nanofluid model. Further, Cattaneo–Christov heat and mass flux expressions are exploited to determine the characteristics of thermal and mass diffusions. As a novelty, the variable thermal conductivity and heat absorption/generation consequences are also utilizing the energy equation. The flow model has been developed by using concerning boundary layer equations which are converted into dimensionless forms by using appropriate variables. The analytical solution of such transmuted equations is computed by using homotopy analytic method. Various physical parameters of interest are scrutinized through various graphs. The observations from analysis convey a declining change in nanofluid concentration and temperature with variation of thermal and solutal relaxation parameters, respectively. Moreover, thermophoresis parameter causes an enhancement of concentration profile while a retarded concentration profile results with increment of Schmidt number. The obtained theoretical results reflect significant applications in cooling and heating systems, thermal sciences, manufacturing processes, extrusion systems, enhancement of transport of energy and heat resources.
DFT study of structural, elastic, electronic, magnetic, thermal and transport properties of new multifunctional NiVSn half-Heusler for spintronic and thermoelectric applications
Authors: Bouldiab Y. , Terkhi S. , Aziz Z. , Bendahma F. , Bennani M. A. , Bentata R. , Boudjeltia M. A.
Published: July 2021

In this work, the first-principles density functional calculations of the structural, elastic, electronic, magnetic, thermal and thermoelectric properties of NiVSn half-Heusler compound are carried out. The exchange and correlation potential are treated by using Generalized Gradient approximation of Perdew, Burke and Ernzerhof (GGA-PBE), GGA plus Tran–Blaha-modified Becke–Johnson (mBJ-GGA) approach and mBJ-GGA+U where U is the Hubbard on-site Coulomb interaction correction (mBJ-GGA+U). Structural calculations revealed that NiVSn is stable in type 1 structure ferromagnetic state. Elastic properties show that our compound is mechanically stable, ductile and anisotropic. The results of the band structures and density of states display a half metallic behavior of NiVSn with an indirect bandgap of 0.476, 0.508 and 0.845 eV by using GGA-PBE, mBJ-GGA, and mBJ-GGA+U, respectively. The total magnetic moment calculated is integer of 1 [Formula: see text]B confirming a half metallic behavior of NiVSn and follows the well-known Slater–Pauling rule ([Formula: see text]); therefore, the studied compound is suitable for application in spintronic fields. The thermodynamic properties such as bulk modulus, the heat capacity, the Debye temperature, and the thermal expansion coefficient are investigated using quasi-harmonic Debye model (QHDM). The thermal results show that NiVSn can be applied in extreme temperature and pressure conditions. The thermoelectric properties are studied employing the BoltzTrap code. The calculated transport properties are very interesting for the spin-down channel with high electrical conductivity, high Seebeck coefficient, and figure of merit value approaching unity. As a result, the half-Heusler alloy NiVSn is a promoter for conventional thermoelectric materials.
Dynamic Selective Edge-Based Integer/Fractional-Order Partial Differential Equation for Degraded Document Image Binarization
Authors: Nnolim Uche A.
Published: July 2021

Conventional thresholding algorithms have had limited success with degraded document images. Recently, partial differential equations (PDEs) have been applied with good results. However, these are usually tailored to handle relatively few specific distortions. In this study, we combine an edge detection term with a linear binarization source term in a PDE formulation. Additionally, a new proposed diffusivity function further amplifies desired edges. It also suppresses undesired edges that comprise bleed-through effects. Furthermore, we develop the fractional variant of the proposed scheme, which further improves results and provides more flexibility. Moreover, nonlinear color spaces are utilized to improve binarization results for images with color distortion. The proposed scheme removes document image degradation such as bleed-through, stains, smudges, etc., and also restores faded text in the images. Experimental subjective and objective results show consistently superior performance of the proposed approach compared to the state-of-the-art PDE-based models.
The probability that a pair of group elements is 2-Engel
Authors: Khoshtarash Raheleh , Moghaddam Mohammad Reza R. , Rostamyari Mohammad Amin
Published: July 2021

In 2016, the second and third authors introduced the notion of 2-Engelizer of an element [Formula: see text] in a given group [Formula: see text] and the set of all such [Formula: see text]-Engelizers in [Formula: see text] denoted by [Formula: see text]. In this paper, among other results, we construct some upper and lower bounds for the probability of randomly chosen a pair of elements of a finite group to be [Formula: see text]-Engel.
Evolution of ultrapotassic volcanism on the Kaapvaal craton: deepening the orangeite versus lamproite debate
Authors: Tappe Sebastian , Shaikh Azhar M. , Wilson Allan H. , Stracke Andreas
Published: July 2021

Orangeites are a significant source of diamonds, yet ambiguity surrounds their status among groups of mantle-derived potassic rocks. This study reports mineralogical and geochemical data for a
c.
140 Ma orangeite dyke swarm that intersects the Bushveld Complex on the Kaapvaal craton in South Africa. The dykes comprise distinctive petrographic varieties that are linked principally by olivine fractionation, with the most evolved members containing minor amounts of primary carbonate, sanidine and andradite garnet in the groundmass. Although abundant groundmass phlogopite and clinopyroxene have compositions that are similar to those of cratonic lamproites, these phases show notable Ti-depletion, which we consider a hallmark feature of type orangeites from the Kaapvaal craton. Ti-depletion is also characteristic of bulk rock compositions and is associated with strongly depleted Th–U–Nb–Ta contents at high Cs–Rb–Ba–K concentrations. The resultant high large ion lithophile element/high field strength element ratios of orangeites suggest that mantle source enrichment occurred by metasomatic processes in the proximity of ancient subduction zones. The Bushveld-intersecting orangeite dykes have strongly enriched Sr–Nd–Hf isotopic compositions (initial
87
Sr/
86
Sr = 0.70701–0.70741;
ε
Nd = −10.6 to −5.8;
ε
Hf = −14.4 to −2.5), similar to those of other orangeites from across South Africa. Combined with the strong Ti–Nb–Ta depletion, this ubiquitous isotopic feature points to the involvement of ancient metasomatized mantle lithosphere in the origin of Kaapvaal craton orangeites, where K-rich metasomes imparted a ‘fossil’ subduction geochemical signature. Previous geochronology studies identified ancient K-enrichment events within the Kaapvaal cratonic mantle lithosphere, possibly associated with collisional tectonics during the 1.2–1.1 Ga Namaqua–Natal orogeny of the Rodinia supercontinent cycle. It therefore seems permissible that the cratonic mantle root was preconditioned for ultrapotassic magma production by tectonomagmatic events that occurred along convergent plate margins during the Proterozoic. However, reactivation of the K-rich metasomes had to await establishment of an extensional tectonic regime, such as that during the Mesozoic breakup of Gondwana, which was accompanied by widespread (1000 × 750 km) small-volume orangeite volcanism between 200 and 110 Ma. Although similarities exist between orangeites and lamproites, these and other potassic rocks are sufficiently distinct in their compositions such that different magma formation processes must be considered. In addition to new investigations of the geodynamic triggers of K-rich ultramafic magmatism, future research should more stringently evaluate the relative roles of redox effects and volatile components such as H
2
O–CO
2
–F in the petrogeneses of these potentially diamondiferous alkaline rocks.
Saliency-Aware Class-Agnostic Food Image Segmentation
Authors: Yarlagadda Sri Kalyan , Montserrat Daniel Mas , Güera David , Boushey Carol J. , Kerr Deborah A. , Zhu Fengqing
Published: July 2021

Advances in image-based dietary assessment methods have allowed nutrition professionals and researchers to improve the accuracy of dietary assessment, where images of food consumed are captured using smartphones or wearable devices. These images are then analyzed using computer vision methods to estimate energy and nutrition content of the foods. Food image segmentation, which determines the regions in an image where foods are located, plays an important role in this process. Current methods are data dependent and thus cannot generalize well for different food types. To address this problem, we propose a class-agnostic food image segmentation method. Our method uses a pair of eating scene images, one before starting eating and one after eating is completed. Using information from both the before and after eating images, we can segment food images by finding the salient missing objects without any prior information about the food class. We model a paradigm of top-down saliency that guides the attention of the human visual system based on a task to find the salient missing objects in a pair of images. Our method is validated on food images collected from a dietary study that showed promising results.
Imaging with Local Speckle Intensity Correlations: Theory and Practice
Authors: Alterman Marina , Bar Chen , Gkioulekas Ioannis , Levin Anat
Published: July 2021

Recent advances in computational imaging have significantly expanded our ability to image through scattering layers such as biological tissues by exploiting the auto-correlation properties of captured speckle intensity patterns. However, most experimental demonstrations of this capability focus on the far-field imaging setting, where obscured light sources are very far from the scattering layer. By contrast, medical imaging applications such as fluorescent imaging operate in the near-field imaging setting, where sources are inside the scattering layer. We provide a theoretical and experimental study of the similarities and differences between the two settings, highlighting the increased challenges posed by the near-field

setting. We then draw insights from this analysis to develop a new algorithm for imaging through scattering that is tailored to the near-field setting by taking advantage of unique properties of speckle patterns formed under this setting, such as their local support. We present a theoretical analysis of the advantages of our algorithm and perform real experiments in both far-field and near-field configurations, showing an order-of magnitude expansion in both the range and the density of the obscured patterns that can be recovered.
Chronic Pain Protective Behavior Detection with Deep Learning
Authors: Wang Chongyang , Olugbade Temitayo A. , Mathur Akhil , Williams Amanda C. DE C. , Lane Nicholas D. , Bianchi-Berthouze Nadia
Published: July 2021

In chronic pain rehabilitation, physiotherapists adapt physical activity to patients’ performance based on their expression of protective behavior, gradually exposing them to feared but harmless and essential everyday activities. As rehabilitation moves outside the clinic, technology should automatically detect such behavior to provide similar support. Previous works have shown the feasibility of automatic protective behavior detection (PBD) within a specific activity. In this article, we investigate the use of deep learning for PBD across activity types, using wearable motion capture and surface electromyography data collected from healthy participants and people with chronic pain. We approach the problem by continuously detecting protective behavior within an activity rather than estimating its overall presence. The best performance reaches mean F1 score of 0.82 with leave-one-subject-out cross validation. When protective behavior is modeled per activity type, performance achieves a mean F1 score of 0.77 for bend-down, 0.81 for one-leg-stand, 0.72 for sit-to-stand, 0.83 for stand-to-sit, and 0.67 for reach-forward. This performance reaches excellent level of agreement with the average experts’ rating performance suggesting potential for personalized chronic pain management at home. We analyze various parameters characterizing our approach to understand how the results could generalize to other PBD datasets and different levels of ground truth granularity.
Can Chatbots Help Support a Person’s Mental Health? Perceptions and Views from Mental Healthcare Professionals and Experts
Authors: Sweeney Colm , Potts Courtney , Ennis Edel , Bond Raymond , Mulvenna Maurice D. , O’neill Siobhan , Malcolm Martin , Kuosmanen Lauri , Kostenius Catrine , Vakaloudis Alex , Mcconvey Gavin , Turkington Robin , Hanna David , Nieminen Heidi , Vartiainen Anna-Kaisa , Robertson Alison , Mctear Michael F.
Published: July 2021

The objective of this study was to understand the attitudes of professionals who work in mental health regarding the use of conversational user interfaces, or chatbots, to support people’s mental health and wellbeing. This study involves an online survey to measure the awareness and attitudes of mental healthcare professionals and experts. The findings from this survey show that more than half of the participants in the survey agreed that there are benefits associated with mental healthcare chatbots (65%, p < 0.01). The perceived importance of chatbots was also relatively high (74%, p < 0.01), with more than three-quarters (79%, p < 0.01) of respondents agreeing that mental healthcare chatbots could help their clients better manage their own health, yet chatbots are overwhelmingly perceived as not adequately understanding or displaying human emotion (86%, p < 0.01). Even though the level of personal experience with chatbots among professionals and experts in mental health has been quite low, this study shows that where they have been used, the experience has been mostly satisfactory. This study has found that as years of experience increased, there was a corresponding increase in the belief that healthcare chatbots could help clients better manage their own mental health.
Specializing FGPU for Persistent Deep Learning
Authors: Ma Rui , Hsu Jia-Ching , Tan Tian , Nurvitadhi Eriko , Sheffield David , Pelt Rob , Langhammer Martin , Sim Jaewoong , Dasu Aravind , Chiou Derek
Published: July 2021

Overlay architectures are a good way to enable fast development and debug on FPGAs at the expense of potentially limited performance compared to fully customized FPGA designs. When used in concert with hand-tuned FPGA solutions, performant overlay architectures can improve time-to-solution and thus overall productivity of FPGA solutions. This work tunes and specializes FGPU, an open source OpenCL-programmable GPU overlay for FPGAs. We demonstrate that our
persistent deep learning
(PDL
)-FGPU architecture maintains the ease-of-programming and generality of GPU programming while achieving high performance from specialization for the persistent deep learning domain. We also propose an easy method to specialize for other domains. PDL-FGPU includes new instructions, along with micro-architecture and compiler enhancements. We evaluate both the FGPU baseline and the proposed PDL-FGPU on a modern high-end Intel Stratix 10 2800 FPGA in simulation running persistent DL applications (RNN, GRU, LSTM), and non-DL applications to demonstrate generality. PDL-FGPU requires 1.4–3× more ALMs, 4.4–6.4× more M20ks, and 1–9.5× more DSPs than baseline, but improves performance by 56–693× for PDL applications with an average 23.1% degradation on non-PDL applications. We integrated the PDL-FGPU overlay into Intel OPAE to measure real-world performance/power and demonstrate that PDL-FGPU is only 4.0–10.4× slower than the Nvidia V100.
“I See What You Did There”
Authors: Schadenberg Bob R. , Reidsma Dennis , Heylen Dirk K. J. , Evers Vanessa
Published: July 2021

Unpredictability in robot behaviour can cause difficulties in interacting with robots. However, for social interactions with robots, a degree of unpredictability in robot behaviour may be desirable for facilitating engagement and increasing the attribution of mental states to the robot. To generate a better conceptual understanding of predictability, we looked at two facets of predictability, namely, the ability to predict robot actions and the association of predictability as an attribute of the robot. We carried out a video human-robot interaction study where we manipulated whether participants could either see the cause of a robot’s responsive action or could not see this, because there was no cause, or because we obstructed the visual cues. Our results indicate that when the cause of the robot’s responsive actions was not visible, participants rated the robot as more unpredictable and less competent, compared to when it was visible. The relationship between seeing the cause of the responsive actions and the attribution of competence was partially mediated by the attribution of unpredictability to the robot. We argue that the effects of unpredictability may be mitigated when the robot identifies when a person may not be aware of what the robot wants to respond to and uses additional actions to make its response predictable.
Fast Video Facial Expression Recognition by a Deeply Tensor-Compressed LSTM Neural Network for Mobile Devices
Authors: Zhen Peining , Chen Hai-Bao , Cheng Yuan , Ji Zhigang , Liu Bin , Yu Hao
Published: July 2021

Mobile devices usually suffer from limited computation and storage resources, which seriously hinders them from deep neural network applications. In this article, we introduce a deeply tensor-compressed long short-term memory (LSTM) neural network for fast video-based facial expression recognition on mobile devices. First, a spatio-temporal facial expression recognition LSTM model is built by extracting time-series feature maps from facial clips. The LSTM-based spatio-temporal model is further deeply compressed by means of quantization and tensorization for mobile device implementation. Based on datasets of Extended Cohn-Kanade (CK+), MMI, and Acted Facial Expression in Wild 7.0, experimental results show that the proposed method achieves 97.96%, 97.33%, and 55.60% classification accuracy and significantly compresses the size of network model up to 221× with reduced training time per epoch by 60%. Our work is further implemented on the RK3399Pro mobile device with a Neural Process Engine. The latency of the feature extractor and LSTM predictor can be reduced 30.20× and 6.62× , respectively, on board with the leveraged compression methods. Furthermore, the spatio-temporal model costs only 57.19 MB of DRAM and 5.67W of power when running on the board.
A Novel Insider Attack and Machine Learning Based Detection for the Internet of Things
Authors: Chowdhury Morshed , Ray Biplob , Chowdhury Sujan , Rajasegarar Sutharshan
Published: July 2021

Due to the widespread functional benefits, such as supporting internet connectivity, having high visibility and enabling easy connectivity between sensors, the Internet of Things (IoT) has become popular and used in many applications, such as for smart city, smart health, smart home, and smart vehicle realizations. These IoT-based systems contribute to both daily life and business, including sensitive and emergency situations. In general, the devices or sensors used in the IoT have very limited computational power, storage capacity, and communication capabilities, but they help to collect a large amount of data as well as maintain communication with the other devices in the network. Since most of the IoT devices have no physical security, and often are open to everyone via radio communication and via the internet, they are highly vulnerable to existing and emerging novel security attacks. Further, the IoT devices are usually integrated with the corporate networks; in this case, the impact of attacks will be much more significant than operating in isolation. Due to the constraints of the IoT devices, and the nature of their operation, existing security mechanisms are less effective for countering the attacks that are specific to the IoT-based systems. This article presents a new insider attack, namedloophole attack, that exploits the vulnerabilities present in a widely used IPv6 routing protocol in IoT-based systems, calledRPL(Routing over Low Power and Lossy Networks). To protect the IoT system from this insider attack, a machine learning based security mechanism is presented. The proposed attack has been implemented using a Contiki IoT operating system that runs on the Cooja simulator, and the impacts of the attack are analyzed. Evaluation on the collected network traffic data demonstrates that the machine learning based approaches, along with the proposed features, help to accurately detect the insider attack from the network traffic data.
Sensorimotor serial dependencies in head movements
Authors: Zimmermann Eckart
Published: July 2021

Head movements are recalibrated by serial dependencies by errors between consecutive trials. Head movements are subject to a regression of the average target location.
Dynamic Performance Evaluation of Concrete Building Using Low‐Yield Point Steel Shear Panels
Authors: Marzban Nima , Esmaeiltabar Nesheli Parisa
Published: July 2021

Steel shear walls are a novel component in the field of construction. It has been of special interest to structural engineers for the reinforcement of steel buildings for the recent decades. Its unique features have attracted more attention, and its features are economical, easy to implement, light weight compared to similar systems, high ductility, fast installation, high energy absorption, and a significant reduction in residual stress in the structure. All the reasons made researchers think about studying its use in the repair of concrete buildings. Because this system has a low weight, it does not add extra load to the structure, and even with its connections, it strengthens the beams and columns around it. The design of this system in concrete buildings does not seem to be economical except in the case of restoration. In this paper, preliminary explanations of the steel shear wall are presented for more familiarity, and in the following sections, the study of reinforcement and repair of concrete structures will be studied and its difference with the low‐yield point will be considered. Finally, the test results will be reviewed. The results of this study show that LYP steel shear panels cause a lot of energy loss and absorption, which is very useful in the safety of buildings exposed to severe earthquakes.
A LSTM-RNN-Based Fiber Optic Gyroscope Drift Compensation
Authors: Mao Ning , Xu Jiangning , Li Jingshu , He Hongyang
Published: July 2021

Fiber optic gyroscope (FOG) inertial measurement unit (IMU) containing a three-orthogonal gyroscope and three-orthogonal accelerometer has been widely utilized in positioning and navigation of military and aerospace fields, due to its simple structure, small size, and high accuracy. However, noise such as temperature drift will reduce the accuracy of FOG, which will affect the resolution accuracy of IMU. In order to reduce the FOG drift and improve the navigation accuracy, a long short-term memory recurrent neural network (LSTM-RNN) model is established, and a real-time acquisition method of the temperature change rate based on moving average is proposed. In addition, for comparative analysis, backpropagation (BP) neural network model, CART-Bagging, classification and regression tree (CART) model, and online support vector machine regression (Online-SVR) model are established to filter FOG outputs. Numerical simulation based on field test data in the range of -20°C to 50°C is employed to verify the effectiveness and superiority of the LSTM-RNN model. The results indicate that the LSTM-RNN model has better compensation accuracy and stability, which is suitable for online compensation. This proposed solution can be applied in military and aerospace fields.