Additional Time Research Articles

Plasma-catalytic CO2 methanation over Ni supported on MCM-41 catalysts: Effect of metal dispersion and process optimization

Catalytic carbon dioxide (CO2) conversion technologies can be important components in carbon capture, storage and utilization for CO2 mitigation and possible future economic activity and have gained significant attention globally in past decades. Electrified non-thermal plasma (NTP) catalysis enables CO2 hydrogenation into value-added chemicals under mild conditions. If the hybrid process is coupled with renewable energy and green hydrogen, it can be the promising solution to address the energy and carbon emission challenges. To enhance the energy efficiency of NTP-catalytic systems, bespoke catalyst design and process optimization are necessary. Here, using Ni catalysts supported on mesoporous MCM-41 and NTP-catalytic CO2 methanation as the model systems, the effects of Ni metal dispersion, argon (Ar) addition and residence time on the NTP catalysis were also studied. The findings show that (i) increased metal dispersion alone did not lead to significant enhancement in the performance of NTP catalysis (e.g., CH4 production rate: 31.4 × 10−5 mol/(s·gNi) for 42.6 % Ni dispersion vs. 26.8 × 10−5 mol/(s·gNi) for 25.1 % dispersion), (ii) Ar addition to the system led to the decreased methane production rate (e.g., CH4 selectivity decreased by ∼19 % due to the increase in Ar addition to the system from 5 to 50 mL/min), and (iii) optimization of the residence time could improve the performance of NTP-catalytic CO2 methanation (i.e., an extension of the residence time to 0.69 s resulted in the higher CO2 conversion of 72.7 % and CH4 selectivity of 95.9 % at 9.6 kV than that at 0.49 s and 11 kV).

The Synthesis of 2'-Hydroxychalcones under Ball Mill Conditions and Their Biological Activities.

Chalcones are polyphenols that belong to the flavonoids family, known for their broad pharmacological properties. They have thus attracted the attention of chemists for their obtention and potential activities. In our study, a library of compounds from 2'-hydroxychalcone's family was first synthesized. A one-step mechanochemical synthesis via Claisen-Schmidt condensation reaction under ball mill conditions was studied, first in a model reaction between a 5'-fluoro-2'-hydroxyacetophenone and 3,4-dimethoxybenzaldehyde. The reaction was optimized in terms of catalysts, ratio of reagents, reaction time, and influence of additives. Among all assays, we retained the best one, which gave the highest yield of 96% when operating in the presence of 1 + 1 eq. of substituted benzaldehyde and 2 eq. of KOH under two grinding cycles of 30 min. Thus, this protocol was adopted for the synthesis of the selected library of 2'-hydroxychalcones derivatives. The biological activities of 17 compounds were then assessed against Plasmodium falciparum, Leishmania donovani parasite development, as well as IGR-39 melanoma cell lines by inhibiting their viability and proliferation. Compounds 6 and 11 are the most potent against L. donovani, exhibiting IC50 values of 2.33 µM and 2.82 µM, respectively, better than the reference drug Miltefosine (3.66 µM). Compound 15 presented the most interesting antimalarial activity against the 3D7 strain, with IC50 = 3.21 µM. Finally, chalcone 12 gave the best result against IGR-39 melanoma cell lines, with an IC50 value of 12 µM better than the reference drug Dacarbazine (IC50 = 25 µM).

Convolutional neural network for estimation of harvest time of forage sorghum (sorghum bicolor) cultivar samurai-1

One of the economic alternatives to improve the quality of ruminant feed is combining grass as the main feed with high-protein forages such as sorghum. To get a quality sorghum harvest during the period, it must be right when it has good biomass content, nutrients, and digestibility. The problem is that measuring quality in the laboratory has additional costs and time, which is not short, causing delays. An approach with machine learning using a convolutional neural network can be a better solution. This research uses a convolutional neural network algorithm with the right architecture to estimate sorghum harvest time from imaging results of unmanned aerial vehicles. The stages of this research include data collection, pre-processing, modeling, and finally, the evaluation stage. This research compares the results of several convolutional neural network (CNN) algorithm architectural models: simple CNN, ResNet50 V2, visual geometry group-16 (VGG-16), MobileNet V2, and Inception V3. The result is determining the CNN algorithm architectural model that can estimate sorghum harvest time with maximum accuracy. The best result is the simple CNN architectural model with an accuracy of 0.95. This research shows that the classification model obtained from the CNN algorithm with a simple CNN architecture is the choice model for estimating sorghum harvest time.

Discovery of Ten Anti-HIV Hit Compounds and Preliminary Pharmacological Mechanisms Studies.

The research and development of HIV drugs is very important, but at the same time it is a long cycle and expensive system project. High-throughput drug screening systems and molecular libraries of potential hit compounds remain the main ways for the discovery of hit compounds with anti-HIV activity. The aim of this study was to screen out the hit compounds against HIV-1 in the natural product molecule library and the antiviral molecule library, and elucidate the molecular mechanism of their inhibition of HIV-1, so as to provide a new choice for AIDS drug research. In this study, a drug screening system using HIV Rev-dependent indicator cell line (Rev-A3R5-GFP reporter cells) with pseudoviruses (pNL4-3) was used. The natural drug molecule library and antiviral molecule library were screened, and preliminary drug mechanism studies were performed. Ten promising hit compounds were screened. These ten molecules and their drug inhibitory IC50 were as follows: Cephaeline (0.50 μM), Yadanziolide A (8.82 μM), Bruceine D (2.48 μM), Astragaloside IV (4.30 μM), RX-3117 (1.32 μM), Harringtonine (0.63 μM), Tubercidin (0.41 μM), Theaflavine-3, 3'-digallate (0.41 μM), Ginkgetin (10.76 μM), ZK756326 (5.97 μM). The results of the Time of additions showed that except for Astragaloside IV and Theaflavine-3, 3'-digallate had a weak entry inhibition effect, and it was speculated that all ten compounds had an intracellular inhibition effect. Cephaeline, Harringtonine, Astragaloside IV, Bruceine D, and Tubercidin may have pre-reverse transcriptional inhibition. Yadanziolide A, Theaflavine-3, 3'-digallate, Ginkgetin and RX-3117 may be in the post-reverse transcriptional inhibition. The inhibitory effect of ZK 75632 may be in the reverse transcriptional process. A drug screening system using Rev-A3R5-GFP reporter cells with pseudoviruses (pNL4-3) is highly efficient. This study provided potential hit compounds for new HIV drug research.

Abstract 4685: The identification of new therapeutic targets in mucinous ovarian carcinoma

Abstract Background: Epithelial ovarian cancer (EOC) is the second cause of death among gynaecological cancersworldwide. Mucinous ovarian carcinoma (mEOC) accounts for 3-5% of all EOCs, and when diagnosed at anadvanced stage its prognosis is very poor mainly for its limited chemosensitivity. PLK1 is a member of thewell-conserved serine/threonine kinase family, that plays a key role in the progression of mitosis, in the G2/Mcheckpoint regulation, DNA damage replication, stress response, and cell death pathways. mEOC has beenshown to be sensitive to PLK1 inhibition both with siRNA and small molecule inhibitor (onvansertib). Giventhis background and the need for new therapeutic approaches in mEOC, the purposes of this work were toidentify new therapeutic targets in mEOC using CRISPR/Cas9 lentivirus libraries and to find synthetic lethalpartners with the PLK1 inhibitor onvansertib. Methods: We used three different mucinous cell lines: MCAS,EFO27, TOV2414, overexpressing Cas9 gene. We evaluated the Cas9 expression through Western Blotanalysis, and the Cas9 activity through a Fluorescent Activated Cell Sorter- based-GFP assay. We used twodifferent lentiviral gRNAs Libraries (Bassik Library Human CRISPR Deletion Library - Apoptosis and cancer(Addgene #101926)/Drug targets, kinases, and phosphatases (Addgene #101927)). The EFO27 Cas9 cells wereused for the screening experiment. Cells were infected with the lentiviral libraries at MOI of 0.3 and put inpuromycin selection. Six days after puromycin addition (Time point 0) 30x10^6 cells were collected forsequencing. The remaining 30x10^6 cells were split in two: control cells and cells treated with a subtoxic doseof onvansertib (IC30). After 7 days (Time point 1) 30x10^6 cells for each condition were collected forsequencing. The infection of libraries was performed alone and in combination with sub-toxic onvansertibtreatment, to identify genes important for mucinous carcinoma cell survival, and those genes in syntheticlethality with onvansertib. Results: Bioinformatic analyses comparing control cells (time 1 vs time 0) andPLK1 treated and non -treated cells (time 1) allowed the generation of a gene ranking list, including genesinvolved in survival of EFO27 cells like ZC2HC1C, RPA2, POLE3, KIN, TUBG1, SMC2, CDC26, CDC42, HOXA9,TAF10, DCLRE1C, SENP1, MRPS31, COPS2; and genes in synthetic lethality with PLK1 treatment, like JUND,CARD9, BCL2L2. Validation experiments are ongoing and will be presented and discussed. Conclusion: Using a CRISPR-based approach, we identified genes that either alone or in combination with PLK inhibitioncould have therapeutic value in mEOC. Citation Format: Serena Petrella, Marika Colombo, Mirko Marabese, Chiara Grasselli, Andrea Panfili, Ilaria Craparotta, Maria Chiara Barbera, Giada Andrea Cassanmagnago, Marco Bolis, Giovanna Damia. The identification of new therapeutic targets in mucinous ovarian carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4685.

Generalized Early Stopping in Evolutionary Direct Policy Search

Lengthy evaluation times are common in many optimization problems such as direct policy search tasks, especially when they involve conducting evaluations in the physical world, e.g. in robotics applications. Often when evaluating solution over a fixed time period it becomes clear that the objective value will not increase with additional computation time (for example when a two wheeled robot continuously spins on the spot). In such cases, it makes sense to stop the evaluation early to save computation time. However, most approaches to stop the evaluation are problem specific and need to be specifically designed for the task at hand. Therefore, we propose an early stopping method for direct policy search. The proposed method only looks at the objective value at each time step and requires no problem specific knowledge. We test the introduced stopping criterion in five direct policy search environments drawn from games, robotics and classic control domains, and show that it can save up to \(75\%\) of the computation time. We also compare it with problem specific stopping criteria and show that it performs comparably, while being more generally applicable.

Integration of a tobacco cessation program into a rural community-based maternal and child health program in India: A stakeholders' perspective on task shifting.

According to the Global Adult Tobacco Survey-2, India, 7.5% of pregnant women are tobacco users with a high prevalence of smokeless tobacco use in rural India. Although pregnant women may receive advice to quit tobacco, lack of knowledge on providing cessation support among healthcare workers results in missed opportunities. Community Health Workers (CHWs) play a significant role in maternal and child health (MCH) programs. Thus, task-shifting for providing cessation support by CHWs was planned and the perceptions and attitudes of concerned stakeholders were explored. A pre-implementation qualitative study was conducted in four states of India within existing rural, community-based MCH program settings. Implementation research frameworks were used to develop data collection tools and for inductive and deductive thematic analysis. In-depth interviews were conducted with stakeholders (n=28) like coordinators, pregnant women and village functionaries of the government health system. Four focus groups were conducted with female CHWs (n=24). Stakeholders intended to adopt the intervention as objectives of the cessation intervention were aligned with the aims of the MCH program. CHWs related to their role in task-shifting and understood the context for implementing the intervention within the MCH program. Pregnant women expressed openness to receiving cessation support from CHWs acting as a facilitator for task-shifting. Barriers anticipated were the additional workload and time required for CHWs to implement the intervention. Task-shifting to female CHWs for screening tobacco users, providing brief advice and cessation support within the MCH program was perceived to be acceptable, adoptable and feasible. The study builds insight into the process of developing a grounded approach for the integration of tobacco cessation intervention into a rural, community-based antenatal care setting by task shifting to female community health workers for providing cessation support to pregnant women. The study fills gaps in the literature related to establishing tobacco cessation interventions for pregnant women. The delineated efforts in integration of the intervention and task shifting can be replicated in other developing countries, especially in rural communities within South Asian and Southeast Asian regions having cultural practices, community-based healthcare structures and tobacco consumption patterns that are comparable to India.

Quantifying cerebral microbleeds using quantitative susceptibility mapping from magnetization-prepared rapid gradient-echo.

T1-weighted magnetization-prepared rapid gradient-echo (MPRAGE) is commonly included in brain studies for structural imaging using magnitude images; however, its phase images can provide an opportunity to assess microbleed burden using quantitative susceptibility mapping (QSM). This potential application for MPRAGE-based QSM was evaluated using in vivo and simulated measurements. Possible factors affecting image quality were also explored. Detection sensitivity was evaluated against standard multiecho gradient echo (MEGE) QSM using 3-T in vivo data of 15 subjects with a combined total of 108 confirmed microbleeds. The two methods were compared based on the microbleed size and susceptibility measurements. In addition, simulations explored the detection sensitivity of MPRAGE-QSM at different representative magnetic field strengths and echo times using microbleeds of different size, susceptibility, and location. Results showed that in vivo microbleeds appeared to be smaller (× 0.54) and of higher mean susceptibility (× 1.9) on MPRAGE-QSM than on MEGE-QSM, but total susceptibility estimates were in closer agreement (slope: 0.97, r2 : 0.94), and detection sensitivity was comparable. In simulations, QSM at 1.5 T had a low contrast-to-noise ratio that obscured the detection of many microbleeds. Signal-to-noise ratio (SNR) levels at 3 T and above resulted in better contrast and increased detection. The detection rates for microbleeds of minimum one-voxel diameter and 0.4-ppm susceptibility were 0.55, 0.80, and 0.88 at SNR levels of 1.5, 3, and 7 T, respectively. Size and total susceptibility estimates were more consistent than mean susceptibility estimates, which showed size-dependent underestimation. MPRAGE-QSM provides an opportunity to detect and quantify the size and susceptibility of microbleeds of at least one-voxel diameter at B0 of 3 T or higher with no additional time cost, when standard T2 *-weighted images are not available or have inadequate spatial resolution. The total susceptibility measure is more robust against sequence variations and might allow combining data from different protocols.

Inclusion of Beef Heart in Ground Beef Patties Alters Quality Characteristics and Consumer Acceptability as Assessed by the Application of Electronic Nose and Tongue Technology.

Consumer purchasing of beef is often driven by the trinity of flavor, palatability, and convenience. Currently, beef patties in the United States are manufactured with fat and lean trimmings derived from skeletal muscles. A reduction in total beef supply may require the use of animal by-product utilization such as variety meats to achieve patty formulations. The current study aimed to assess textural, color, and flavor characteristics in addition to volatile compounds through electronic technology, e-nose and e-tongue, of ground beef patties formulated with beef heart. Ground beef patties were manufactured with 0%, 6%, 12%, or 18% beef heart, with the remainder of the meat block being shoulder clod-derived ground beef. Patties (n = 65/batch/treatment) within each batch (n = 3) with each treatment were randomly allocated to cooked color (n = 17/batch/treatment), Allo-Kramer shear force (AKSF; n = 17/batch/treatment), texture profile analysis (TPA; n = 6/batch/treatment), cooking loss (n = 17/batch/treatment), consumer panel (n = 3/batch/treatment), e-nose (n = 1/batch/treatment), and e-tongue (n = 1/batch/treatment) analysis groups. Patties containing beef heart did not require additional cooking time (p = 0.1325) nor exhibit greater cooking loss (p = 0.0803). Additionally, inclusion rates of beef heart increased hardness (p = 0.0030) and chewiness values (p = 0.0316) in TPA, were internally redder (p = 0.0001), and reduced overall liking by consumer panelists (p = 0.0367). Lastly, patties containing beef heart exhibited greater red-to-brown (p = 0.0003) and hue angle (p = 0.0001) values than control patties. The results suggest that beef heart inclusion does alter ground beef quality characteristics and consumer acceptability.

Investigating the design, participation and experience of teaching and learning facilitated by user-generated microgames on an open educational platform

Investigating the design, participation and experience of teaching and learning facilitated by user-generated microgames on an open educational platform

An effort to understand parents’ media mediation roles and early childhood children's digital game addiction tendency: A descriptive correlational survey study

AbstractThis study aims to determine whether parents' media mediation roles are related to their early childhood children's digital game addiction tendencies. In addition, it examines whether these variables are related to the child's and parent's digital device usage habits and whether they differ according to various sociodemographic variables and digital device usage habits. In this context, we collected data from 433 parents (mother = 336, father = 97) with children aged 3–6. We analyzed the data using correlation analysis, one-way ANOVA, and t-test. Active-supportive, restrictive-supportive, active-limiting, restrictive-limiting, and active-interpreter roles of parents were negatively related to children's digital game addiction tendencies. In addition, parents' and children's digital device screen time was negatively associated with parents' media mediation roles and positively with children's digital game addiction tendencies. Mothers found their children more likely to have digital game addiction than fathers. Children of parents who play digital games have higher digital game addiction than those of parents who do not play, male children than female, children who have their own digital devices than those who do not, and children who only watch YouTube videos than those who only watch television channels for kids. Finally, we observed that mothers are more active in media mediation roles than fathers and that parents behave more restrictive toward their daughters.

Diagnostic value of synthetic diffusion-weighted imaging on breast magnetic resonance imaging assessment: comparison with conventional diffusion-weighted imaging.

To compare images generated by synthetic diffusion-weighted imaging (sDWI) with those from conventional DWI in terms of their diagnostic performance in detecting breast lesions when performing breast magnetic resonance imaging (MRI). A total of 128 consecutive patients with 135 enhanced lesions who underwent dynamic MRI between 2018 and 2021 were included. The sDWI and DWI signals were compared by three radiologists with at least 10 years of experience in breast radiology. Of the 82 malignant lesions, 91.5% were hyperintense on sDWI and 73.2% were hyperintense on DWI. Of the 53 benign lesions, 71.7% were isointense on sDWI and 37.7% were isointense on DWI. sDWI provides accurate signal intensity data with statistical significance compared with DWI (P < 0.05). The diagnostic performance of DWI and sDWI to differentiate malignant breast masses from benign masses was as follows: sensitivity 73.1% [95% confidence interval (CI): 62-82], specificity 37.7% (95% CI: 24-52); sensitivity 91.5% (95% CI: 83-96), specificity 71.7% (95% CI: 57-83), respectively. The diagnostic accuracy of DWI and sDWI was 59.2% and 83.7%, respectively. However, when the DWI images were evaluated with apparent diffusion coefficient mapping and compared with the sDWI images, the sensitivity was 92.68% (95% CI: 84-97) and the specificity was 79.25% (95% CI: 65-89) with no statistically significant difference. The inter-reader agreement was almost perfect (P < 0.001). Synthetic DWI is superior to DWI for lesion visibility with no additional acquisition time and should be taken into consideration when conducting breast MRI scans. The evaluation of sDWI in routine MRI reporting will increase diagnostic accuracy.

Descriptive study of the challenges when implementing an app for patients with neovascular age-related macular degeneration to monitor their vision at home

ObjectivesRemote monitoring of health has the potential to reduce the burden to patients of face-to-face appointments and make healthcare more efficient. Apps are available for patients to self-monitor vision at...

Gait retraining targeting foot pronation: A systematic review and meta-analysis.

Foot pronation is a prevalent condition known to contribute to a range of lower extremity injuries. Numerous interventions have been employed to address this issue, many of which are expensive and necessitate specific facilities. Gait retraining has been suggested as a promising intervention for modifying foot pronation, offering the advantage of being accessible and independent of additional materials or specific time. We aimed to systematically review the literature on the effect of gait retraining on foot pronation. We searched four databases including PubMed, Web of Science, Scopus and Embase from their inception through 20 June 2023. The Downs and Black appraisal scale was applied to assess quality of included studies. Two reviewers screened studies to identify studies reporting the effect of different methods of gait-retraining on foot pronation. Outcomes of interest were rearfoot eversion, foot pronation, and foot arch. Two authors separately extracted data from included studies. Data of interest were study design, intervention, variable, sample size and sex, tools, age, height, weight, body mass index, running experience, and weekly distance of running. Mean differences and 95% confidence intervals (CI) were calculated with random effects model in RevMan version 5.4. Fifteen studies with a total of 295 participants were included. The results of the meta-analysis showed that changing step width does not have a significant effect on peak rearfoot eversion. The results of the meta-analysis showed that changing step width does not have a significant effect on peak rearfoot eversion. Results of single studies indicated that reducing foot progression angle (MD 2.1, 95% CI 0.62, 3.58), lateralizing COP (MD -3.3, 95% CI -4.88, -1.72) can effectively reduce foot pronation. Overall, this study suggests that gait retraining may be a promising intervention for reducing foot pronation; Most of the included studies demonstrated significant improvements in foot pronation following gait retraining. Changing center of pressure, foot progression angle and forefoot strike training appeared to yield more favorable outcomes. However, further research is needed to fully understand its effectiveness and long-term benefits.

Laboratory investigation of the effect of using metakaolin and clay on the behaviour of recycled glass powder-based geopolymer mortars

Civil infrastructure relies on cement, a common building material. However, Portland cement production pollutes the world by consuming mineral resources and emitting carbon dioxide. Using modern, cost-effective, and eco-friendly cement materials seems necessary. One such material is geopolymer cement, also known as green cement, composed of aluminosilicate base materials and alkaline-silicate activators. In the present study, waste glass powder was utilised to provide a rich aluminosilicate base material by substituting 10%, 20%, and 30% of the metakaolin or clay with calcium carbide residue as an alkaline activator. The samples were processed under two distinct temperature conditions: natural environment and thermal processing at 80 °C in an autoclave. The mechanical and microstructural properties of the mortars were evaluated regarding compressive strength, bending strength, setting time, volume control, and Scanning Electron Microscope (SEM). The results indicate that the type and amount of glass powder alternatives significantly determine the final sample strength. Substituting 10% metakaolin and 20% clay for glass powder maximises compressive strength. The optimal bending strength of geopolymer samples was obtained by substituting 10% clay with 10% metakaolin. SEM images validate this discovery by exhibiting a more compact and cohesive arrangement. Additionally, the processing conditions of geopolymer samples significantly influence the mechanical properties of geopolymer mortars. The results of the V-cut test indicate that geopolymeric mortars are sluggish and require additional time to reach their primary and secondary strength. This study suggests that geopolymers could produce environmentally friendly concrete by reducing cement use and advancing economic and environmental goals.

Space limited linear-time graph algorithms on big data

We study algorithms for graph problems in which the graphs are of extremely large size N so that super-linear time ω(N) or linear space Θ(N) would become impractical. We use a parameter k to characterize the computational power of a normal computer that can provide additional time and space bounded by polynomials of k in dealing with the large graphs. In particular, we are interested in strict linear-time algorithms using space O(kO(1)). In our case studies, as examples, we present (1) a randomized greedy algorithm of time O(N) and space O(k2) for a parameterized version of the Maximal Matching problem; and (2) randomized kernelization algorithms of time O(N) and space O(kO(1)) for a number of well-known NP-hard problems. Our kernelization algorithms have their kernel sizes match the best kernel sizes by known polynomial-time kernelization algorithms with no space constraints for the problems. We also study the relationship between our proposed model and the streaming model. This study motivates a new streaming kernelization algorithm for the famous Vertex Cover problem that has an optimal update time complexity while matches the best known space complexity of streaming algorithms for the problem.

Acute effect of dry needling on trunk kinematics and balance of patients with non-specific low back pain

BackgroundLimited knowledge exists about the effectiveness of dry needling (DN) concerning the torso kinematics in patients with non-specific low back pain (NS-LBP). Acute effects of DN in NS-LBP patients from a functional perspective were investigated. MethodsSixteen NS-LBP patients and 11 healthy individuals (HG) were examined. NS-LBP patients received a single session of DN at the lumbar region. Baseline and immediate post-treatment measurements during flexion-extension and lateral bending of the trunk were conducted for the NS-LBP patients. HG were measured only at baseline to be used as a reference of NS-LBP patients' initial condition. Algometry was applied in NS-LBP patients. Centre of pressure, range of motion of the trunk and its’ derivatives were obtained. FindingsHG performed significantly faster, smoother and with greater mobility in the performed tasks compared to the pre intervention measurements of the NS-LBP patients. For the NS-LBP patients, significant greater angular velocity in frontal plane and significant lower jerk in the sagittal plane were demonstrated post intervention. DN alleviated pain tolerance significantly at the L5 level. Regarding the effectiveness of the DN upon spine kinematics, their derivatives were more sensitive. InterpretationIt appeared that the pathological type of torso movement was acutely affected by DN. NS-LBP patients showcased smoother movement immediately after the intervention and better control as imprinted in the higher derivative of motion although range of motion did not improve. This quantitative variable may not be subjected to acute effects of DN but rather need additional time and training to be improved.

Tractable skew-normal approximations via matching

Many approximate Bayesian inference methods assume a particular parametric form for approximating the posterior distribution. A Gaussian distribution provides a convenient density for such approaches; examples include the Laplace, penalized quasi-likelihood, Gaussian variational, and expectation propagation methods. Unfortunately, these all ignore potential posterior skewness. The recent work of Durante et al. [Skewed Bernstein-von Mises theorem and skew-modal approximations; 2023. ArXiv preprint arXiv:2301.03038.] addresses this using skew-modal (SM) approximations, and is theoretically justified by a skewed Bernstein-von Mises theorem. However, the SM approximation can be impractical to work with in terms of tractability and storage costs, and uses only local posterior information. We introduce a variety of matching-based approximation schemes using the standard skew-normal distribution to resolve these issues. Experiments were conducted to compare the performance of this skew-normal matching method (both as a standalone approximation and as a post-hoc skewness adjustment) with the SM and existing Gaussian approximations. We show that for small and moderate dimensions, skew-normal matching can be much more accurate than these other approaches. For post-hoc skewness adjustments, this comes at very little cost in additional computational time.

Quasi-3D: reducing convergence effort improves visual comfort of head-mounted stereoscopic displays

The diffusion of virtual reality urges to solve the problem of vergence-accommodation conflict arising when viewing stereoscopic displays, which causes visual stress. We addressed this issue with an approach based on reducing ocular convergence effort. In virtual environments, vergence can be controlled by manipulating the binocular separation of the virtual cameras. Using this technique, we implemented two quasi-3D conditions characterized by binocular image separations intermediate between 3D (stereoscopic) and 2D (monoscopic). In a first experiment, focused on perceptual aspects, ten participants performed a visuo-manual pursuit task while wearing a head-mounted display (HMD) in head-constrained (non-immersive) condition for an overall exposure time of ~ 7 min. Passing from 3D to quasi-3D and 2D conditions, progressively resulted in a decrease of vergence eye movements—both mean convergence angle (static vergence) and vergence excursion (dynamic vergence)—and an increase of hand pursuit spatial error, with the target perceived further from the observer and larger. Decreased static and dynamic vergence predicted decreases in asthenopia trial-wise. In a second experiment, focused on tolerance aspects, fourteen participants performed a detection task in near-vision while wearing an HMD in head-free (immersive) condition for an overall exposure time of ~ 20 min. Passing from 3D to quasi-3D and 2D conditions, there was a general decrease of both subjective and objective visual stress indicators (ocular convergence discomfort ratings, cyber-sickness symptoms and skin conductance level). Decreased static and dynamic vergence predicted the decrease in these indicators. Remarkably, skin conductance level predicted all subjective symptoms, both trial-wise and session-wise, suggesting that it could become an objective replacement of visual stress self-reports. We conclude that relieving convergence effort by reducing binocular image separation in virtual environments can be a simple and effective way to decrease visual stress caused by stereoscopic HMDs. The negative side-effect—worsening of spatial vision—arguably would become unnoticed or compensated over time. This initial proof-of-concept study should be extended by future large-scale studies testing additional environments, tasks, displays, users, and exposure times.

Nano‐Calcium Carbonate with Core–Shell Structure was Prepared by Dopamine Chelation Using Pluronic F‐127 as Template

AbstractHerein, a new template carbonization method is used to prepare calcite‐type nano‐calcium carbonate (CaCO3) with a core–shell structure using calcium hydroxide as a solute and Pluronic F‐127 as a templating and pore‐forming agent. Dopamine hydrochloride is added to control the size of calcium hydroxide particles. The morphology, particle size, and crystal type of CaCO3 are characterized via transmission electron microscopy, X‐ray diffraction, nanoparticle size, and zeta potentiometer. The creation of core–shell calcium carbonate nanoparticles is examined in relation to reaction circumstances (i.e., additive sequence, additive amount, and additive mixing time), carbonization temperature, liquid flow rate, and templates with varying chain lengths. Furthermore, a discussion is held regarding the formation mechanism of spherical core–shell calcium carbonate that is created using the innovative template carbonization method. The results show that the order, amount, liquid flow rate, and template type of additives have a significant effect on the crystal shape of calcium carbonate nanoparticles. The mixing time of additives has a significant effect on the particle size of calcium carbonate nanoparticles. Interestingly, the thickness of the shell depends on the carbonization temperature, and too slow or too fast flow rate will lead to the formation of cyclic calcium carbonate nanoparticles.