Browse Articles

A resilience assessment framework for slopes considering multiple performance indicators

Effects of plasma-activated water on germination ‎and initial seedling growth of wheat

In this research, the effect of seed halopriming with plasma activated water (PAW) on wheat germination parameters have been studied. Response surface methodology was used to investigate the effect of three factors including: 1) type of water (distilled water, 0.2 and 0.4 min/mL PAW), 2) priming time (1, 3 and 5 h), and 3) salinity of the priming solution (0, 25 and 50 mmol/L NaCl) on wheat germination parameters. The results revealed that increasing PAW levels up to 0.18 min/mL led to an increase in seed germination percentage, seedling weight (both fresh and dry), seedling length, vigor indexes A and B, and water uptake and decreasing mean germination time. Increasing the level of PAW by more than 0.18 min/mL had a negative effect on these parameters. The fresh and dry weight of the seedlings respectively at the 0.18 and 0.2 min/mL levels of PAW, in all salinity levels, had the highest value. The effect of halopriming on enhancing seedling length was more than other characteristics. The optimum ranges of PAW, salinity and priming time were 0.13 min/mL, 10.3 mmol/L and 120.22 min for germination percentage, 0.18 min/mL, 15 mmol/L and 191.24 min for seedling fresh weight, 0.15 min/mL, 13.84 mmol/L and 221.2 min for seedling dry weight, 0.33 min/mL, 24.36 mmol/L and 152.62 min for mean germination time, 0.11 min/mL, 19.03 mmol/L and 177.77 min for vigor indexes A and 0.1 min/mL, 18.1 mmol/L and 178.99 min for vigor indexes B.

Biocementation beyond the Petri dish, scaling up to 900 L batches and a meter-scale column

Abstract Microbial-induced calcite precipitation (MICP), which leverages ureolytic microorganisms, has received significant attention during the past decade as a promising method for sustainable building and geoenvironmental applications. However, transitioning from lab-scale experimentation to volumes suitable for practical use poses challenges. This study addresses these obstacles by screening and analyzing over 50 strains sourced from (i) a natural environment in the canton of Ticino in Switzerland; (ii) microorganism banks; and (iii) an industry-scale bioreactor. Several ureolytic Sporosarcina species have been identified in the natural environment, and their ureolytic potential has been compared with that of other strains. A reference, banked microorganism yielded the highest ureolysis rate. When this latter strain was inoculated in 900 L batches and continuously cultivated at 5400 L, no contamination issues were observed, and the reference strain remained the dominant species. The produced culture, obtained under an optimized medium composition involving the circular valorization of NH4 +, was subsequently used to induce the biocementation of a 650 kg column of 0–1 mm sand. The results reveal the successful stabilization of the whole mass, with undrained Tresca strength values ranging from 90 to 140 kPa. This research lays the groundwork for scalable MICP production, which is capable of meeting the demands of real-world building and geoenvironmental projects.

Predicting vasovagal reactions to needles from video data using 2D-CNN with GRU and LSTM

When undergoing or about to undergo a needle-related procedure, most people are not aware of the adverse emotional and physical reactions (so-called vasovagal reactions; VVR), that might occur. Thus, rather than relying on self-report measurements, we investigate whether we can predict VVR levels from the video sequence containing facial information measured during the blood donation. We filmed 287 blood donors throughout the blood donation procedure where we obtained 1945 videos for data analysis. We compared 5 different sequences of videos—45, 30, 20, 10 and 5 seconds to test the shortest video duration required to predict VVR levels. We used 2D-CNN with LSTM and GRU to predict continuous VVR scores and to classify discrete (low and high) VVR values obtained during the blood donation. The results showed that during the classification task, the highest achieved F1 score on high VVR class was 0.74 with a precision of 0.93, recall of 0.61, PR-AUC of 0.86 and an MCC score of 0.61 using a pre-trained ResNet152 model with LSTM on 25 frames and during the regression task the lowest root mean square error achieved was 2.56 using GRU on 50 frames. This study demonstrates that it is possible to predict vasovagal responses during a blood donation using facial features, which supports the further development of interventions to prevent VVR.

Sex-specific association of immunological markers in CS-delivered newborns with pre-pregnancy body mass index and gestational weight gain of mothers

Abstract Just as overweight and obesity may impair immunity, excessive body weight-related parameters of women in the pre-conception period and during pregnancy are possible detrimental factors for fetal programming of the immune system in their offspring. We investigated the relationship of pre-pregnancy body mass index (pBMI) and gestational weight gain (GWG) of mothers with the placental transport rate (PTR) of IgG antibodies and antineutrophil cytoplasmatic antibodies against lactoferrin (Lf-ANCA) and their concentration in umbilical cord blood serum (UCS), verifying the sex-specificity of this relationship. The examined group of this cross-sectional pilot study consisted of 101 pregnant women and their healthy CS-delivered newborn children. The concentration of antibodies in maternal serum (MS) and UCS were determined by ELISA method. PTR was assessed as a ratio of the concentration of antibodies in the UCS and MS. A significantly lower PTR of IgG and their concentration in the UCS were demonstrated in newborns of mothers with an excessive pBMI compared to those with pBMI < 25 and the association was more pronounced in male newborns. The lowest PTR of beneficial IgG and their concentration in the UCS as well as the highest PTR of detrimental Lf-ANCA and their concentration in UCS were observed in newborns born to mothers with co-occurrence of both an excessive pBMI and GWG. It seems that maternal preconception overweight and obesity along with an excessive GWG can be a predictor of unfavorable immune effects in fetuses. Further studies are needed to explain the role of maternal weight-related parameters in the development of immunological health of their offspring.

Association between asymptomatic submicroscopic and microscopic malaria infections and anemia: A study in southern Benin

Introduction Recently, efforts to eliminate malaria have shifted focus from symptomatic cases alone to include asymptomatic carriers, who are now recognized as significant contributors to the disease’s transmission and control. This study examines the relationship between asymptomatic malaria infection and hemoglobin levels in Benin. Methods A cohort in Benin was enrolled and categorized into three age groups (under 5 years, 5–15 years, and over 15 years) for follow-up from August to November 2021. Participants were monitored over two months and assessed for malaria infection through microscopy and polymerase chain reaction (PCR) during their three visits. A questionnaire was employed to gather general and clinical characteristics. Multivariate models were utilized to analyze the associations between asymptomatic infection, anemia, and hemoglobin levels. Results Among 393 participants, 58.2% were diagnosed at enrolment with malaria via PCR, and 30.5% through microscopy. Anemia, defined as hemoglobin levels < 11 g/dL, was observed in 40.5% of the cohort. The risk of anemia declined with increasing age (OR for ages 5–15: 0.64, 95% CI [0.37; 1.09]; OR for over 15 years: 0.34, 95% CI [0.20; 0.59]) compared to children under 5. Individuals with both microscopic and submicroscopic infections exhibited higher odds of anemia (respectively OR = 4.15, 95% CI [2.41; 7.13] and OR = 2.09 [1.22; 3.57]) relative to those uninfected. Hemoglobin levels were consistently lower in participants with microscopic malaria across all age groups (β = -2.73, 95% CI [-3.41; -2.05] for those under 5, β = -1.35, 95% CI [-1.89; -0.82] for ages 5–15, and β = -0.72, 95% CI [-1.34; -0.07]) compared to non-infected individuals. Discussion Our findings suggest that asymptomatic malaria infections, including submicroscopic cases, are associated with anemia and decreased hemoglobin levels. This underscores the importance of employing ultrasensitive diagnostic methods for such infections and acknowledging their potential health implications.

Utilizing machine learning to predict hospital admissions for pediatric COVID-19 patients (PrepCOVID-Machine)

Modelling sensory attenuation as Bayesian causal inference across two datasets

Introduction To interact with the environment, it is crucial to distinguish between sensory information that is externally generated and inputs that are self-generated. The sensory consequences of one’s own movements tend to induce attenuated behavioral- and neural responses compared to externally generated inputs. We propose a computational model of sensory attenuation (SA) based on Bayesian Causal Inference, where SA occurs when an internal cause for sensory information is inferred. Methods Experiment 1investigates sensory attenuation during a stroking movement. Tactile stimuli on the stroking finger were suppressed, especially when they were predictable. Experiment 2 showed impaired delay detection between an arm movement and a video of the movement when participants were moving vs. when their arm was moved passively. We reconsider these results from the perspective of Bayesian Causal Inference (BCI). Using a hierarchical Markov Model (HMM) and variational message passing, we first qualitatively capture patterns of task behavior and sensory attenuation in simulations. Next, we identify participant-specific model parameters for both experiments using optimization. Results A sequential BCI model is well equipped to capture empirical patterns of SA across both datasets. Using participant-specific optimized model parameters, we find a good agreement between data and model predictions, with the model capturing both tactile detections in Experiment 1 and delay detections in Experiment 2. Discussion BCI is an appropriate framework to model sensory attenuation in humans. Computational models of sensory attenuation may help to bridge the gap across different sensory modalities and experimental paradigms and may contribute towards an improved description and understanding of deficits in specific patient groups (e.g. schizophrenia).

Elevated D-dimer on admission may predict poor prognosis in childhood influenza associated encephalopathy

Assessment of temporospatial and kinematic gait parameters using human pose estimation in patients with Parkinson’s disease: A comparison between near-frontal and lateral views

Gait disturbance is one of the most common symptoms in patients with Parkinson’s disease (PD) that is closely associated with poor clinical outcomes. Recently, video-based human pose estimation (HPE) technology has attracted attention as a cheaper and simpler method for performing gait analysis than marker-based 3D motion capture systems. However, it remains unclear whether video-based HPE is a feasible method for measuring temporospatial and kinematic gait parameters in patients with PD and how this function varies with camera position. In this study, treadmill and overground walking in 24 patients with early PD was measured using a motion capture system and two smartphone cameras placed on the near-frontal and lateral sides of the subjects. We compared the differences in temporospatial gait parameters and kinematic characteristics between joint position data obtained from the 3D motion capture system and the markerless HPE. Our results confirm the feasibility of analyzing gait in patients with PD using HPE. Although the near-frontal view, where the heel and toe are clearly visible, is effective for estimating temporal gait parameters, the lateral view is particularly well-suited for assessing spatial gait parameters and joint angles. However, in clinical settings where lateral recordings are not feasible, near-frontal view recordings can still serve as a practical alternative to motion capture systems.

Tool wear prediction based on XGBoost feature selection combined with PSO-BP network

Virtual reality perimetry compared to standard automated perimetry in adults with glaucoma: A systematic review

Purpose The purpose of this systematic review was to consolidate and summarize available data comparing virtual reality perimetry (VRP) with standard automated perimetry (SAP) in adults with glaucoma. Understanding the utility and diagnostic performance of emerging VRP technology may expand access to visual field testing but requires evidence-based validation. Methods A systematic literature search was conducted in 3 databases (PubMed Central, Embase, and Cochrane Central Register of Controlled Trials) from the date of inception to 10/09/2024. Eligibility criteria included randomized controlled trials or prospective or retrospective cohort studies that compared different modalities of VRP to SAP in adults >18 years of age with glaucoma. Studies were excluded if they were review articles, letters, case reports, abstract-only papers, unavailable full text, or non-English language. Identified studies were formally evaluated for risk of bias using the Newcastle-Ottawa tool. The study protocol was prospectively registered with PROSPERO in May 2023 (registration number: CRD42023429071). Results The literature search yielded 1657 results. After deduplication, abstract and title screening, 14 studies met inclusion criteria and were included in the final systematic review. Compared to Humphrey Field Analyzer or Octopus 900, 10 different VRP devices were included in our study: Oculus Quest, Smartphone-based Campimetry, Toronto Portable Perimeter, VirtualEye, Advance Vision Analyzer, VisuALL, Vivid Vision Perimeter, C3 fields visual field analyzer, Radius, and Virtual Field. Overall, published studies of VRP are promising; however, more work is required to better evaluate these devices, namely test-retest repeatability. Conclusions VRP holds strong potential to evaluate visual fields in adults with glaucoma, though further data is needed to validate emerging technologies and testing protocols. Eye providers may consider using these devices to monitor certain adults with glaucoma.

A method of coating life prediction based on high temperature thermal shock life test and three-dimensional heat transfer analysis

Correction: Achieving the 95 95 95 targets for all: A pathway to ending AIDS

Dose-dependent enhancement of in vitro osteogenic activity on strontium-decorated polyetheretherketone

Psychometric validation of the Cystic Fibrosis Impact Questionnaire (CF-IQ): A patient-reported outcome assessing impacts of cystic fibrosis

The Cystic Fibrosis (CF) Impact Questionnaire (CF-IQ) was qualitatively developed to assess the impact of CF in the context of treatment advancements and increased longevity. This study reports the CF-IQ validation. In this noninterventional validation study, people with CF completed the 40-item CF-IQ and validating patient-reported outcome measures (PROMs) via electronic diaries at enrollment (baseline) and at the 4-week follow-up. Validation consisted of modern methods and focus groups to finalize structural validity, and classical methods to assess internal consistency [1–3], test-retest reliability [4,5], concurrent validity [5], and known-groups validity [5] of the CF-IQ. At baseline, 214 adults completed the survey; 193 completed the follow-up survey. Unidimensional item response theory (IRT) models were separately fit to 5 prespecified domains (Control and Burden of CF Treatment Impacts, Physical Activity Impacts, Social Activity Impacts, Emotional Impacts, and Work/School Limitation Impacts). IRT local dependence (LD) statistics identified 17 redundant items. Two independent CF-patient focus groups (14 total patients) confirmed these findings, and the 17 items were dropped. Each domain defined on the final 23 items achieved the criterion of exact model fit as measured by the root mean squared error of approximation (RMSEA, values = 0), Internal consistency (Cronbach’s α) values ranged from 0.81 to 0.89, 4 of 5 domains achieved acceptable test-retest reliability, with intraclass correlation coefficient (ICC) values ≥ 0.7, acceptable concurrent validity was achieved for all domains, and known-groups validity was established. The novel CF-IQ is a psychometrically robust PROM capturing patient-centric impacts of CF in the context of the current standard of care.

Pharmacovigilance imbalance analysis of VEGFR-TKI-related taste and smell disorders

NKp46 enhances type 1 innate lymphoid cell proliferation and function and anti-acute myeloid leukemia activity

Abstract NKp46 is a critical regulator of natural killer (NK) cell immunity, but its function in non-NK innate immune cells remains unclear. Here, we show that NKp46 is indispensable for expressing IL-2 receptor-α (IL-2Rα) by non-NK liver-resident type-1 innate lymphoid cells (ILC1s). Deletion of NKp46 reduces IL-2Rα on ILC1s by downregulating NF-κB signaling, thus impairing ILC1 proliferation and cytotoxicity in vitro and in vivo. The binding of anti-NKp46 antibody to NKp46 triggers the activation of NF-κB, the expression of IL-2Rα, interferon-γ (IFN-γ), tumor necrosis factor (TNF), proliferation, and cytotoxicity. Functionally, NKp46 expressed on mouse ILC1s interacts with tumor cells through cell–cell contact, increasing ILC1 production of IFN-γ and TNF, and enhancing cytotoxicity. In a mouse model of acute myeloid leukemia, deletion of NKp46 impairs the ability of ILC1s to control tumor growth and reduces survival. This can be reversed by injecting NKp46+ ILC1s into NKp46 knock-out mice. Human NKp46+ ILC1s exhibit stronger cytokine production and cytotoxicity than their NKp46− counterparts, suggesting that NKp46 plays a similar role in humans. These findings identify an NKp46–NF-κB–IL-2Rα axis and suggest that activating NKp46 with an anti-NKp46 antibody may provide a potential strategy for anti-tumor innate immunity.

Low-resource MobileBERT for emotion recognition in imbalanced text datasets mitigating challenges with limited resources

Modern dialogue systems rely on emotion recognition in conversation (ERC) as a core element enabling empathetic and human-like interactions. However, the weak correlation between emotions and semantics poses significant challenges to emotion recognition in dialogue. Semantically similar utterances can express different types of emotions, depending on the context or speaker. In order to tackle this challenge, our paper proposes a novel loss called Focal Weighted Loss (FWL) with adversarial training and the compact language model MobileBERT. Our proposed loss function handles the problem of imbalanced emotion classification through Focal Weighted Loss and adversarial training and does not require large batch sizes or more computational resources. Our approach has been employed on four text emotion recognition benchmark datasets, MELD, EmoryNLP, DailyDialog and IEMOCAP demonstrating competitive performance. Extensive experiments on these benchmark datasets validate the effectiveness of our proposed FWL with adversarial training. This enables more human-like interactions on digital platforms. Our approach shows its potential to deliver competitive performance under limited resource constraints, comparable to large language models.

Characteristics and analysis of PM2.5 particles in a light-polluted atmosphere in winter