bluuebunny/crossref_metadata_2025 huggingface dataset:
The peptidoglycan-associated lipoprotein gene mutant elicits robust immunological defense in mice against Salmonella enteritidis
Authors: Zhao Guixin , Duan Wenlong , Zhang Lu , Sun Wenchao , Liu Wan , Zhang Xiaoyu , Zhang Yanying , Shi Qiumei , Wu Tonglei
Published: June 2024

Background

Salmonella enteritidis (S. enteritidis), a zoonotic pathogen with a broad host range, presents a substantial threat to global public health safety. Vaccination stands as an effective strategy for the prevention and control of S. enteritidis infection, highlighting an immediate clinical need for the creation of safe and efficient attenuated live vaccines.

Methods

In this study, a S. enteritidis peptidoglycan-associated lipoprotein (pal) gene deletion strain (Δpal), was constructed. To assess its virulence, we conducted experiments on biofilm formation capability, motility, as well as cell and mouse infection. Subsequently, we evaluated the immune-protective effect of Δpal.

Results

It was discovered that deletion of the pal gene reduced the biofilm formation capability and motility of S. enteritidis. Cell infection experiments revealed that the Δpal strain exhibited significantly decreased abilities in invasion, adhesion, and intracellular survival, with downregulation of virulence gene expression, including mgtC, invH, spvB, sipA, sipB, ssaV, csgA, and pipB. Mouse infection experiments showed that the LD50 of Δpal increased by 104 times, and its colonization ability in mouse tissue organs was significantly reduced. The results indicated that the pal gene severely affected the virulence of S. enteritidis. Further, immunogenicity evaluation of Δpal showed a significant enhancement in the lymphocyte transformation proliferation capability of immunized mice, producing high titers of specific IgG and IgA, suggesting that Δpal possesses good immunogenicity. Challenge protection tests demonstrated that the strain could provide 100% immune protection against wild-type strains in mice.

Discussion

This study proves that the pal gene influences the virulence of S. enteritidis, and Δpal could serve as a candidate strain for attenuated live vaccines, laying the foundation for the development of attenuated live vaccines against Salmonella.
Cathepsins and Parkinson’s disease: insights from Mendelian randomization analyses
Authors: Yusufujiang Aishanjiang , Zeng Shan , Li Hongyan
Published: June 2024

Background

Parkinson’s disease (PD), the second most prevalent neurodegenerative condition, has a multifaceted etiology. Cathepsin-cysteine proteases situated within lysosomes participate in a range of physiological and pathological processes, including the degradation of harmful proteins. Prior research has pointed towards a potential link between cathepsins and PD; however, the precise causal relationship between the cathepsin family and PD remains unclear.

Methods

This study employed univariate and multivariate Mendelian randomization (MR) analyses to explore the causal relationship between the nine cathepsins and Parkinson’s disease (PD) risk. For the primary analysis, genome-wide association study (GWAS) summary statistics for the plasma levels of the nine cathepsins and PD was obtained from the INTERVAL study and the International Parkinson’s Disease Genomics Consortium. GWAS for PD replication analysis were obtained from the FinnGen consortium, and a meta-analysis was performed for the primary and replication analyses to evaluate the association between genetically predicted cathepsin plasma levels and PD risk. After identifying significant MR estimates, genetic co-localization analyses were conducted to determine whether shared or distinct causal variants influenced both cathepsins and PD.

Results

Elevated cathepsin B levels were associated with a decreased risk of PD in univariate MR analysis (odds ratio [OR] = 0.890, 95% confidence interval [CI]: 0.831–0.954, pFDR = 0.009). However, there was no indication that PD affected cathepsin B levels (OR = 0.965, 95% CI: 0.858–1.087, p = 0.852). In addition, after adjusting for the remaining cathepsins, cathepsin B levels independently and significantly contributed to the reduced risk of PD in multivariate MR analysis (OR = 0.887, 95% CI: 0.823–0.957, p = 0.002). The results of the replication MR analysis with the FinnGen GWAS for PD (OR = 0.921, 95% CI: 0.860–0.987, p = 0.020) and meta-analysis (OR = 0.905, 95% CI: 0.862–0.951, p < 0.001) were consistent with those of the primary analysis. Colocalization analysis did not provide any evidence of a shared causal variant between cathepsins and PD (PP.H4.abf = 0.005).

Conclusion

This genetic investigation supports the hypothesis that cathepsin B exerts a protective effect against PD. The quantification of cathepsin B levels could potentially serve as a predictive biomarker for susceptibility to PD, providing new insights into the pathomechanisms of the disease and possible interventions.
Progress and challenges in designing dynamic in vitro gastric models to study food digestion
Authors: Singh R. Paul
Published: June 2024

Understanding the mechanisms involved in food breakdown in the human gastrointestinal (GI) tract is essential in food digestion research. Research to study food digestion in the human GI tract requires in vivo and in vitro approaches. In vivo methods involving human or animal subjects are often cost-prohibitive and raise ethical concerns. For these reasons, in vitro approaches are becoming more common. Several dynamic in vitro models that mimic one or more components of the GI tract have been developed at various research institutions and by commercial companies. While there is evidence of considerable novelty and innovation in the design of these models, there are many differences among them in how the mechanical breakdown of solid foods is accomplished. In some systems, modulating water pressure is used to achieve peristaltic contractions of the gastric antrum, whereas, in other models, the flexible walls of a gastric chamber are compressed by the movement of rollers or clamps outside the walls of the test chamber. Although much progress has been made in standardizing the biochemical environment appropriate to the food digestion process, there is a lack of standard protocols to measure mechanical forces that result in the breakdown of solid foods. Similarly, no standardized methods are available to evaluate the results obtained from in vitro trials for validation purposes. Due to the large variability in the design features of in vitro models used for food digestion studies, developing consensus-based standards for the mechanical aspects of food breakdown is needed.
Combination of plant metabolites hinders starch digestion and glucose absorption while facilitating insulin sensitivity to diabetes
Authors: Huang Xin , Lin Kaihuang , Liu Sinian , Yang Junxiong , Zhao Haowei , Zheng Xiao-Hui , Tsai May-Jywan , Chang Chun-Sheng , Huang Liyue , Weng Ching-Feng
Published: June 2024

Introduction

Diabetes mellitus (DM) is a common endocrine disease resulting from interactions between genetic and environmental factors. Type II DM (T2DM) accounts for approximately 90% of all DM cases. Current medicines used in the treatment of DM have some adverse or undesirable effects on patients, necessitating the use of alternative medications.

Methods

To overcome the low bioavailability of plant metabolites, all entities were first screened through pharmacokinetic, network pharmacology, and molecular docking predictions. Experiments were further conducted on a combination of antidiabetic phytoactive molecules (rosmarinic acid, RA; luteolin, Lut; resveratrol, RS), along with in vitro evaluation (α-amylase inhibition assay) and diabetic mice tests (oral glucose tolerance test, OGTT; oral starch tolerance test, OSTT) for maximal responses to validate starch digestion and glucose absorption while facilitating insulin sensitivity.

Results

The results revealed that the combination of metabolites achieved all required criteria, including ADMET, drug likeness, and Lipinski rule. To determine the mechanisms underlying diabetic hyperglycemia and T2DM treatments, network pharmacology was used for regulatory network, PPI network, GO, and KEGG enrichment analyses. Furthermore, the combined metabolites showed adequate in silico predictions (α-amylase, α-glucosidase, and pancreatic lipase for improving starch digestion; SGLT-2, AMPK, glucokinase, aldose reductase, acetylcholinesterase, and acetylcholine M2 receptor for mediating glucose absorption; GLP-1R, DPP-IV, and PPAR-γ for regulating insulin sensitivity), in vitro α-amylase inhibition, and in vivo efficacy (OSTT versus acarbose; OGTT versus metformin and insulin) as nutraceuticals against T2DM.

Discussion

The results demonstrate that the combination of RA, Lut, and RS could be exploited for multitarget therapy as prospective antihyperglycemic phytopharmaceuticals that hinder starch digestion and glucose absorption while facilitating insulin sensitivity.
The effects of artificial intelligence on human resource activities and the roles of the human resource triad: opportunities and challenges
Authors: Dima Justine , Gilbert Marie-Hélène , Dextras-Gauthier Julie , Giraud Laurent
Published: June 2024

Introduction

This study analyzes the existing academic literature to identify the effects of artificial intelligence (AI) on human resource (HR) activities, highlighting both opportunities and associated challenges, and on the roles of employees, line managers, and HR professionals, collectively referred to as the HR triad.

Methods

We employed the scoping review method to capture and synthesize relevant academic literature in the AI–human resource management (HRM) field, examining 27 years of research (43 peer-reviewed articles are included).

Results

Based on the results, we propose an integrative framework that outlines the five primary effects of AI on HR activities: task automation, optimized HR data use, augmentation of human capabilities, work context redesign, and transformation of the social and relational aspects of work. We also detail the opportunities and challenges associated with each of these effects and the changes in the roles of the HR triad.

Discussion

This research contributes to the ongoing debate on AI-augmented HRM by discussing the theoretical contributions and managerial implications of our findings, along with avenues for future research. By considering the most recent studies on the topic, this scoping review sheds light on the effects of AI on the roles of the HR triad, enabling these key stakeholders to better prepare for this technological change. The findings can inform future academic research, organizations using or considering the application of AI in HRM, and policymakers. This is particularly timely, given the growing adoption of AI in HRM activities.
The mediating role of sleep disturbance in the relationship between depression and cardiovascular disease
Authors: Chen Feng , Lin Hao , Zhang Yuansi , Zhang Yu , Chen Linlin
Published: June 2024

Background

Studies suggest that both depression and disrupted sleep disturbance are linked to cardiovascular disease (CVD). However, the precise role of sleep disturbance in the connection between depression and CVD is poorly understood. Therefore, we sought to examine the associations among these factors and further explore the mediating role of sleep disturbance in the association between depression and CVD.

Methods

This study included data from 29,831 adults (≥20 years old). Multifactorial logistic regression analyses were conducted to examine the relationships among depression, sleep disturbance, and CVD. Additionally, bootstrap tests were used to investigate whether the association between depression and CVD was mediated by sleep disturbance.

Results

Our research showed that individuals who experienced depression or sleep disturbance had a notably greater likelihood of developing CVD than those who did not have these issues (depression: OR: 2.21, 95% CI=1.96–2.49; sleep disturbance: OR: 1.74, 95% CI=1.6–1.9). Even after adjusting for potential confounders, depression was still positively associated with the risk of sleep disturbance (OR: 4.07, 95% CI=3.73–4.44). Furthermore, sleep disturbance significantly mediated the association between depression and CVD, with a mediating effect of 18.1%.

Conclusion

Our study demonstrated that depression, sleep disturbance, and CVD are interrelated. The increased risk of CVD among patients with depression may be attributed to the mediating role of sleep disturbance. This finding underscores the importance of interventions focused on sleep disturbances as a means to address the connection between depression and CVD.
Can digital financial inclusion help reduce migrant workers’ overwork? Evidence from China
Authors: Zhang Yuzheng , Li Yundong , Zhuang Xugao , Liu Huan , Xu Yang , Zhang Shuxian , Yan Yueping , Li Yalin
Published: June 2024

Introduction

Migrant workers in China are migrants from the rural to the urban areas who usually work in the cities and return to the countryside after a certain period. Due to China’s strict household registration system, they differ significantly from urban residents’ access to public services. However, at the same time, China’s workers are facing a severe phenomenon of overwork, and the group of migrant workers is even more hard-hit by overwork, which will cause various adverse effects on workers and society and should attract the attention of all sectors of society.

Methods

This paper focuses on the impact of digital financial inclusion on the overwork of migrant workers. This study considered cross-sectional data containing 98,047 samples based on the 2017 China Migrants Dynamic Survey 2017 (CMDS) and China Municipal Statistical Yearbook after robustness tests and heterogeneity analysis using probit models.

Results

(1) digital financial inclusion can effectively alleviate overwork among migrant workers; (2) the impact of digital finance on overwork is more significant for the new generation, digitized industries, and self-employed migrant workers; it is also more significant for the South, East, and small and medium-sized cities than for the North, the Midwest, and large cities; (3) job quality and income are crucial factors in how digital financial inclusion affects overwork among migrant workers. Digital financial inclusion can improve the quality of employment for migrant workers and alleviate overwork. However, the income substitution effect partially reduces the inhibitory impact of digital financial inclusion on overwork.

Conclusion

Continuously promote the development of digital inclusive finance, improve laws and regulations, and protect the labor rights and interests of migrant workers. At the same time, vocational training and skills upgrading for rural migrant workers should be strengthened to improve the quality of their employment so that they can leave the secondary labor market and enter the primary labor market.
Exploring the mediating role of promoting school physical activity on the relationship between low socioeconomic status and academic achievement and school climate: evidence from 4,990 Chilean schools
Authors: Delgado-Floody Pedro , Cristi-Montero Carlos , Jerez-Mayorga Daniel , Ruiz-Ariza Alberto , Guzmán-Guzmán Iris Paola , Álvarez Cristian , Gómez-López Manuel , Carter-Thuillier Bastian , Caamaño-Navarrete Felipe
Published: June 2024

There is evidence that promoting school physical activity (PSPA) benefits children and adolescents, but little is understood about how this promotion may relate to academic achievement and school climate across varying levels of socioeconomic status (SES). Hence, the study aimed to address this knowledge gap by examining two main objectives: (1) determining the association between PSPA and academic achievement and school climate according to schools’ SES and (2) exploring the potential mediating role of PSPA in the relationship between schools’ SES and academic achievement and school climate. This cross-sectional study at the school level focused on 4,990 schools (including public, subsidized, and private schools) that participated in the National Educational Study 2018 (Chile), which was applied to primary schoolchildren (4th grade, aged 8–10 years). Schools were divided into non-PSPA (n = 4,280) and PSPA (n = 710) during the year 2018. Changes in academic achievement from 2017 to 2018 and school climate were considered. PSPA was associated with improvements in maths (low-SES OR: 1.80, p < 0.001) and reading (middle-SES OR: 1.45, p = 0.029; low-SES OR: 1.47, p < 0.001). The indirect effect (IE) showed that PSPA partially mediated the relationship between SES and academic achievement in reading (IE = 1.017; SE = 0.12; 95%CI, −1.27, −0.77), maths (IE = –1.019; SE = 0.12; 95%CI, −1.25, −0.78), and school climate (IE = –0.46; SE = 0.52; 95%CI, −0.56, −0.35). In conclusion, PSPA was linked to positive changes in academic achievement, especially among low SES, and PSPA presented a potential mediating role in the relationship between SES of schools and academic achievement and school climate.
Reducing barriers to promote engagement and retention in adolescent substance use treatment: results from a quality improvement evaluation
Authors: Chen Eileen , Seely Hayley D. , Thurstone Christian
Published: June 2024

Introduction

Although research on the development and efficacy of adolescent substance use treatment has made recent strides, many models do not translate into practice, especially when working with underserved youth who often face barriers to treatment. Meal incentives, rolling admission, and transportation assistance may be promising approaches to decrease barriers, thereby increasing treatment engagement, retention, and completion. The purpose of this evaluation was two-fold: (1) to examine treatment engagement amongst diverse, underserved youth in an intensive outpatient program for substance misuse in an urban metropolitan area, and (2) to investigate the role of meal incentives, rolling admission, and transportation assistance in youth engagement.

Methods

The intervention was 8 weeks of Acceptance and Commitment Therapy and trauma-focused group intervention, combined with contingency management, meal incentives, and transportation assistance. Treatment engagement, retention, and completion was compared against selected demographic variables (i.e., race and insurance coverage) and at three phases of program implementation: cohort admissions with transportation assistance (phase 1); rolling admissions with transportation assistance (phase 2); and rolling admissions with transportation assistance and meal incentives (phase 3). Data was analyzed using two-way ANOVAs; identified interactions were probed.

Results

Participants were 110 adolescents (ages 13–17) consecutively admitted to an intensive outpatient substance treatment program. Racial identities of participants were 40.0% Latinx, 3.6% Black, 0.9% American Indian or Alaska Native, 6.4% two or more races, and 49.1% White. A total of 67 of 110 (60.9%) youth had state-funded Medicaid or no insurance. Of the youth that engaged in treatment across all implementation phases, 68.7% were provided transportation assistance. Analyses illustrated no difference in outcomes based on selected demographic variables. The percentage of youth completing treatment was 22.7% and the average number of groups attended was 6.32 (SD = 6.49). Results showed a significant improvement in outcomes with the implementation of incentives such that engagement and retention in treatment was significantly higher for those in phase 3 compared to those in phase 1 (p < .001) and phase 2 (p = .021).

Discussion

This evaluation shows that previously documented health disparities in substance treatment engagement and retention are not found when certain barriers are addressed.
The Power of Engaging Young People in Research
Authors: Partridge Stephanie R. , Mandoh Mariam , Wardak Sara , Todd Allyson , Raeside Rebecca
Published: June 2024

Youth advisory groups (YAGs) are super teams of young people who help scientists understand what is important to people their age. In our study, we wanted to find out how being involved in a YAG benefits young people and improves scientific research. We found that when young people joined a YAG for 1 year, they gained leadership and problem-solving skills. They told us that being in a YAG made them feel their voices were heard and included. They got to share their ideas, influence decision making, and make a difference in scientific research. But it was not always easy. We learned that YAGs face challenges, like not having enough time and difficulty meeting face-to-face. Yet, with some flexibility and supportive scientists, YAGs can succeed. We learned that a small group of thoughtful and committed young people can make a big difference and help make health research better.
Publishing publicly available interview data: an empirical example of the experience of publishing interview data
Authors: Enriquez Diana
Published: June 2024

In September 2021 I made a collection of interview transcripts available for public use under a CreativeCommons license through the Princeton DataSpace. The interviews include 39 conversations I had with gig workers at AmazonFlex, Uber, and Lyft in 2019 as part of a study on automation efforts within these organizations. I made this decision because (1) I was required to contribute to a publicly available data set as a requirement of my funding and (2) I saw it as an opportunity to engage in the collaborative qualitative science experiments emerging in Science and Technology studies. This article documents my thought process and step-by-step design decisions for designing a study, gathering data, masking it, and publishing it in a public archive. Importantly, once I decided to publish these data, I determined that each choice about how the study would be designed and implemented had to be assessed for risk to the interviewee in a very deliberate way. It is not meant to be comprehensive and cover every possible condition a researcher may face while producing qualitative data. I aimed to be transparent both in my interview data and the process it took to gather and publish these data. I use this article to illustrate my thought process as I made each design decision for this study in hopes that it could be useful to a future researcher considering their own data publishing process.
Extraction of phenolic compounds from lucuma (Pouteria lucuma) seeds with natural deep eutectic solvents: modelling using response surface methodology and artificial neural networks
Authors: Puma-Isuiza Gustavo , García-Chacón Juliana María , Osorio Coralia , Betalleluz-Pallardel Indira , Chue Jorge , Inga Marianela
Published: June 2024

The present study aimed to extract polyphenolic compounds from lucuma (Pouteria lucuma) seeds using natural deep eutectic solvents (NADES) as a green, efficient, and environmentally friendly extraction. This was optimized by using the Response Surface Method (RSM) and comparing its predictive capacity with Artificial Neural Networks (ANN) and Convolutional Neural Networks (CNN). Four NADES were prepared by mixing lactic acid (LA) with each of the following reagents: sodium acetate (SA), urea (U), glucose (G), and ammonium acetate (AA), separately. The yield of total phenolic compounds (TPC) obtained from lucuma seeds with each NADES was measured as an optimization criterion with the Box-Benhken design. The following factors were evaluated: time, temperature, and the lucuma seed flour (LSF): NADES ratio. The response variables were TPC and antioxidant activity. The LA-AA extract was selected because it exhibited the highest TPC value and was analyzed by UHPLC–MS (Ultra-performance Liquid Chromatography-Mass Spectrometry). From the RSM, the optimal extraction parameters were 80 min, 52°C, and LSF: NADES ratio of 8:100 (w/v), obtaining a TPC value of 3601.51 ± 0.51 mg GAE/100 g LFS. UHPLC–MS analysis evidenced the formation of epigallocatechin isomers from epigallocatechin gallate. The predictive ability of ANNs compared to RSM was demonstrated.
Red foxes (Vulpes vulpes) and raccoon dogs (Nyctereutes procyonoides) as potential spreaders of Sarcocystis species
Authors: Máca Ondřej , Gudiškis Naglis , Butkauskas Dalius , González-Solís David , Prakas Petras
Published: June 2024

Background

Sarcocystis includes a global group of apicomplexan parasites with two-host life cycle frequently circulating in wildlife and domestic hosts, including humans. Two of the most important wild terrestrial carnivores acting as definitive hosts are the red fox and raccoon dog, due to their wide distribution in Europe and usage of wild and farmed animals as prey. This study was conducted to determine the prevalence of Sarcocystis in hunted red foxes and raccoon dogs from nine regions of the Czech Republic and to identify isolated sporocysts by molecular techniques.

Methods

Approximately 5 g of the contents of large intestine from 200 animals (197 red foxes and three raccoon dogs) were examined by flotation centrifugation coprological method. Only samples of 50 red foxes and one raccoon dog positive to Sarcocystis spp. were used for the nested PCR (nPCR) method to amplify a fragment or partial sequence on the cox1 gene. Ten species-specific primer pairs for detection of Sarcocystis spp. using farm animals as intermediate hosts were utilized.

Results

In total, 38.1% of the red foxes and 66.7% of the raccoon dogs were positive to Sarcocystis by light microscopy. The molecular characterization resulted in the identification of five species in the red fox: S. arieticanis, S. capracanis, S. cruzi, S. miescheriana, and S. tenella, while the PCR was negative for the sole raccoon dog. The highest intraspecific variation was found for S. miescheriana, while S. tenella was the most prevalent. Co-infections occurred in the large intestine of the red fox. No zoonotic species were found in our samples.

Conclusion

This is the first study where the potential role of the red fox and raccoon dogs as spreaders of Sarcocystis to farm animals in the Czech Republic is shown. The use of species-specific primers provides a fast and easy method for screening multiple samples for a particular Sarcocystis species.
RETRACTED: Eapen et al. A 6U CubeSat Platform for Low Earth Remote Sensing: DEWASAT-2 Mission Concept and Analysis. Aerospace 2023, 10, 815
Authors: Eapen Ann Mary , Bendoukha Sidi Ahmed , Al-Ali Reem , Sulaiman Abdulrahman
Published: June 2024

The Aerospace Editorial Office retracts and removes the article entitled “Eapen et al [...]
Detection of Precursors of Thermoacoustic Instability in a Swirled Combustor Using Chaotic Analysis and Deep Learning Models
Authors: Xu Boqi , Wang Zhiyu , Zhou Hongwu , Cao Wei , Zhong Zhan , Huang Weidong , Nie Wansheng
Published: June 2024

This paper investigates the role of chaotic analysis and deep learning models in combustion instability predictions. To detect the precursors of impending thermoacoustic instability (TAI) in a swirled combustor with various fuel injection strategies, a data-driven framework is proposed in this study. Based on chaotic analysis, a recurrence matrix derived from combustion system is used in deep learning models, which are able to detect precursors of TAI. More specifically, the ResNet-18 network model is trained to predict the proximity of unstable operation conditions when the combustion system is still stable. The proposed framework achieved state-of-the-art 91.06% accuracy in prediction performance. The framework has potential for practical applications to avoid an unstable operation domain in active combustion control systems and, thus, can offer on-line information on the margin of the combustion instability.
Vision System for the Mars Sample Return Capture Containment and Return System (CCRS)
Authors: Bos Brent J. , Donovan David L. , Capone John I. , Wang Chen , Hardwick Terra C. , Bell Dylan E. , Zhu Yuqing , Podgurski Robert , Rizk Bashar , Orlowski Ireneusz , Edison Rachel A. , Harvey David A. , Dizon Brianna , Haseltine Lindsay , Olsen Kristoffer C. , Sheng Chad , Bousquet Robert R. , Vo Luan Q. , Georgiev Georgi T. , Washington Kristen A. , Singer Michael J. , Ioana Stefan , Le Anloc H. , Georgieva Elena M. , Hackett Michael T. , Ravine Michael A. , Caplinger Michael , Coulter Phillip , Percy Erin , Torisky Charles , Lauenstein Jean-Marie , Ryder Kaitlyn L. , Campola Michael J. , Johnstone Dillon E. , Thomes William J. , Schnurr Richard G. , McCloskey John C. , De Marco Eugenia L. , Lee Ellen , Yew Calinda M. , Yang Bo , Han Mingyu , Blonski Bartosz
Published: June 2024

The successful 2020 launch and 2021 landing of the National Aeronautics and Space Administration’s (NASA) Perseverance Mars rover initiated the first phase of the NASA and European Space Agency (ESA) Mars Sample Return (MSR) campaign. The goal of the MSR campaign is to collect scientifically interesting samples from the Martian surface and return them to Earth for further study in terrestrial laboratories. The MSR campaign consists of three major spacecraft components to accomplish this objective: the Perseverance Mars rover, the Sample Retrieval Lander (SRL) and the Earth Return Orbiter (ERO). Onboard the ERO spacecraft is the Capture, Containment and Return System (CCRS). CCRS will capture, process and return to Earth the samples that have been collected after they are launched into Mars orbit by the Mars Ascent Vehicle (MAV), which is delivered to Mars onboard the SRL. To facilitate the processing of the orbiting sample (OS) via the CCRS, we have designed and developed a vision system to determine the OS capture orientation. The vision system is composed of two cameras sensitive to the visible portion of the electromagnetic spectrum and two illumination modules constructed from broadband light emitting diodes (LED). Vision system laboratory tests and physics-based optical simulations predict CCRS ground processing will be able to correctly identify the OS post-capture orientation using only a single vision system image that is transmitted to Earth from Mars orbit.
Effect of Powdery Mildew on the Photosynthetic Parameters and Leaf Microstructure of Melon
Authors: Tian Mei , Yu Rong , Yang Wanbang , Guo Song , Liu Shengfeng , Du Huiying , Liang Jinjin , Zhang Xingxu
Published: June 2024

Powdery mildew is a fungal disease devastating to crops, causing significant quality and yield loss. As one of the most important fruits in the world, melon also is damaged by powdery mildew. The present study investigated the effect of powdery mildew on the photosynthetic parameters and leaf microstructure of melons, the ultrastructure of the leaf surface, photosynthetic index, chlorophyll content, yield, and quality index of five thick-skinned and differently shaped melon varieties. The net photosynthetic rate, transpiration rate, leaf water use efficiency, and chlorophyll levels were significantly (p < 0.05) higher in Kangbing F3800 plants compared to the other four varieties. In the case of powdery mildew infection, the total number of stomata in the upper and lower epidermis was particularly high in the Zhongtian No. 8 and Zhongtianxueqiong varieties, respectively. The stomatal length and width were highest in the upper epidermis of Zhongtian No. 12 leaves and in the lower epidermis of Zhongtian No. 8 leaves compared to the other varieties. The total yield and meat thickness were significantly (p < 0.05) higher in the Zhongtianxueqiong variety than the others, along with the low edge sugar content. Overall, powdery mildew impacted differently the photosynthetic and leaf surface characteristics of the five melon varieties. Kangbing F3800 emerged as the most resistant variety, making it the preferred choice for introducing and promoting thick-skinned melon varieties in the Ningxia Hui Autonomous Region of China.
Chemical Control of Coffee Berry Borer Using Unmanned Aerial Vehicle under Different Operating Conditions
Authors: Cunha João Paulo Arantes Rodrigues da , Lopes Luana de Lima , Alvarenga Cleyton Batista de
Published: June 2024

The application of pesticides using unmanned aerial vehicles (UAVs) has grown, but there is a lack of information to support more efficient applications. Using a DJI AGRAS-MG-1P octocopter equipped with different spray tips, this study sought to explore spray deposition (leaves and fruit) and efficacy of chlorpyrifos on control of coffee berry borer at different spray volumes and flight heights. The study was conducted in an Arabica coffee plantation. The study consisted of eight treatments and four replications in a 2 × 2 × 2 factorial scheme: two flight heights (1.5 and 3.0 m), two spray tips (hollow cone and flat fan), and two spray volumes (10 and 15 L ha−1). Deposition was assessed by detecting a tracer in the coffee leaves and fruit using spectrophotometry. The coffee berry borer-control efficacy trial was conducted in two areas by evaluating the percentage of damaged fruit 60 days after two insecticide applications. The flight height of 1.5 m promoted higher spray deposition on leaves and fruit and a lower incidence of damaged fruit. Flat fan spray tips resulted in higher spray deposition on the leaves, not interfering with the deposition on fruit or the coffee berry borer control. Increasing the spray volume from 10 to 15 L ha−1 did not increase spray deposition on coffee leaves and fruit. Chlorpyrifos applied via UAVs reduced the incidence of coffee berry borer.
Oxidative Status, Iron Plasma Levels in Venous Thrombosis Patients
Authors: Signorelli Salvatore Santo , Barbagallo Andrea , Oliveri Conti Gea , Fiore Maria , Cristaldi Antonio , Ferrante Margherita
Published: June 2024

Exaggerated clot induces venous thrombosis (VTE); oxidative stress (OxS) can to be postulated as additional risk factor. This study evaluates firstly OxS by measuring surrogate biomarkers (malondialdehyde-MDA, 4-hydroxinonenal-4-HNE, superoxide desmutase enzyme (SOD)), secondly the iron (Fe) plasma level and thirdly the hepcidin protein (Hep) level in patients with VTE. A case control study was performed enrolling twenty hospitalized patients and an equal number of healthy individuals. In VTE patients, the following results were found. The MDA was 8.38 ± 0.5 µM/L, the 4-HNE measured 2.75 ± 0.03 µM/L and the SOD was 0.025 ± 0.01 U/mL. The I was 73.10 ± 10 µg/dL and the He was 4.77 ± 0.52 ng/mL. In the control group, the MDA measured 5.5 ± 0.6 µM/L, the 4-HNE 2.24 ± 0.021 µM/L and the SOD 0.08 ± 0.12 U/mL. The Hep was 2.1 ± 0.55 ng/mL and the Fe was 88.2 ± 9.19 µg/dL. Differences were statistically significant. Results suggest that in VTE there is activated OxS, Fe deregulation and over-production of Hep. Fe deregulation induces OxS, leading both to inflammation in the clot activator and stimulation of the pro-thrombotic status. The study highlights OxS and Fe and their regulation as intriguing indicators for risk of VTE.
Application of Convolutional Neural Networks for Classifying Penetration Conditions in GMAW Processes Using STFT of Welding Data
Authors: Kim Dong-Yoon , Lee Hyung Won , Yu Jiyoung , Park Jong-Kyu
Published: June 2024

For manufacturing components with thick plates, such as in the heavy equipment and shipbuilding industries, the gas metal arc welding (GMAW) process is applied. Among the components that apply the thick plate GMAW process, there are groove butt joints, which are fabricated through multi-pass welding. Various welding qualities are managed in multi-pass welding, and the root-pass weld is controlled to ensure complete joint penetration (CJP). Currently, the state of complete joint penetration during root-pass welding is managed visually, making it difficult to confirm the penetration condition in real time. Therefore, there is a need to predict the penetration condition in real time. In this study, we propose a convolutional neural network (CNN)-based prediction model that can classify penetration conditions using welding current and voltage data from the root pass of V-groove butt joints. The root gap of the joints was varied between 1.0 and 2.0 mm, and the wire feed rate was adjusted. During welding, the current and voltage were measured. The welding current and voltage are transformed into a short-time Fourier transform (STFT) representation depicting the arc and wire extension lengths. The transformed dynamic resistance STFT information serves as the input variable for the CNN model. Preprocessing steps, including thresholding, are applied to optimize the input variables. The CNN architecture comprises three convolutional layers and two pooling layers. The model classifies penetration conditions as partial joint penetration (PJP), CJP, and burn-through, achieving a high accuracy of 97.8%. The proposed method facilitates the non-destructive evaluation of the root-pass welding quality without expensive monitoring equipment, such as vision cameras. It is expected to be immediately applied to the thick plate welding process using readily available welding data.
FES Control of a Finger MP Joint with a Proxy-Based Super-Twisting Algorithm
Authors: Chen Hua , Xiong Xiaogang , Honda Koki , Okunami Shouta , Yamamoto Motoji
Published: June 2024

To improve motion accuracy through functional electrical stimulation (FES) of forearm muscles, feedback control laws are applied to the index finger’s metacarpophalangeal (MP) joint. This paper introduces a proxy-based super-twisting algorithm (PSTA) for precise servo control of MP joints via FES. The PSTA combines first-order sliding mode control with a second-order super-twisting algorithm, effectively preventing windup during FES saturation and ensuring robust, accurate control. An implicit Euler method minimizes numerical chattering in the digital implementation. Experiments with Arduino and volunteers confirm the algorithm’s effectiveness.
Text Classification Model Based on Graph Attention Networks and Adversarial Training
Authors: Li Jing , Jian Yumei , Xiong Yujie
Published: June 2024

Text information on the internet often has a strong sense of immediacy, constantly reflecting societal dynamics and evolving events. This is especially crucial in the field of news text, where the classification and analysis of these immediate and varied text data become essential. Existing text classification models frequently struggle to effectively represent the semantic and local feature information of texts, limiting their effectiveness. The primary challenge lies in improving the representation of both semantic and local feature information in text classification models, which is critical for capturing the nuanced meanings in rapidly evolving news texts. This paper proposes a deep learning-driven framework designed to enhance the effectiveness of text classification models. The method incorporates noise perturbation during training for adversarial training, thereby enhancing the model’s generalization ability on original samples and increasing its robustness. A graph attention network is employed to extract the contextual semantic information of vocabulary from sequential texts. This information is then combined with extracted sentence feature information to enrich the feature representation of the sequence. An attention mechanism is also introduced to extract more critical feature information from the text, thereby deepening the understanding of textual semantic information. Experimental results demonstrate that this method successfully integrates the boundary and semantic information of vocabulary into the classification task. The approach comprehensively and deeply mines the semantic features of the text, leading to improved classification performance.
Investigation and Utilization of Alkali-Activated Grouting Materials Incorporating Engineering Waste Soil and Fly Ash/Slag
Authors: Wang Zhijia , Li Haojie , Duan Shusu , Feng Zhisheng , Zhang Youliang , Zhang Jianjing
Published: June 2024

The alkali-activated composites technique is a promising method for the in situ preparation of cavity filling/grouting materials from engineering waste soil. To investigate the feasibility of engineering waste soil utilization by the alkali activation process, the macroscopic and microscopic properties of the fly ash/slag-based alkali-activated composites, after solidification/stabilization (S/S) with sandy clay excavated at Baishitang Station of Shenzhen Metro, were studied. The unconfined compressive strength (UCS) test was conducted to evaluate the S/S effect of alkali-activated composites. The results show that the optimum quality ratio of slag and fly ash correspond to 7:3, the modulus of alkaline activator to 1.3, and the alkalinity of alkaline activator to 10%. The alkali-activated composite’s strength under these parameters can reach 45.25 MPa at 3 days, 49.85 MPa at 7 days, and 62.33 MPa at 28 days. A maximum 3-day UCS of 21.71 MPa, 75% of the 28-day UCS, was achieved by an engineering waste soil and alkali-activated composites mass ratio of 5:5, slaked lime content of 4.5%, and a water-to-solid ratio of 0.26, and it can also meet the required fluidity and setting time for construction well. Fluidity is primarily affected by the soil-to-binder ratio, which decreases as the ratio decreases, while the water-to-solid ratio increases fluidity. Slaked lime has minimal impact on fluidity. The setting time is mainly influenced by the soil-to-binder ratio, followed by slaked lime content and water-to-solid ratio, with setting time shortening as the soil-to-binder ratio and slaked lime content increase, and lengthening as the water-to-solid ratio increases. Through Fourier Transform Infrared Spectroscopy (FTIR), Scanning Electron Microscopy (SEM), and Energy Dispersive Spectroscopy (EDS) tests, microscopic analysis showed that loose granular units are firmly cemented by alkali-activated composites. Based on the results of on-site grouting tests in karst caves, the alkali-activated grout materials reached a strength of 5.2 MPa 28 days after filling, which is 162.5% of the strength of cement grouting material, satisfying most of the requirements for cavity filling in Shenzhen.
Two Coffee Diterpenes, Kahweol and Cafestol, Inhibit Extracellular Melanogenesis: An In Vitro Pilot Study
Authors: Goenka Shilpi
Published: June 2024

Hyperpigmentation skin disorders are marked by an abnormal accumulation or export of melanin pigment synthesized within melanocytes and pose a significant aesthetic concern. The search for novel natural compounds that exhibit pharmacological potential for treating pigmentation disorders is growing. In this study, kahweol (KW) and cafestol (CFS), two structural analogs of coffee diterpenes, were evaluated and compared for their effects on melanogenesis using B16F10 mouse melanoma cells and primary human melanocytes derived from Asian and African American skin. To the best of our knowledge, there are no reports of the effects of KW and CFS on melanogenesis yet. We first screened nontoxic concentrations of both compounds using an MTS assay after 72 h incubations and subsequently tested their effects on melanin synthesis and export. Cellular tyrosinase activity and cell-free mushroom tyrosinase activity were assayed to study the mechanisms of melanogenesis suppression. Human melanocytes from a moderately pigmented donor (HEMn-MP cells) and from a darkly pigmented donor (HEMn-DP cells) were next examined, and effects on cellular viability, melanin content, cellular tyrosinase activity, and melanin export (quantitated via dendricity) were similarly examined for both compounds. Our results show that KW and CFS did not significantly affect intracellular melanin content but suppressed extracellular melanin in B16F10 cells and dendritic parameters in human melanocytes, indicating their unique capacity to target extracellular melanogenesis and melanin export. Although KW showed a greater extracellular melanogenesis inhibitory capacity in B16F10 cells, in both primary melanocyte cells, CFS emerged as a potent inhibitor of melanin export compared to KW. Together, these results reveal novel modes of action of both compounds and indicate a promise to use CFS as a novel candidate for treating hyperpigmentation disorders of the human skin for clinical and cosmetic use. Additional research is necessary to shed light on the molecular pathways and the efficacy of melanogenesis inhibition by CFS in 3D human skin equivalents and in vivo studies.
Endolithic Fungal Diversity in Antarctic Oligocene Rock Samples Explored Using DNA Metabarcoding
Authors: Rabelo Natana G. , Gonçalves Vívian N. , Carvalho Marcelo A. , Scheffler Sandro M. , Santiago Gustavo , Sucerquia Paula A. , Oliveira Fabio S. , Campos Larissa P. , Lopes Fabyano A. C. , Santos Karita C. R. , Silva Micheline C. , Convey Peter , Câmara Paulo E. A. S. , Rosa Luiz H.
Published: June 2024

In this study, we evaluated the fungal diversity present associated with cores of Oligocene rocks using a DNA metabarcoding approach. We detected 940,969 DNA reads grouped into 198 amplicon sequence variants (ASVs) representing the phyla Ascomycota, Basidiomycota, Mortierellomycota, Chytridiomycota, Mucoromycota, Rozellomycota, Blastocladiomycota, Monoblepharomycota, Zoopagomycota, Aphelidiomycota (Fungi) and the fungal-like Oomycota (Stramenopila), in rank abundance order. Pseudogymnoascus pannorum, Penicillium sp., Aspergillus sp., Cladosporium sp., Aspergillaceae sp. and Diaporthaceae sp. were assessed to be dominant taxa, with 22 fungal ASVs displaying intermediate abundance and 170 being minor components of the assigned fungal diversity. The data obtained displayed high diversity indices, while rarefaction indicated that the majority of the diversity was detected. However, the diversity indices varied between the cores analysed. The endolithic fungal community detected using a metabarcoding approach in the Oligocene rock samples examined contains a rich and complex mycobiome comprising taxa with different lifestyles, comparable with the diversity reported in recent studies of a range of Antarctic habitats. Due to the high fungal diversity detected, our results suggest the necessity of further research to develop strategies to isolate these fungi in culture for evolutionary, physiological, and biogeochemical studies, and to assess their potential role in biotechnological applications.
Predictors of Speech-in-Noise Understanding in a Population of Occupationally Noise-Exposed Individuals
Authors: Andéol Guillaume , Paraouty Nihaad , Giraudet Fabrice , Wallaert Nicolas , Isnard Vincent , Moulin Annie , Suied Clara
Published: June 2024

Understanding speech in noise is particularly difficult for individuals occupationally exposed to noise due to a mix of noise-induced auditory lesions and the energetic masking of speech signals. For years, the monitoring of conventional audiometric thresholds has been the usual method to check and preserve auditory function. Recently, suprathreshold deficits, notably, difficulties in understanding speech in noise, has pointed out the need for new monitoring tools. The present study aims to identify the most important variables that predict speech in noise understanding in order to suggest a new method of hearing status monitoring. Physiological (distortion products of otoacoustic emissions, electrocochleography) and behavioral (amplitude and frequency modulation detection thresholds, conventional and extended high-frequency audiometric thresholds) variables were collected in a population of individuals presenting a relatively homogeneous occupational noise exposure. Those variables were used as predictors in a statistical model (random forest) to predict the scores of three different speech-in-noise tests and a self-report of speech-in-noise ability. The extended high-frequency threshold appears to be the best predictor and therefore an interesting candidate for a new way of monitoring noise-exposed professionals.