bluuebunny/crossref_metadata_2025 huggingface dataset:
Sarcopenia increases the risk of early biliary infection after percutaneous transhepatic biliary stent placement
Authors: Chen Qi , Lu Xun , Wang Zhong-kai , Feng Cheng , Yao Xi-Juan , Guo Jin-He
Published: December 2022

Purpose

To assess the association between sarcopenia and the risk of early biliary infection (EBI) after percutaneous transhepatic biliary stent (PTBS) placement in patients with inoperable biliary tract cancer (BTC).

Patients and methods

In this single center, retrospective observational study, patients diagnosed with inoperable BTC undergoing PTBS placement between January 2013 and July 2021 were enrolled. Preoperative sarcopenia was defined based on skeletal muscle mass measured by computed tomography images on the level of third lumbar vertebra within one month before PTBS placement. Patients were divided into two groups in accordance with the status of sarcopenia. Univariate and further multivariate logistic analyses were performed to determine predictors for EBI. Stratified and interactive analyses were conducted to investigate the stability of results. Further receiver operating characteristic curve was performed to determine the predictive value of sarcopenia on EBI after PTBS placement.

Results

Totally, 134 patients were included in this retrospective study, with 45 (33.6%) patients characterized as sarcopenia. The incidence rate of EBI was 26.9% (36/134). Multivariate analyses demonstrated that sarcopenia [Odds ratio (OR), 2.75; 95%CI: 1.11–6.77; P=0.028], obstruction length (OR, 1.04; 95%CI: 1.00–1.08; P=0.030) and diabetes (OR, 2.46; 95%CI: 1.01–5.96; P=0.047) were significant predictors of EBI. There were no significant interactions in different subgroups (P for interaction > 0.05). Moreover, the areas under the curves (AUC) revealed that the combined index containing sarcopenia, obstruction length, and diabetes showed the better predictive value (AUC= 0.723) than either one alone.

Conclusion

Sarcopenia increased the risk of EBI in patients with inoperable BTC after PTBS placement. Preoperative assessment of sarcopenia may aid in risk stratification. Patients with sarcopenia should be given intensive monitoring.
Presumptive bacteriological diagnosis of spondylodiscitis in infants less than 4 years by detecting K. kingae DNA in their oropharynx: Data from a preliminar two centers study
Authors: Chargui Moez , Krzysztofiak Andrzej , Bernaschi Paola , De Marco Giacomo , Coulin Benoit , Steiger Christina , Dayer Romain , Ceroni Dimitri
Published: December 2022

Background and Objectives

Most cases of spondylodiscitis in children aged between 6 and 48 months old could be caused primarily by K. kingae. The present prospective study aimed to determine whether an innovative and indirect diagnosis approach - based on detection of K. kingae DNA in the oropharynx of children with suspected spondylodiscitis – provides sufficient evidence that this microorganism is responsible for the infection.

Methods

We prospectively analysed infants admitted for spondylodiscitis, considering above all the results of PCR realized in oropharyngeal swabs and in blood samples.

Results

Four of the 29 performed K. kingae-specific real-time PCR assay in blood were positive (13.8%), whereas 28 of the 32 K. kingae-specific real-time PCR assay realized on throat swabs were positive (87.5%).

Conclusions

This study demonstrates that performing oropharyngeal swab PCR is able to detect K. kingae in almost 90% of the toddlers with confirmed spondylodiscitis. That provides strong arguments for the hypothesis that K. kingae should be considered as the main aetiological pathogen to suspect in children between 6 and 48 months old with spondylodiscitis. Finally, it seems to us reasonable that oropharyngeal swab may become an early decision-making tool for the indirect identification of K. kingae in spondylodiscitis.
Qualitative and quantitative analysis of the bioactive components of “ginseng–polygala” drug pair against PC12 cell injury based on UHPLC-QTOF-MS and HPLC
Authors: Wang Zhengyang , Sun Xiaomeng , Zhao Yue , Ga Liba , Li Qi , Li Qian , Wang Xiaotong , Yang Chunjuan
Published: December 2022

Aβ25-35-induced PC12 cells were used as the in vitro injury model to evaluate the effects on PC12 cells after intervention with the “ginseng–polygala” drug pair. The results showed that the drug pair could significantly increase cell activity and reduce the level of reactive oxygen species and the concentration of inflammatory factors to improve the Alzheimer’s disease treatment process. Furthermore, to rapidly identify and classify complicated bioactive components of the drug pair, a liquid chromatography with quadrupole time-of-flight mass spectrometry method combined with a molecular network strategy was established. With this strategy, 40 constituents were preliminarily identified and a database of the compounds was successfully established. Among them, 12 compounds of different categories were accurately identified by comparison with reference substances. The content of the aforementioned active components was simultaneously determined by HPLC to control the quality of compatible medicinal materials, and the verification results of the analytical method met the content determination requirements. The results revealed that after compatibility, the content change of the components is not the simple addition of quantity but the comprehensive effect of the two medicines. In conclusion, this study could provide a generally applicable strategy for pharmacological activity, structural identification, and content determination in traditional Chinese medicine and its compatibility.
Ophiopogonin D increase apoptosis by activating p53 via ribosomal protein L5 and L11 and inhibiting the expression of c-Myc via CNOT2
Authors: Ko Hyun Min , Jee Wona , Lee Duckgue , Jang Hyeung-Jin , Jung Ji Hoon
Published: December 2022

Ophiopogonin D (OP-D), which is extracted from the root tuber of Ophiopogon japonicus, is well known for its anti-inflammatory, anti-oxidant, and anti-cancer effects. It is also therapeutic for various diseases such as diabetic myocardial injuries, obesity, atopic dermatitis, and osteoporosis. However, there are insufficient reports on the anti-cancer effects and molecular mechanisms of OP-D in colorectal cancer. Therefore, this study aimed to investigate the anti-cancer-modulating effect of OP-D on colorectal cancer. The study proved that OP-D (20–40 uM) has significant cell viability inhibition and anti-proliferative effects in Cell Counting Kit-8 (CCK-8) assay and colony formation assay. In addition, our immunofluorescence analysis data showed that OP-D (40 uM) inhibited the expression of Ki67, a cell proliferation marker, and confirmed that OP-D could induce nucleolar stress by depletion of IPO7 and XPO1. Furthermore, our western blot data showed that OP-D induced p53 expression via ribosomal protein (RP) L5 or L11 and inhibited c-Myc expression through CNOT2 in a dose-dependent manner. Additionally, OP-D regulated cyclin D1 and CDK4, which are well known as cell cycle regulatory proteins. OP-D consistently inhibited the phosphorylation of AKT expression in a dose-dependent manner. Furthermore, OP-D shortened c-Myc’s half-life in a time-dependent manner. Furthermore, CNOT2 knockdown enhanced the inhibitory effect of OP-D on c-Myc in colon cancer cells. Besides that, we confirmed that OP-D has a combinational anti-cancer effect of 5-FU or doxorubicin to reduce cell viability and induce apoptosis through p53 and c-Myc regulation. Altogether, our results suggest that OP-D regulates colon cancer cell proliferation and induces apoptosis by inhibiting c-Myc expression via activation of p53 and CNOT2 regulation. The study demonstrated that OP-D may be a promising natural anti-cancer agent for the treatment of colorectal cancer.
Sharpening the tip of the spear: Tailoring performance psychology for Special Operation Forces
Authors: Ytterbøl Christian , Collins Dave , MacPherson Alan
Published: December 2022

As performance psychology expands to address different environments, military settings are viewed as a natural extension. In certain cases, however, we suggest that a sub-optimal approach has been employed, due to a lack of specific knowledge of military culture and context, coupled with a diminished emphasis on conducting psychological research targeted directly on military performance. In this paper we explore the specific and importantly unique challenges encountered when researching and consulting with Special Operation Forces (SOF) within the North Atlantic Treaty Organization (NATO) alliance. To support both researchers and practitioners, we offer an overview of the current state of knowledge in this specific domain. We highlight key differences between SOF and conventional forces, then look at the specific requirements for developing performance psychology in the SOF context. Finally, we offer some perspectives on where opportunities might have been missed and offer some suggestions for more impactful (and accurate) research and practice.
Meaning in life, meaning-making and posttraumatic growth in cancer patients: Systematic review and meta-analysis
Authors: Almeida Margarida , Ramos Catarina , Maciel Laura , Basto-Pereira Miguel , Leal Isabel
Published: December 2022

Introduction

The purpose of this systematic review and meta-analysis is to assess the association between meaning in life (MiL), meaning-making and posttraumatic growth (PTG) in the context of cancer.

Methods

A systematic search was conducted in eighteen electronic databases. The screening and selection process followed the PRISMA guidelines. For the purpose of the meta-analysis, the correlation coefficients between meaning in life and posttraumatic growth were extracted from the included studies. The effect size (r) was calculated using the restricted maximum-likelihood estimator, a random-effects model. Heterogeneity was assessed through the Q statistic, I2 index and forest plot, while publication bias was analyzed with the use of the funnel plot and Egger’s test.

Results

889 records were considered according to the inclusion criteria. A total of nine articles, published between 2006 and 2021, were included in the systematic review. More than half were published in the last five years. The sample was mostly diagnosed with breast cancer. The meta-analysis included five articles (N = 844) and the results indicate a significant moderate correlation between meaning in life and posttraumatic growth (r = 0.43, 95% IC [0.36, 0.50]).

Discussion

In conclusion, there is a clear association between meaning in life and posttraumatic growth in cancer patients. Future research should explore this relationship further, in order to better assist and guide meaning centered interventions that can potentiate a positive adjustment and possibly growth from the cancer experience.
A microswitch-aided program to enable people with extensive multiple disabilities to control environmental stimulation through different responses
Authors: Lancioni Giulio E. , Singh Nirbhay N. , O'Reilly Mark F. , Sigafoos Jeff , Alberti Gloria , Chiariello Valeria , Desideri Lorenzo
Published: December 2022

Objectives

This study assessed whether a simple technology-aided program (i.e., a program involving the use of microswitches linked to a smartphone) could be set up to enable people with motor, sensory and intellectual disabilities to control preferred environmental stimulation through two different response movements.

Methods

Ten participants were involved in the study. Each of them was exposed to an ABAB design, in which A represented baseline phases without the program and B intervention phases with the use of the program. The study assessed whether the participants (a) had significant increases of each of the two response movements available and/or showed response variability across sessions and over time and (b) had signs of satisfaction/happiness during the study sessions, in connection with their stimulation access and control.

Results

The program was effective in increasing the participants' responding and consequently their self-regulated stimulation input. Half of the participants showed a significant increase of both responses available from the first intervention phase. Other participants seemed to focus more on one of the two responses. Even so, they tended to have occasionally high performance frequencies also with regard to their non-dominant (not significantly increased) response. Finally, all participants showed clear signs of satisfaction/happiness during the intervention sessions.

Conclusions

The program represents a potentially useful approach for enabling people with extensive multiple disabilities to self-regulate their access to preferred environmental stimulation and improve their mood.
Association between early childhood caries and diet quality among Chinese children aged 2–5 years
Authors: Wang Xinfeng , Ma Zhe , Lei Min , Zhao Caiyun , Lin Xiuyan , Cao Fengdi , Shi Hong
Published: December 2022

Background

Early childhood caries (ECC) is a major oral problem affecting the health and wellbeing of children worldwide. Diet quality is a better predictor of ECC risk than single foods or specific nutrients. The purposes of this study were to assess the associations between ECC and diet quality among 2- to 5-year-old Chinese children.

Methods

A total of 150 eligible children were included in this study. The decayed, missing, or filled surface (dmfs) score was recorded for each child by dental examination. All participants were divided into three groups based on their age and dmfs score [the caries-free group, the ECC group, and the severe early childhood caries (S-ECC) group]. Parents were invited to complete a questionnaire on the general characteristics and oral health behaviors of the participants. The information of 24-h dietary intake from each child was captured via a mobile APP. The Chinese diet balance index for preschool children (DBI_C) indicators score, high bound score (HBS), low bound score (LBS), and diet quality distance (DQD) score were calculated to assess the diet quality of study subjects. The associations of ECC with HBS, LBS, DQD score, and DBI_C indicators score were analyzed by Mann-Whitney U test and multivariable logistic regression analysis.

Results

In this study, 21, 31, and 98 children were diagnosed with caries-free, ECC, and S-ECC, respectively. Statistical analysis revealed that the risk of ECC and S-ECC were significantly increased with the DQD score (OR = 1.283 and 1.287, respectively), but both were not associated with HBS and LBS (P > 0.05). In the meantime, the risk of ECC and S-ECC were significantly increased with the Grains score (OR = 1.623 and 1.777, respectively), and significantly decreased with the Food diversity score (OR = 0.271 and 0.315, respectively). Moreover, the risk of S-ECC also significantly decreased with the Vegetables score (OR = 0.137).

Conclusion

Both ECC and S-ECC were associated with a high degree of dietary imbalance and grains intake as well as a low degree of food diversity among Chinese children aged 2–5 years. In addition, S-ECC was also associated with a low degree of vegetable intake.
Acceptability of wearable inertial sensors, completeness of data, and day-to-day variability of everyday life motor activities in children and adolescents with neuromotor impairments
Authors: Rast Fabian Marcel , Herren Silvia , Labruyère Rob
Published: December 2022

Monitoring the patients' motor activities in a real-world setting would provide essential information on their functioning in daily life. In this study, we used wearable inertial sensors to monitor motor activities of children and adolescents with congenital and acquired brain injuries. We derived a set of clinically meaningful performance measures and addressed the following research questions: Is the target population willing to wear the sensors in their habitual environment? Which factors lead to missing data, and can we avoid them? How many measurement days are needed to obtain reliable estimates of the children's and adolescents' motor performance? The study participants wore our sensor system for seven consecutive days during waking hours. First, we derived the daily hand use of all participants, the duration of different body positions and the wheeling activity of individuals using a manual wheelchair, and walking-related measures in individuals being able to walk. Then, we analyzed the reasons for missing data and determined the reliability of the performance measures mentioned above. The large majority (41 of 43 participants) was willing to wear the sensor system for a week. However, forgetting to reattach the sensors after charging them overnight and taking them off during bathing and swimming was the main contributor to missing data. Consequently, improved battery life and waterproofness of the sensor technology are essential requirements for measurements in daily life. Besides, 5 of 11 performance measures showed significant differences between weekdays and weekend days. The reliability, measured with the intraclass correlation coefficient, ranged between 0.82 and 0.98. Seven measurement days were enough to obtain significantly higher reliability scores than the desired level of 0.8 for all but two performance measures. In children and adolescents with neuromotor impairments, we recommend monitoring everyday life motor activities on seven consecutive days. The target population accepted this measurement protocol, it covers school days and weekend days, and the number of measurement days is sufficient to obtain reliable estimates of motor performance.
A window into magnetic reconnection: IRIS observations of the consequences of reconnection during solar flares
Authors: Reeves Katharine K.
Published: December 2022

Magnetic reconnection is a dynamic process that occurs in solar flares in a tenuous and hot environment. High-cadence, high-spatial resolution spectroscopic observations with the Interface Region Imaging Spectrometer (IRIS) have provided a unique window into the reconnection process that occurs during solar flares. IRIS has observed many consequences of the reconnection process, including detailed observations of outflows that are thought to be indicative of reconnection, possible observations of the termination shocks that are predicted by-products of reconnection, and observations of flare ribbons which are imprints of the reconnection process in the chromosphere. This paper will review these observations and put them in the context of flare models that predict reconnection signatures.
Physical fitness assessment in wheelchair basketball: A mini-review
Authors: Petrigna Luca , Pajaujiene Simona , Musumeci Giuseppe
Published: December 2022

Introduction

Wheelchair basketball (WB) is a Paralympic sport ideated for people with motor disabilities, and the research on this topic still requires attention. It is fundamental to evaluate physical fitness characteristics with appropriate tests and standardized routines to plan and monitor the training. Considering that a standard operating procedure is a document that makes the test battery replicable, the objective of the present study was to review the literature on physical fitness assessment in WB players and to create a standard operating procedure.

Methods

Studies were collected from different databases, and after a screening process, data were discussed narratively.

Results

Only 18 articles met the eligibility criteria. The test batteries presented similarities in different studies.

Conclusion

The suggested standard operating procedure consists of 10-min warm-up followed by handgrip evaluation (only if the instrument is available), 20-m sprint test, maximal pass, modified push-up, back scratch test, and the Yo-Yo intermittent recovery test adapted test Version 1.
Cell Fault Identification and Localization Procedure for Lithium-Ion Battery System of Electric Vehicles Based on Real Measurement Data
Authors: Kocsis Szürke Szabolcs , Sütheö Gergő , Apagyi Antal , Lakatos István , Fischer Szabolcs
Published: December 2022

Vehicle safety risk can be decreased by diagnosing the lithium-ion battery system of electric road vehicles. Real-time cell diagnostics can avoid unexpected occurrences. However, lithium-ion batteries in electric vehicles can significantly differ in design, capacity, and chemical composition. In addition, the battery monitoring systems of the various vehicles are also diverse, so communication across the board is not available or can only be achieved with significant difficulty. Hence, unique type-dependent data queries and filtering are necessary in most cases. In this paper, a Volkswagen e-Golf electric vehicle is investigated; communication with the vehicle was implemented via an onboard diagnostic port (so-called OBD), and the data stream was recorded. The goal of the research is principally to filter out, identify, and localize defective/weak battery cells. Numerous test cycles (constant and dynamic measurements) were carried out to identify cell abnormalities (so-called deviations). A query and data filtering process was designed to detect defective battery cells. The fault detection procedure is based on several cell voltage interruptions at various loading levels. The methodology demonstrated in this article uses a fault diagnosis technique based on voltage abnormalities. In addition, it employs a hybrid algorithm that executes calculations on measurement and recorded data. In the evaluation, a status line comprising three different categories was obtained by parametrizing and prioritizing (weighting) the individual measured values. It allows the cells to be divided into the categories green (adequate region), yellow (to be monitored), and red (possible error). In addition, several querying strategies were developed accordingly to clarify and validate the measurement results. The several strategies were examined individually and analyzed for their strengths and weaknesses. Based on the results, a data collection, processing, and evaluation strategy for an electric vehicle battery system have been developed. The advantage of the developed algorithm is that the method can be adapted to any electric or hybrid vehicle battery.
Evaluation, Comparison and Monitoring of Multiparameter Systems by Unified Graphic Visualization of Activity Method on the Example of Learning Process
Authors: Uglev Viktor , Sychev Oleg
Published: December 2022

The article discusses the problem of visualization of complex multiparameter systems, defined by datasets on their structure, functional structure, and activity in the form of complex graphs and transition of traditional representation of the data acquired by graph mining to a compact image built by pictographic methods. In these situations, we propose using the Unified Graphic Visualization of Activity (UGVA) method for data concentration and structuring. The UGVA method allows coding in an anthropomorphic image of elements of graphs with data on structural and functional features of systems and overlaying these images with the data on the system’s activity using coloring and artifacts. The image can be composed in different ways: it can include the zone of integral evaluation parameters, segmented data axes of five types, and four types of symmetry. We describe the method of creating UGVA images, which consists of 13 stages: the parametric model is represented as a structural image that is converted to a basic image that is then detailed into the particular image by defining geometric parameters of the primitives and to the individualized image with the data about a particular object. We show how the individualized image can be overlaid with the operative data as color coding and artifacts and describe the principles of interpreting UGVA images. This allows solving tasks of evaluation, comparison, and monitoring of complex multiparameter systems by showing the decision-maker an anthropomorphic image instead of the graph. We describe a case study of using the UGVA method for visualization of data about an educational process: curricula and graduate students, including the data mined from the university’s learning management system at the Siberian Federal University for students majoring in “informatics and computing”. The case study demonstrates all stages of image synthesis and examples of their interpretation for situation assessment, monitoring, and comparison of students and curricula. It allowed for finding problematic moments in learning for individual students and their entire group by analyzing the development of their competence profiles and formulating recommendations for further learning. The effectiveness of the resulting images is compared to the other approaches: elastic maps and Chernoff faces. We discuss using graph mining to generate learning problems in order to lessen the workload of gathering raw data for the UGVA method and provide general recommendations for using the UGVA method based on our experience of supporting decision making.
The Relationship between Demographics and Knowledge Risk Perception of High School Teachers: Training as a Mediator
Authors: Borgia Michele , Nissi Eugenia , La Torre Maura , Ortolani Guido
Published: December 2022

As a knowledge-based career, teachers can be exposed to knowledge risks. Since risk perception is the product of the experiences, values, memories and ideologies of individuals, the ways of perceiving knowledge risks could be useful for setting up prevention and mitigation strategies for these kinds of risks. The present paper aimed at analyzing the relationship between the demographics and the knowledge risk perception of high school teachers. The role of a teacher’s training as a mediator of said relationship was analyzed as well. Using a sample of high school teachers working in Italian schools, a questionnaire was administered to gather data, and structural equation modeling analysis was employed to test the hypotheses. The results showed that demographics had a significant effect on teachers’ knowledge risk perception and that training mediated this relationship. The study could be helpful for educational institutions that want to train their teachers to be prepared to face risky events related to knowledge management.
Chemical Profile, Bioactivity, and Biosafety Evaluations of Essential Oils and Main Terpenes of Two Plant Species against Trogoderma granarium
Authors: Almadiy Abdulrhman , Nenaah Gomah
Published: December 2022

In order to search for bio-rational and eco-friendly pest control agents to protect crops from insect infestation, while avoiding the toxic hazards of chemical pesticides, essential oils (EOs) were hydrodistilled from Juniperus procera and Thymus vulgaris and analyzed using gas chromatography–flame ionization detection (GC–FID), and gas chromatography–mass spectrometry (GC–MS). Eugenol (71.3%), β-caryophyllene (11.8%), and α-pinene (6.1%) were isolated as the major components of J. procera EO, whereas thymol (58.1%), p-cymen (10.3%), and carvacrol (8.3%) were the main terpenes in T. vulgaris EO. The EOs and terpenes exhibited considerable bioactivity against the khapra beetle using the contact and fumigation bioassays, where T. vulgaris EO was superior in bioactivity. Among the terpenes tested, carvacrol and eugenol were superior. Regarding contact toxicity using impregnated filter paper and after 24 h of exposure, the LC50 values ranged between 21.4 and 77.0 µL/cm2 against larvae and between 16.1 and 69.6 µL/cm2 against adults. After 48 h, these values decreased remarkably. Upon fumigation and after 48 h of exposure, the LC50 values ranged between 23.0 and 65.3 µL/L against larvae, and from 14.2 to 56.4 µL/L against adults. The botanicals effectively inhibited the acetylcholinesterase activity of the larvae; however, they were safe for the earthworm E. fetida and did not alter the viability of wheat grains. There is a potential for using these botanicals to control T. granarium. However, further investigations are needed to confirm the safety of these phytochemicals before use as grain protectants on a commercial scale.
Evaluation of Indian Mustard Genotypes for White Rust Resistance Using BjuWRR1Gene and Their Phenotypic Performance
Authors: Devi Yengkhom Sanatombi , Devi Th. Renuka , Thakur Ajay Kumar , Ngangkham Umakanta , Devi H. Nanita , Kh. Pramesh , Sinha Bireswar , Senjam Pushparani , Singh N. Brajendra , Mishra Lokesh Kumar
Published: December 2022

The present investigation was carried out to identify the potential donors of resistant gene(s)/the source of white rust disease in B. juncea using 30 genotypes, including locally adapted accessions and advanced breeding lines. Out of 30 genotypes, ten lines viz. Bio-YSR, CAULC-1, CAULC-2, CAULC-3, CAULC-4, CAURM-2, CAULR-7, CAURM-4, CAURM 4-1, and CAURM 4-2 exhibited a lower PDI value (lesser than mean 10.83) with a superior agronomic performance related with the disease. The evaluation of these ten genotypes for the presence of the BjuWRR1 gene using a gene-based marker depicted the presence of the functional allele of the BjuWRR1 gene in the five genotypes viz., Bio-YSR, CAULC-1, CAULC-3, CAURM 4-1 and CAURM 4-2. When compared with the sequenced amplicon of these genotypes, it is found to be identical with that of an east European Brassica juncea line, Donskaja-IV, the completely resistant genotype against various isolates of Albugo candida. The findings from the present study suggested that besides Bio-YSR, the local lines of Manipur CAULC-1 (Local Yella of Potshangbam) and CAULC-3 (Local Yella of Kakching Lamjao) can be used as the potential white rust resistance sources/donors in disease resistance breeding programmes for the development of elite B. juncea cultivars in the future. In addition to the local lines, two improved advanced lines, viz. CAURM 4-1 and CAURM 4-2, obtained from a hybridization programme, may be further evaluated for releasing resistant varieties against white rust.
Design and Preparation of Antimicrobial Agents
Authors: Hrast Martina
Published: December 2022

Improper use and misuse of antibacterial agents have led to the emergence of (multi)resistant bacterial strains, which are 1 of the top-10 public-health threats, according to the WHO [...]
Occurrence and Genomic Characterization of mcr-1-Harboring Escherichia coli Isolates from Chicken and Pig Farms in Lima, Peru
Authors: Carhuaricra Dennis , Duran Gonzales Carla G. , Rodríguez Cueva Carmen L. , Ignacion León Yennifer , Silvestre Espejo Thalia , Marcelo Monge Geraldine , Rosadio Alcántara Raúl H. , Lincopan Nilton , Espinoza Luis Luna , Maturrano Hernández Lenin
Published: December 2022

Resistance to colistin generated by the mcr-1 gene in Enterobacteriaceae is of great concern due to its efficient worldwide spread. Despite the fact that the Lima region has a third of the Peruvian population and more than half of the national pig and poultry production, there are no reports of the occurrence of the mcr-1 gene in Escherichia coli isolated from livestock. In the present work, we studied the occurrence of E. coli carrying the mcr-1 gene in chicken and pig farms in Lima between 2019 and 2020 and described the genomic context of the mcr-1 gene. We collected fecal samples from 15 farms in 4 provinces of Lima including the capital Lima Metropolitana and recovered 341 E. coli isolates. We found that 21.3% (42/197) and 12.5% (18/144) of the chicken and pig strains were mcr-1-positive by PCR, respectively. The whole genome sequencing of 14 mcr-1-positive isolates revealed diverse sequence types (e.g., ST48 and ST602) and the presence of other 38 genes that confer resistance to 10 different classes of antibiotics, including beta-lactamase blaCTX-M-55. The mcr-1 gene was located on diverse plasmids belonging to the IncI2 and IncHI1A:IncHI1B replicon types. A comparative analysis of the plasmids showed that they contained the mcr-1 gene within varied structures (mikB–mcr1–pap2, ISApl1–mcr1–pap2, and Tn6330). To the best of our knowledge, this is the first attempt to study the prevalence of the mcr-1 gene in livestock in Peru, revealing its high occurrence in pig and chicken farms. The genetic diversity of mcr-1-positive strains suggests a complex local epidemiology calling for a coordinated surveillance under the One-Health approach that includes animals, retail meat, farmers, hospitals and the environment to effectively detect and limit the spread of colistin-resistant bacteria.
Bioactive Activities of the Phenolic Extract from Sterile Bracts of Araucaria angustifolia
Authors: Fischer Thaís Estéfane , Marcondes Amanda , Zardo Danianni Marinho , Nogueira Alessandro , Calhelha Ricardo C. , Vaz Josiana A. , Barros Lillian , Zielinski Acácio Antonio Ferreira , Alberti Aline
Published: December 2022

Sterile bracts can represent 80% of Araucaria angustifolia pinecone and are a rich source of phenolic compounds. This study aimed to optimize the extraction of the phenolic compounds from Araucaria angustifolia bracts using response surface methodology; the bioactivity properties were also investigated. The effects of the ethanol concentration, solute/solvent ratio, and temperature in relation to the phenolic composition and antioxidant activity were evaluated. The quantification and identification of the individual phenolic compounds (using high-performance liquid chromatography) and their bioactivity were evaluated. The optimized extraction conditions, which detected gallic acid, catechin, epicatechin, quercetin, and kaempferol, were obtained using 60% ethanol at a ratio of 1:38 (w/v) and a temperature of 80 °C. The extract showed high levels of phenolic classes and antioxidant activity. The extract also showed an inhibitory activity for pathogenic (approximately 80%, 10,000 µg/mL) and lactic acid (27.9%, 15,000 µg/mL) bacteria strains. The α-glucosidase inhibitory activity was approximately ten times greater than acarbose, demonstrating its high antiglycemic potential. No antioxidant and anti-inflammatory cellular activity were determined; however, a high cytotoxicity for non-tumor cells and the antiproliferative activity against the tumor cells were observed. Overall, the phenolic extract showed promising action in relation to the fight against the diseases related to oxidative stress and, hopefully, the application of the safe concentrations of the extract, based on bioavailability assays, can be verified.
Predicting the Porosity in Selective Laser Melting Parts Using Hybrid Regression Convolutional Neural Network
Authors: Alamri Nawaf Mohammad H. , Packianather Michael , Bigot Samuel
Published: December 2022

Assessing the porosity in Selective Laser Melting (SLM) parts is a challenging issue, and the drawback of using the existing gray value analysis method to assess the porosity is the difficulty and subjectivity in selecting a uniform grayscale threshold to convert a single slice to binary image to highlight the porosity. This paper proposes a new approach based on the use of a Regression Convolutional Neural Network (RCNN) algorithm to predict the percent of porosity in CT scans of finished SLM parts, without the need for subjective difficult thresholding determination to convert a single slice to a binary image. In order to test the algorithm, as the training of the RCNN would require a large amount of experimental data, this paper proposed a new efficient approach of creating artificial porosity images mimicking the real CT scan slices of the finished SLM part with a similarity index of 0.9976. Applying RCNN improved porosity prediction accuracy from 68.60% for image binarization method to 75.50% using the RCNN. The algorithm was then further developed by optimizing its parameters using Bees Algorithm (BA), which is known to mimic the behavior of honeybees, and the hybrid Bees Regression Convolutional Neural Network (BA-RCNN) produced better prediction accuracy with a value of 85.33%.
LUMDE: Light-Weight Unsupervised Monocular Depth Estimation via Knowledge Distillation
Authors: Hu Wenze , Dong Xue , Liu Ning , Chen Yuanfeng
Published: December 2022

The use of the unsupervised monocular depth estimation network approach has seen rapid progress in recent years, as it avoids the use of ground truth data, and also because monocular cameras are readily available in most autonomous devices. Although some effective monocular depth estimation networks have been reported previously, such as Monodepth2 and SC-SfMLearner, most of these approaches are still computationally expensive for lightweight devices. Therefore, in this paper, we introduced a knowledge-distillation-based approach named LUMDE, to deal with the pixel-by-pixel unsupervised monocular depth estimation task. Specifically, we use a teacher network and lightweight student network to distill the depth information, and further, integrate a pose network into the student module to improve the depth performance. Moreover, referring to the idea of the Generative Adversarial Network (GAN), the outputs of the student network and teacher network are taken as fake and real samples, respectively, and Transformer is introduced as the discriminator of GAN to further improve the depth prediction results. The proposed LUMDE method achieves state-of-the-art (SOTA) results in the knowledge distillation of unsupervised depth estimation and also outperforms the results of some dense networks. The proposed LUMDE model only loses 2.6% on δ1 accuracy on the NYUD-V2 dataset compared with the teacher network but reduces the computational complexity by 95.2%.
Trends of Changes in Minimum Lake Water Temperature in Poland
Authors: Ptak Mariusz , Olowoyeye Temidayo , Sojka Mariusz
Published: December 2022

Water temperature in lakes is their basic property that determines many processes. Changes in average values are thoroughly investigated using a long-term approach. Knowledge of extreme situations such as temperature minimums is still insufficient. This paper analyses changes in the minimum temperature in 10 lakes in Poland in the period 1972–2021. The obtained results show variability over the course of the parameter, both at the annual and monthly scale. In the first case, half of the analysed set showed statistically significant increasing trends (on average 0.10 °C per decade). In the latter case, the greatest changes occurred in the months of the warm half-year (on average 0.57 °C per decade). The reported situation is caused by the individual conditions of particular lakes, i.e., their location, morphometric parameters, or the dynamics of the occurrence of ice phenomena. A successive increase in the minimum temperature in lakes has its consequences for biotic and abiotic processes. Exceeding specific thresholds results in the evident transformation of these ecosystems.
Investigation of a Calibration Method of Coriolis Mass Flowmeters by Density- and Pressure-Matching Approaches for Hydrogen Refueling Stations
Authors: Kang Woong , Shin Jinwoo , Yoon Byungro , Kil Sunghee , Yim Sangsik , Han Wonguk , Baek Unbong
Published: December 2022

Hydrogen fuel cell electric vehicles are emerging as a means of transportation using renewable and carbon-free energy due to global warming and air pollution. Hydrogen fuel cell electric vehicles are typically refueled at a wide range of temperatures (−40 °C to 85 °C) in hydrogen refueling stations in accordance with globally accepted standards. Currently, there is no traceable method by which to verify and calibrate the Coriolis mass flowmeters used at hydrogen refueling stations, except for a water calibration process as a conventional method for mass flowrate calibration. To verify the hydrogen flow metering to a suitable level of accuracy under the challenging condition of high pressures and a wide range of temperatures, necessary methodologies and calibration facilities are developed in the present study. A flow measurement characteristic test of the hydrogen mass flowmeter under identical density conditions of the refueled hydrogen was conducted using the high-pressure gas flow standard system of the Korea Research Institute of Standards and Science to assess the effects on the medium and pressure of the mass flowmeter in a density-matching approach. To investigate the pressure dependence of the mass flowmeter at a hydrogen refueling station, a high-pressure water flow test was conducted in the pressure range of 2 bar to 700 bar, which is a pressure-matching approach. Finally, the KRISS Hydrogen Field Test Standard based on the gravimetric principle was developed to verify the measurement accuracy of the mass flowmeter to be used at hydrogen refueling stations for the first time in Korea.
Artificial Intelligence Algorithm-Based Arrangement Optimization of Structural Isolation Bearings
Authors: Zou Zhongliang , Yan Qiwu
Published: December 2022

The determination of an isolation-bearing scheme usually depends on experience, and needs numerous iterative calculations, especially when considering many factors such as total cost of the scheme, various design indicators, eccentricity of stiffness center of isolation bearings and the center of gravity of superstructure, and so on. Moreover, during the usual optimization process, the isolation scheme is often limited in several kinds of sizes and fixed predetermined distribution of types of isolation bearings based on experience or trial calculations due to computational efficiency, which would make it incapable of exploring other possible schemes. In this paper, artificial intelligence technology is applied to optimize the layout of isolation bearings. Types of isolation bearings are predicted through a Convolutional Neural Network, and sizes of isolation bearings are optimized by Hunter–prey optimization algorithm to improve computational efficiency and optimal arrangements of bearings. To simplify the optimization process, an optimization objective function considering a seismic decrease coefficient, story drift ratio and total cost of isolation bearings is proposed. In this function, weight coefficients reflect significance of various factors during the optimization process. In order to investigate influence of different combinations of weight coefficients on the optimal layout, 12 groups of combinations of weight coefficients are designed and analyzed. The results show that the optimal layout method of isolation bearings based on the artificial intelligence algorithm has good convergence efficiency of optimization and makes it possible to search more practical isolation scheme with good performance. When focusing on total cost of bearings, the ideal weight coefficient of the total cost would be larger than 0.4. While the structural performance factors are mainly considered, the weight coefficient of the maximum story drift ratio or seismic decrease coefficient should be larger than 0.2. For factors that designers pay more attention to, the corresponding weight coefficient should be larger than others.
Deep Learning Algorithms to Predict Output Electrical Power of an Industrial Steam Turbine
Authors: Fakir Kossai , Ennawaoui Chouaib , El Mouden Mahmoud
Published: December 2022

Among the levers carried in the era of Industry 4.0, there is that of using Artificial Intelligence models to serve the energy interests of industrial companies. The aim of this paper is to estimate the active electrical power generated by industrial units that self-produce electricity. To do this, we conduct a case study of the historical data of the variables influencing this parameter to support the construction of three analytical models three analytical models based on Deep Learning algorithms, which are Long Short-Term Memory (LSTM), Convolutional Neural Network (CNN), as well as the hybrid CNN algorithm coupled with LSTM (CNN-LSTM). Subsequently, and thanks to the evaluation of the created models through three mathematical metrics which are Root Mean Square Error (RMSE), Mean Square Error (MSE), and the variance score (R-squared), we were able to make a comparative study between these models. According to the results of this comparison, we attested that the hybrid model is the one that gives the best prediction results, with the following findings: the variance score was about 98.29%, the value of RMSE was exactly 0.1199 MW, and for MSE the error was equal to 0.0143 MW. The obtained results confirm the reliability of the hybrid model, which can help industrial managers save energy by acting upstream of the process parameters influencing the target variable and avoiding substantial energy bills.
Field and Wind Tunnel Experiments of Wind Field Simulation in the Neutral Atmospheric Boundary Layer
Authors: Xie Dong , Xiao Peilin , Cai Ninghua , Sang Lixin , Dou Xiumin , Wang Hanqing
Published: December 2022

To investigate the pollutant dispersion of a nuclear power plant, a field tracing experiment was carried out in neutral stratification weather with the main wind direction SSW. On this basis, a wind speed profile and turbulence intensity profile consistent with the site were created in the wind tunnel. Meanwhile, how to generate a wind field of neutral stratification in a wind tunnel was studied in detail. Finally, a 1:1000 nuclear power area model was made to conduct tracing experiments in the wind tunnel. The results show that when the horizontal and vertical distances of the spire are 300 mm and 500 mm, and the horizontal and vertical distances of the rough element are 250 mm and 500 mm. A wind speed profile with a wind profile index of 0.321 was generated in the wind tunnel (0.334 in the field test), and the wind tunnel tracer experiment had the same diffusion trend as the field, which verified the accuracy of the flow field.
Evolution of Ozone above Togo during the 1979–2020 Period
Authors: Ayassou Koffi , Pazmiño Andrea , Sabi Kokou , Bazureau Ariane , Godin-Beekmann Sophie
Published: December 2022

The objective of this paper is to estimate the trend of the Total Ozone Column (TOC) over Togo. A Multi-Sensor Reanalysis-2 (MSR-2) of the TOC over the entire territory of Togo was used. A Multiple Linear Regression (MLR) method has been applied to retrieve the interannual contributions of different forcings and the long-term variability. It was found that the Annual Oscillation (AnO), the Quasi Biennial Oscillation at 30 mb (QBO30), the Solar Flux (SF), and the El Niño–Southern Oscillation (ENSO) has a statistically significant influence on the interannual variability of the TOC. The strongest contribution (22 ± 1.4 DU) is allocated to the AnO while the weakest (<1 DU) is attributed to the Semi-Annual Oscillations (SAnO). Before the peak year of the Equivalent Effective Stratospheric Chlorine (EESC) in the tropics in 1997, the trend is negative (−0.3% ± 0.9% per decade) and is not statistically significant. After the peak year, a statistically significant positive trend is observed. The trend of the TOC is 0.6% ± 0.2% per decade. The monthly TOC trend over Togo is positive and statistically significant during the rainy season (particularly during the monsoon period) except in April, unlike during the harmattan period (DJF), where the trend is not significant.