bluuebunny/crossref_metadata_2025 huggingface dataset:
Almost Periodic Solutions for a Second-Order Nonlinear Equation with Mixed Delays
Authors: Xu Mei , Du Bo
Published: August 2022

This paper is devoted to studying a second-order nonlinear equation with mixed delays. Some sufficient conditions for the existence and exponential stability of the almost periodic solutions are established. The results of this paper extend the existing ones.
Study on Multifactor Control Experiment and Design of Quality Detection System for Yuba Skin Production
Authors: Shen Yinjie , Tao Yanhu , Tang Qiansheng , Xu Liangyuan
Published: August 2022

In view of the low control precision, low degree of intelligence, low utilization rate of soybean milk, and poor conjunctiva quality in current Yuba skin production technology, a system of multifactor control and intelligent quality detection for Yuba skin was studied and designed in this paper. The system uses LabVIEW as the upper computer and the single chip microcomputer as the lower computer. Uses programming electronic control technology to set process parameters in advance, precisely control each factor to achieve adaptive control of wind speed, concentration, liquid level, and temperature, the control error of each factor is within 1%, and the quality of Yuba skin was detected by image processing technology. The application of the system greatly improves the production efficiency and intellectualization of the production line and reduces the damage degree of Yuba skin. An orthogonal test and response surface optimization were carried out for the process parameters. The test results show that the accuracy of the test results using radial basis kernel function (RBF) can reach 92.06% when the characteristic combination mode is all the characteristics, and the optimal yield will be 48.57% and the optimal quality score is 9.20 when the export angle is 36.75°, the export diameter is 9.90 mm, the export wind speed is 1.22 m/s, the slurry concentration is 7.66%, the slurry temperature is 83.26°C, and the liquid level is 30.52 mm. Comparison between the results from the regression model validation test and those from the response surface methodology is made. The relative errors of yield and quality were 0.14% and 0.87%, which indicates that the response surface methodology can effectively optimize the process parameters of Yuba skin.
Application of Knowledge Model in Dance Teaching Based on Wearable Device Based on Deep Learning
Authors: Zhang Yan
Published: August 2022

With the great changes in the social, economic, and cultural background, the traditional education model can no longer meet the current goal of cultivating dance talents. The application of wearable devices based on deep learning helps to improve students’ understanding and application of dance movements. Through extensive data analysis, experimental research, and kinesthetic theory, it is found that trainers based on deep neural networks can effectively improve students’ overall learning performance. At the same time, the application of emotion-intelligence teaching mode theory in dance experiments and the conclusions drawn from the experimental research fully demonstrate the teaching advantages of applying deep learning wearable devices to dance emotion-intelligence teaching mode. In order to explore the application of wearable devices based on deep learning in dance teaching, this paper discusses the improvement of deep learning through the elaboration of parameter smoothing initialization, convolutional pooling layer, optimal smoothing filter, and dynamic pruning method, and then a wearable device is designed. A device can recognize dance movements to verify the application of deep learning-based wearables in dance teaching in emotional mode.
English Syntactic Analysis and Word Sense Disambiguation Strategy of Neutral Set from the Perspective of Natural Language Processing
Authors: Liang Chaohui , Shang Jiling
Published: August 2022

In order to improve the effect of English semantic analysis, under the support of natural language processing, this paper analyzes English syntactic analysis and the word sense strategy of the neutral set and solves the parameters through data training, so as to solve the probability distribution of the maximum entropy model of each order. Moreover, by comparing the prediction probability of the model to the judgment mode with the experimental data, it is found that the first-order maximum entropy model (independent model) is quite different from the data. Therefore, when judging data in English semantics, we cannot only consider the influence of second-order correlations but should also consider higher-order correlations. The research results of the simulation experiment show that the English syntactic analysis and the word sense disambiguation strategy of the neutral set proposed in this paper from the perspective of natural language processing are very effective.
An Enhanced Gated Recurrent Unit-Based Adaptive Fault Diagnosis of Rotating Machinery
Authors: Li Zhen , Riaz Saleem , Waqas Muhammad , Batool Munira
Published: August 2022

As the most basic component of rotating machinery, rolling bearing frequently works in harsh environments and complex working conditions, and its health status affects seriously the working efficiency. The health statuses of rolling bearing can not only reduce equipment maintenance costs but also contribute to reducing major accidents. Based on this, an adaptive diagnosis method that combines deep gated recurrent unit (DGRU) with wavelet packet decomposition (WPD) and extreme learning machine (ELM) is proposed for rolling bearing. Firstly, WPD is utilized to eliminate the noise of data. Secondly, DGRU is designed to extract the representative features of denoised data. Finally, ELM is utilized to output the diagnosis results. Massive results prove that the superiority and robustness of our approach outperform existing popular methods. Additionally, the proposed method can also achieve powerful antinoise ability.
Modeling and Simulation of Emergency Resource Allocation Process Based on Generalized Stochastic Petri Net
Authors: Zhang Bin , Wei Zhanguo
Published: August 2022

The outbreak of emergencies usually triggers the phenomenon of a lack of emergency resources, and the lack of resources may lead to untimely rescue affecting the social life order. How to guarantee a smooth and efficient emergency resource allocation process and improve the efficiency of emergency relief disposal is the key to ensuring the successful completion of disaster relief tasks. To this end, this paper focuses on the emergency resource allocation process and considers the recycling of emergency resources after disaster relief with the background of emergencies. An emergency resource allocation process model is constructed based on the generalized stochastic Petri net, and the activity, reachability, boundedness, and security of the model are analyzed. The homogeneous Markov chain is utilized for simulation, and the performance analysis is carried out by calculating the steady-state probability and transition utilization rate of each state using examples. Simulation results show that the database and the recovery process should be the key steps to optimizing the emergency resource allocation process. Therefore, improving the effectiveness of these critical links’ emergency disposal will further improve the effectiveness of emergency resource allocation.
Construction of Higher Education Management and Student Achievement Evaluation Mechanism Based on Apriori Algorithm
Authors: Liu Dongdong
Published: August 2022

The Apriori algorithm and DM technology are introduced, examined, and a relationship between bettering teachers’ classroom teaching quality, methods, and means is discussed. An evaluation system for student achievement in higher education is proposed and built on the basis of the Apriori algorithm. The Apriori algorithm is also improved in order to further avoid blind search during mining and increase the effectiveness of frequent itemsets. This paper avoids repeatedly scanning the database and instead reads the entire database into a two-dimensional array, which increases program performance. The algorithm is used to extract useful data from the database using data association mining in the higher education management system. According to the experimental findings, the improved Apriori algorithm’s accuracy can reach 94.81%, which is 10.31% higher than the accuracy of the original Apriori algorithm. The outcomes demonstrate the applicability and reliability of the algorithm model developed in this paper. For managers in teaching and management, it can be a useful reference.
Monitoring of an Electromechanical Prototype Material for Environmental Parameters Using IoT
Authors: Siva Varma P. Bharat , Phani Varma Kothapalli , Anjani Kranthi V. , Rudraraju Anusha , Nandakishore Nalla
Published: August 2022

The Internet of Things (IoT) is a phenomenon where everything is connected to everything, where the development of sensors and microprocessors helped in the rise of embedded technologies, such as Wi-Fi and Bluetooth, and the evolution of bandwidth available on the Internet. This phenomenon will continue unabated due to sensor technology, programmable chips, and embedded technologies. In recent years, the Internet of Things (IoT) has become one of the most prominent technology niches. IoT is the network of interconnected devices or “things” that exchange information or send data with each other over the Internet. The article describes a computer prototype for monitoring and controlling the environmental parameters of a communication equipment room. A technological tool, such as the one obtained, can be implemented in many applications, such as weather stations, food chains, smart home systems, measuring the heart rate of humans, and fruit dehydrators. The article’s research was focused on an IoT electronic device and a web platform. A major feature of this electronic device is that its Internet connectivity is achieved using the TCP/IP protocol, an integrated feature of the Shield Ethernet board stacked on top of the Arduino mega board.
Determinants of Pregnancy-Related Anxiety among Women Attending Antenatal Checkup at Public Health Institutions in Debre Markos Town, Ethiopia
Authors: Abegaz Marta Yimam , Muche Haymanot Alem , Aynalem Getie Lake
Published: August 2022

Background. Pregnancy-related anxiety has been associated with many pregnancy adverse outcomes including preterm birth, low birth weight, postpartum depression, and resulting in long-term sequels on the child’s emotional, cognitive, and behavioral development. This study is aimed at assessing the magnitude of pregnancy-related anxiety and associated factors among pregnant women attending antenatal checkup at Debre Markos town public health institutions, Northwest Ethiopia. Methods. An institution-based cross-sectional study was conducted among 423 pregnant women at Debre Markos town, Northwest Ethiopia, from February 1st to March 30th, 2021. A systematic random sampling technique was used to select the study participants. Data were collected sing a structured, pretested, and interviewer-administered questionnaire. The collected data were entered with Epi-data version 4.6 and then exported to SPSS version 23. Both bivariable and multivariable logistic regression analyses were undertaken to identify significantly associated variables with pregnancy-related anxiety. The adjusted odds ratio (AOR) with its 95% confidence interval (CI) at a

p

value of ≤0.05 was used to claim statistical association. Result. In this study, a total of 408 pregnant women participated, giving a 96.4% response rate. The prevalence of pregnancy-related anxiety was found to be 43.9% (95% CI: 39.5, 49.2). Having no formal education (

AOR
=
3.37

; 95% CI: 1.32, 8.58), primigravida (

AOR
=
1.94

; 95% CI: 1.17, 3.24), intimate partner violence (

AOR
=
2.88

; 95% CI: 1.47, 5.64), and poor social support (

AOR
=
2.05

; 95% CI: 1.18, 3.56) was significantly associated with pregnancy-related anxiety. Conclusion. In this study, the prevalence of pregnancy-related anxiety was found to be high when compared to other study findings. The regional educational department should give emphasis for gender pedagogies which pay attention to the specific learning needs of girls. In addition, interventions on violence against women and social support for the women may reduce the problem.
Surface Flaw Detection of Plug Valve Material Using Infrared Thermography and Weighted Local Variation Pixel-Based Fuzzy Clustering Technique
Authors: Jacintha V. , Karthikeyan S. , Sivaprakasam P.
Published: August 2022

This study focuses on the identification and categorization of plug valve defects. We utilize a thermal fluke camera to obtain the plug valve thermal images. The thermal camera utilizes passive infrared thermography towards the identification of plug valve defects such as cracks, porosity, and internal defects. These flaws depict variation in surface temperature induced by heat flux. Infrared thermography is capable of identification of surface flaws such as cracks and subsurface flaws such as porosity. Its flaw identification range is effective only up to a certain depth in the metal. The heat flux variations are clearly visible for surface cracks and subsurface porosity. However, the heat flux shows no fluctuations for internal defects. Hence, to identify the internal defects in the metal, we opt for a combination of passive infrared thermography and dye penetrating test. In the dye penetrating test, a thinned paint is applied over the metal surface that aids in the identification of cracks, porosity, and internal defects as well. The PIT-DPT (passive infrared thermography-dye penetrating test) works in combination with weighted local variation pixel-based fuzzy clustering (WLVPBFC) to measure the depth of the defects. The defects were measured against parametric quantities such as F-value, precision, recall, accuracy, Jaccard index, TP, FP, TN, FN, FP rate, TP rate, and MCC. These parameters depict variations with regard to surface texture and extent of defect level. The PIT-DPT and WLVPBFC techniques identify metal flaws with 87.88% efficiency when evaluated against other existing algorithms.
A Novel Feature Selection Method for Classification of Medical Data Using Filters, Wrappers, and Embedded Approaches
Authors: Bashir Saba , Khattak Irfan Ullah , Khan Aihab , Khan Farhan Hassan , Gani Abdullah , Shiraz Muhammad
Published: August 2022

Feature selection is the process of identifying the most relevant features from the given data having a large feature space. Microarray datasets are comprised of high‐quality features and very few samples of data. Feature selection is performed on such datasets to identify the optimal feature subset. The major goal of feature selection is to improve the accuracy by identifying a minimal feature subset. For this purpose, the proposed research focused on analyzing and identifying effective feature selection algorithms. A novel framework is proposed which utilizes different feature selection methods from filters, wrappers, and embedded algorithms. Furthermore, classification is then performed on selected features to classify the data using a support vector machine (SVM) classifier. Two publically available benchmark datasets are used, i.e., the Microarray dataset and the Cleveland Heart Disease dataset, for experimentation and analysis, and they are archived from the UCI data repository. The performance of SVM is analyzed using accuracy, sensitivity, specificity, and f‐measure. The accuracy of 94.45% and 91% is achieved on each dataset, respectively.
A Case of Fungemia Caused by Postoperative Chronic Lumbar Intervertebral Disc Infection
Authors: Zheng Rui , Jin Taicheng , Tao Rui , Xu Ning
Published: August 2022

Postoperative surgical site infection is one of the serious postoperative complications of spine surgery, especially fungal infections. Late-stage surgical site fungal infections often lack typical clinical symptoms and have a variable clinical presentation. In this case, the patient was a senior patient with usually only tolerable pain and discomfort, which was detected 2 years after the first surgery. Such cases are even rarer for fungal bloodstream infections caused by delayed postoperative chronic fungal osteomyelitis and deserve further study for early identification and intervention to minimize harm.
Dynamic Budget Management of Rural Public Affairs Based on Internet of Things Technology
Authors: Pei Xue
Published: August 2022

In order to improve the budget management of rural public affairs, this paper combines the Internet of things technology to construct an information processing system that can be used for dynamic budget management of rural public affairs and optimizes the internal resource processing process of the system. In order to overcome the constraints and differences of resource QoS attributes and ensure that the QoS attribute values of candidate resources are within the user’s expectations, this paper introduces penalty factors and grey incidence matrix to analyze the gap between resource QoS attribute values, and calculates the similarity between matching resources and user-requested resources. In addition, this paper combines the dynamic budget requirements of rural public affairs to construct system function modules. Finally, this paper evaluates the Internet of Things data transmission and rural public affairs dynamic budget management effects of the system constructed in this paper, and conducts simulation research based on the data collected by the network. From the experimental research, we can see that the dynamic budget management system of public affairs based on the Internet of things technology constructed in this paper has good results.
Technical Research on Optimization of Irrigation Canal System Considering Genetic Algorithm
Authors: Wang Yijia
Published: August 2022

In order to solve the lack of optimization and comparison of the previous schemes in the irrigation and water conservancy project reconstruction, the engineering design and planning are difficult to reach the best state, resulting in water resource waste and other problems. In this paper, genetic algorithm optimization technology of the irrigation canal system is studied, in-depth learning technology of image processing is elaborated, the rectangular optimization model is established, and the optimal nonlinear design of trapezoidal and U-shaped sections of irrigation channel is verified by engineering examples. According to the geographical location, water source, irrigation area, irrigation area, and designer’s experience, two possible irrigation scheme layouts have been determined, and the trapezoidal section has been optimized. The results show that the value of the objective function decreases rapidly with the increase of iteration time. Scheme 1 has stabilized for about 19 generations. Scheme 2 tends to be stable for about 25 generations. The optimization results of the U-shaped section show that scheme 1 is stable for about 43 generations, while scheme 2 tends to be stable for about 60 generations. By comparing the optimal schemes of the trapezoidal section and the U-section, it can be found that the water supply cost of the U-section is low. Therefore, under the condition of layout scheme 2, the U-shaped section is the best scheme. The calculation shows that under the same conditions, the trapezoidal section area is about 45% larger than the U-shaped section area. Although the trapezoidal section is adopted in the original project, the U-shaped section is recommended when construction conditions permit. The optimization method can quickly determine the overall optimization scheme of irrigation channels. The water supply cost depends on the final optimized objective function value, which is used as the reference basis for formulating the water supply price. The optimal design scheme should not only meet the provisions of engineering practice but also meet the requirements of the lowest water supply cost.
Ethnobotanical Study and Conservation Status of Plants Used by the Tigwahanon-Manobo in Mt. Malimumu, San Fernando, Bukidnon, Philippines
Authors:   Center for Biodiversity Research and Extension in Mindanao (CEBREM), Central Mindanao University, Musuan, Bukidnon 8714, Philippines., Dapar Mark ,   Microtechnique and Systematics Laboratory, Natural Science Research Center (NSRC), Central Mindanao University, Musuan, Bukidnon 8714, Philippines,   Department of Biology, College of Arts and Sciences, Central Mindanao University, Musuan, Bukidnon 8714, Philippines., Victor Amoroso ,   Center for Biodiversity Research and Extension in Mindanao (CEBREM), Central Mindanao University, Musuan, Bukidnon 8714, Philippines,   Department of Biology, College of Arts and Sciences, Central Mindanao University, Musuan, Bukidnon 8714, Philippines.
Published: August 2022

Central Mindanao, Philippines, is a center of the cultural wealth of knowledge and botanical resources in the southern archipelago. However, traditional plant resources remain unexplored, and most of the tribal communities remain undocumented. Manobo tribe is one of the most populated and diverse tribal communities in the country, including the secluded Tigwahanon-Manobo community in Mt. Malimumu, San Fernando, Bukidnon, Philippines. Hence, this study provides ethnobotanical information and conservation status of plants along a 1-km transect walk in Mt. Malimumu used by the Tigwahanon-Manobo. A guided field walk with the tribal chieftains and tribal healer documented a total of 23 species in 22 genera belonging to 20 families, of which four species, namely Dillenia philippinensis Rolfe, Nepenthes cornuta Marwinski, Coritico, Wistuba, Micheler, Gronem., Gieray & V.B.Amoroso, Nepenthes truncata Macfarl., and Pandanus mindanaensis Martelli, are Philippine endemics. Three families, namely Nepenthaceae, Melastomataceae, and Rubiaceae, are the most represented with two species each. Based on the combined international (IUCN 2021) and national (DENR DAO 2017-11) listing of conservation status, one species was assessed as Critically Endangered (Aquilaria malaccensis Lam.) and another one as Endangered (N. truncata). Two species were assessed as Vulnerable (Agathis philippinensis Warb. and N. cornuta) and one species as Near Threatened (D. philippinensis). Six species were identified as Least Concern while the rest of the species were not yet evaluated. This participatory research provides the first ethnobotanical study and conservation status of traditional plants used by Tigwahanon-Manobo for food and medicine, as well as economic and ecological uses needing conservation and protection of their natural resources. Keywords: Conservation, Ethnobotany, Food plants, Indigenous, Medicinal plants, Mindanao
Prevalence of Antibiotic Resistance Bacteria in Aquaculture Sources in Johor, Malaysia Prevalence of Antibiotic Resistance
Authors:   Department of Biosciences, Faculty of Science, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia, Yern Kam , Zain Nor ,   Department of BiosciencesFaculty of ScienceBlok T02Universiti Teknologi Malaysia81310 Skudai, JohorOffice: +607-5557524, Jaafar Mohd ,   Bahagian Penyelidikan Akuakultur Air Payau, FRI Gelang Patah, 81550 Johor Bahru, Johor, Malaysia, Sani Mohd ,   Department of Biosciences, Faculty of Science, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia, Suhaimin Mohd ,   School of Chemical Engineering, Faculty of Engineering, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia
Published: August 2022

The intensive use of antibiotics in aquaculture results in the proliferation of antibiotic. In this study, antibiotic resistant bacteria from six different aquaculture sources (pond of Fisheries Research Institute (FRI), and rivers of Kukup, Pulai, Pendas Laut, Sungai Melayu and Kong Kong) were isolated. These isolates were tested for antibiotic resistance against seven antibiotics via the disc diffusion method. Finally, phenotypic and genotypic identification via 16S rRNA sequencing and phylogenetic analysis were carried out. The results show that 58 out of 118 bacterial isolates are resistant to multiple antibiotics. The highest isolate resistance was observed towards rifampicin (89.66%), followed by ampicillin (79.31%) and sulfafurazole (67.24%). The isolates with multiple antibiotic resistant (MAR) index values with more than 20% were subjected to 16S rRNA gene sequencing. The majority of the bacterial strains exhibit multiple antibiotic resistance, indicating that they were isolated from highly contaminated sources based on the tested water qualities profiles, which showed the high level of turbidity and total dissolved solid (TDS) in most sampling sites with the high number of MAR bacteria obtained.Keywords: Antibiotic resistance, Multiple antibiotic resistance, Aquaculture sources,MAR index value, 16S rRNA gene sequencing
TİCARET POLİTİKASI BELİRSİZLİKLERİNİN ABD’NİN ÇİN KARŞISINDAKİ DIŞ TİCARET DENGESİNE ETKİLERİ: YAPISAL KIRILMALI BİR ANALİZ
Authors: ÖZÇELİK Oğuzhan
Published: August 2022

Bu çalışmada; ticaret politikası belirsizliklerinin (TPU) 2000:M01-20212:M03 döneminde ABD-Çin dış ticaret dengesine etkileri analiz edilmiş ve bu dengenin sürdürülebilir olduğu bulunmuştur. Reel kurdaki artışlar ABD’nin Çin’e ihracatını ve dış ticaret dengesinin sürdürülebilirliğini azaltmıştır. ABD ve Çin’de TPU’nun artmasının ABD’nin Çin’e ihracatı ve dış ticaret dengesi üzerinde anlamlı bir etkisinin olmadığı belirlenmiştir. Toda-Yamamoto (1995) testinde reel kurdan ABD’nin dış ticaret dengesine doğru belirlenen nedensellik; ABD’nin Çin’e ulusal parasının değerini baskılamayı bırakması yönündeki çabalarının haklılığına işaret etmektedir. ABD ve Çin’deki TPU’dan ABD’nin dış ticaret dengesine doğru nedensellik ilişkisi olmaması; ABD’nin uyguladığı agresif dış ticaret politikalarının bir işe yaramadığını göstermektedir. Reel kur ve ABD’nin TPU’sundan ABD’nin Çin’den ithalatına doğru belirlenen nedensellik ilişkileri; ABD’nin uyguladığı heteredoks dış ticaret politikaları ile ancak Çin’den yaptığı ithalatı etkileyebildiğini, Çin’e ihracatınınsa bu ülkenin iç dinamiklerce belirlendiğini göstermektedir. Reel kurdan Çin’in TPU’suna doğru doğru belirlenen nedensellik ilişkisi; Çin’deki TPU’nun önemli bir kaynağının, uygulanmakta olan kur politikaları olduğuna işaret etmektedir.
Two new species and a new record of Epidendrum (Orchidaceae) from the Carpish Montane Forest Regional Conservation Area, Peru
Authors: OCUPA-HORNA LUIS , JIMÉNEZ MARCO M. , DUARTE SALINAS JULIAN , SANTIAGO AYALA ELIZABETH , HÁGSATER ERIC
Published: August 2022

Two new species and one record of Epidendrum, found in the forests of the Carpish Montane Forest Regional Conservation Area, are described, illustrated and compared with morphologically similar species. Epidendrum churubambense is characterized by the roots present only at base of primary pseudobulbs, the narrower leaves, the narrowly lanceolate and the yellow-green flowers with sepals slightly tinged brown. Epidendrum unchogense is characterized by lanceolate leaves, flowers with longer sepals, trullate petals, usually more long, entire lip, narrowly ovate with acute apex. Epidendrum sanctae-rosae a previously known species from Colombia, is reported as new country record to the Peruvian flora.
Safety Assessment of the Interaction Between an Automated Vehicle and a Cyclist: A Controlled Field Test
Authors: Oskina Maria , Farah Haneen , Morsink Peter , Happee Riender , van Arem Bart
Published: August 2022

The operation of automated vehicles (AVs) on shared roads requires attention concerning their interactions with vulnerable road users (VRUs), such as cyclists. This study investigates the safety of cyclists when they interact with an AV and compares it with their interaction with a conventional vehicle. Overall, 29 cyclists participated in a controlled field experiment consisting of interaction scenarios in which a vehicle approached the cyclist from behind. Four interaction scenarios were included: manual and automated following and manual and automated overtaking of the cyclist. The vehicle operated in all scenarios in a manual mode for safety reasons. However, before each ride, participants received information about the vehicle’s operation mode (automated or manual). The following attributes were considered: overtaking speed, overtaking lateral distance, following distance, and roadside objects. The objective and the subjective risks were evaluated in each scenario. The objective risk was assessed using the probabilistic driving risk field, and the subjective risk was assessed based on the cyclists’ self-reported risk values, cycling behavior, and their trust in AVs. The results show that automated and manual following have similar objective and subjective risks, while automated overtaking has a higher level of objective and subjective risks than manual overtaking. The results also show that a longer interaction time leads to an increase in cycling speed and a decrease in the lateral distance of the cyclist to the curb. Thus, we conclude that automated following is a safer option for short traveling distances, while for longer traveling distances, manual overtaking is preferred. Additionally, a short lateral distance from the cyclist when overtaking increases the subjective and objective risks.
School Nursing Workforce Differences Between Urban and Non-Urban Areas: Implications for School Health Services and Equity
Authors: Ramos Mary M. , Sebastian Rachel , Shattuck Daniel , Acosta Susan , Zamarin Kim
Published: August 2022

The professional experiences of school nurses who work outside of urban areas are not often described. We used data from a 2019 statewide survey of school nurses to describe differences between the urban and non-urban (urban cluster and rural) school nurse workforce in New Mexico. Non-urban school nurses were twice as likely as urban nurses to provide clinical services to multiple school campuses ( P  < .001) and more likely to serve both elementary and secondary school settings ( P  = .002). They were less likely than urban school nurses to be bachelor's prepared, or to have received recent continuing education on diabetes ( P  < .001), reproductive health ( P = 0.02), LGBQ+ and transgender student health ( P  < .001, for each), and suicide risk assessment and screening ( P  = .012). Our findings underscore concerns about geographic differences in the school nursing workforce in terms of educational preparation and student access that could potentially limit the school nurse role in advancing child health equity.
Mineral stabilities in soils: how minerals can feed the world and mitigate climate change
Authors: Manning David A.C.
Published: August 2022

Mineral reactions in soils demonstrably take place on a human timescale. The weathering of silicate ‘rock-forming’ minerals releases nutrients that are essential for plant growth, including silica. This process consumes CO2, which is ultimately derived from the atmosphere, through enhanced rock weathering. From a human perspective, the weathering process has two beneficial functions – crop nutrition and climate mitigation – through the removal of atmospheric CO2. By considering these as a coupled process, the release of silica during weathering can be matched to what is taken from the soil by a crop (e.g. wheat). A simple analysis shows that the amount of silica that accumulates in wheat during a 4 month growing period is readily released by the weathering of pyroxene and plagioclase, minerals that commonly occur in basaltic igneous rocks. In contrast, the dissolution rate for quartz is so low that it cannot supply the silica taken up by the crop and is inert. Similarly, dissolution of clay minerals releases sufficient silica for plant uptake. Rapid weathering of silicate minerals within soils is evident from images of surfaces of grains exposed in soils for periods of 10–100 years. The evidence for silicate rock weathering as part of the soil system that sustains humanity is provided by the vegetation that we see around us.
Abdominal pain and fever in a patient with human immunodeficiency virus: a case report
Authors: Ackerman Max , Frost Arian , Stanford Kimberly
Published: August 2022

Background

Neutropenic enterocolitis (NE), or typhlitis, a condition typically associated with severe neutropenia in the setting of chemotherapy, is highly morbid (50–100%) and benefits from early diagnosis. It has been associated with neutropenia in the setting of human immunodeficiency virus (HIV) but has not been described in a patient with HIV who was not neutropenic on presentation. We present the case of a patient with HIV who was not neutropenic on presentation but found to have NE.

Case presentation

A 27-year-old male with a history of HIV on antiretroviral therapy and epilepsy presented with concern for breakthrough seizure. The patient revealed he was having non-bloody, non-bilious emesis and diarrhea for 3 days. Initial labs were white blood cell count 3.9 × 109/L, absolute neutrophil count (ANC) 3.14 × 109/L, CD4 count 290 cells/mm3, and undetectable viral load. A computed tomography (CT) scan of the abdomen/pelvis with contrast revealed wall thickening of the cecum and proximal ascending colon (Fig. 1), suggestive of NE. The patient was started on cefepime and metronidazole but switched to piperacillin/tazobactam after he became leukopenic/neutropenic.

Conclusions

Neutropenic enterocolitis, typically presenting with fever, abdominal pain, and hematochezia, can be difficult to identify, particularly in patients without a history of malignancy. However, it should be considered in patients with HIV presenting with these symptoms, even with a normal ANC and CD4 count above 200 cells/mm3. Prompt diagnosis can be made with CT, and early initiation of broad-spectrum antibiotics greatly reduces the risk of morbidity/mortality.
SMaSH: a scalable, general marker gene identification framework for single-cell RNA-sequencing
Authors: Nelson M. E. , Riva S. G. , Cvejic A.
Published: August 2022

Background

Single-cell RNA-sequencing is revolutionising the study of cellular and tissue-wide heterogeneity in a large number of biological scenarios, from highly tissue-specific studies of disease to human-wide cell atlases. A central task in single-cell RNA-sequencing analysis design is the calculation of cell type-specific genes in order to study the differential impact of different replicates (e.g. tumour vs. non-tumour environment) on the regulation of those genes and their associated networks. The crucial task is the efficient and reliable calculation of such cell type-specific ‘marker’ genes. These optimise the ability of the experiment to isolate highly-specific cell phenotypes of interest to the analyser. However, while methods exist that can calculate marker genes from single-cell RNA-sequencing, no such method places emphasise on specific cell phenotypes for downstream study in e.g. differential gene expression or other experimental protocols (spatial transcriptomics protocols for example). Here we present , a general computational framework for extracting key marker genes from single-cell RNA-sequencing data which reliably characterise highly-specific and niche populations of cells in numerous different biological data-sets.

Results

extracts robust and biologically well-motivated marker genes, which characterise a given single-cell RNA-sequencing data-set better than existing computational approaches for general marker gene calculation. We demonstrate the utility of through its substantial performance improvement over several existing methods in the field. Furthermore, we evaluate the markers on spatial transcriptomics data, demonstrating they identify highly localised compartments of the mouse cortex.

Conclusion

is a new methodology for calculating robust markers genes from large single-cell RNA-sequencing data-sets, and has implications for e.g. effective gene identification for probe design in downstream analyses spatial transcriptomics experiments. has been fully-integrated with the framework and provides a valuable bioinformatics tool for cell type characterisation and validation in every-growing data-sets spanning over 50 different cell types across hundreds of thousands of cells.
TMbed: transmembrane proteins predicted through language model embeddings
Authors: Bernhofer Michael , Rost Burkhard
Published: August 2022

Background

Despite the immense importance of transmembrane proteins (TMP) for molecular biology and medicine, experimental 3D structures for TMPs remain about 4–5 times underrepresented compared to non-TMPs. Today’s top methods such as AlphaFold2 accurately predict 3D structures for many TMPs, but annotating transmembrane regions remains a limiting step for proteome-wide predictions.

Results

Here, we present TMbed, a novel method inputting embeddings from protein Language Models (pLMs, here ProtT5), to predict for each residue one of four classes: transmembrane helix (TMH), transmembrane strand (TMB), signal peptide, or other. TMbed completes predictions for entire proteomes within hours on a single consumer-grade desktop machine at performance levels similar or better than methods, which are using evolutionary information from multiple sequence alignments (MSAs) of protein families. On the per-protein level, TMbed correctly identified 94 ± 8% of the beta barrel TMPs (53 of 57) and 98 ± 1% of the alpha helical TMPs (557 of 571) in a non-redundant data set, at false positive rates well below 1% (erred on 30 of 5654 non-membrane proteins). On the per-segment level, TMbed correctly placed, on average, 9 of 10 transmembrane segments within five residues of the experimental observation. Our method can handle sequences of up to 4200 residues on standard graphics cards used in desktop PCs (e.g., NVIDIA GeForce RTX 3060).

Conclusions

Based on embeddings from pLMs and two novel filters (Gaussian and Viterbi), TMbed predicts alpha helical and beta barrel TMPs at least as accurately as any other method but at lower false positive rates. Given the few false positives and its outstanding speed, TMbed might be ideal to sieve through millions of 3D structures soon to be predicted, e.g., by AlphaFold2.
Blockade of exosome generation by GW4869 inhibits the education of M2 macrophages in prostate cancer
Authors: Peng Yilin , Zhao Min , Hu Yinying , Guo Hongyan , Zhang Yanyan , Huang Yanqin , Zhao Lin , Chai Yong , Wang Zhigang
Published: August 2022

Background

Tumor-associated macrophages are considered to be a major contributor affecting the development of tumors. Recently, numerous studies have shown that tumor cells were able to educate their microenvironment by delivering a significant amount of exosomes, however, the mechanism that exosomes from PCa cells work in macrophage polarization remains obscure. Therefore, we sought to determine whether blockade of exosome generation by GW4869, an inhibitor of exosome biogenesis, would impede macrophages from differentiating into M2 cells.

Results

In this study, we first obtained exosomes from the supernatant media of PCa cells cultured with exosome-free serum using the Magcapture™ Exosome Isolation Kit PS, and then investigated their effects on macrophages. Our data confirmed that exosomes released by prostate cancer cells can induce macrophages to differentiate into M2 cells. Mechanistically speaking, exosomes exert their effects on macrophages through activating the AKT and STAT3 signaling pathways. Importantly, treatment with GW4869 significantly inhibited the release of exosomes from PCa cells, and further impaired M2 differentiation of macrophages and their pro-tumor activity. We also demonstrated that GW4869 was able to inhibit the education of M2 macrophages, and then inhibit the progression of prostate cancer in vivo.

Conclusions

In brief, our findings indicated that GW4869 impeded the PCa exosome-induced M2 differentiation of macrophages and the progression of prostate cancer, suggesting that GW4869 could play an important role in the treatment of prostate cancer metastasis as an inhibitor of tumor exosome secretion.
Integrated metabolomic and transcriptomic analyses of the parasitic plant Cuscuta japonica Choisy on host and non-host plants
Authors: Guo Chenglin , Qin Liuyan , Ma Yongling , Qin Jianlin
Published: August 2022

Background

Cuscuta japonica Choisy (Japanese dodder) is a parasitic weed that damages many plants and affects agricultural production. The haustorium of C. japonica plays a key role during parasitism in host plants; in contrast, some non-host plants effectively inhibit its formation. However, the metabolic differences between normal dodder in host plants and dodder inhibition in non-host plants are largely unknown. Here, we utilized an integrative analysis of transcriptomes and metabolomes to compare the differential regulatory mechanisms between C. japonica interacting with the host plant Ficus microcarpa and the non-host plant Mangifera indica.

Results

After parasitization for 24 h and 72 h, the differentially abundant metabolites between these two treatments were enriched in pathways associated with α-linolenic acid metabolism, linoleic acid metabolism, phenylpropanoid biosynthesis, and pyrimidine metabolism. At the transcriptome level, the flavor biosynthesis pathway was significantly enriched at 24 h, whereas the plant–pathogen interaction, arginine and proline metabolism, and MARK signaling-plant pathways were significantly enriched at 72 h, based on the differentially expressed genes between these two treatments. Subsequent temporal analyses identified multiple genes and metabolites that showed different trends in dodder interactions between the host and non-host plants. In particular, the phenylpropanoid biosynthesis pathway showed significant differential regulation between C. japonica in host and non-host plants.

Conclusions

These results provide insights into the metabolic mechanisms of dodder–host interactions, which will facilitate future plant protection from C. japonica parasitism.
Nutrition mediates the relationship between number of teeth and sarcopenia: a pathway analysis
Authors: Xia Xin , Xu Zhigang , Hu Fengjuan , Hou Lisha , Zhang Gongchang , Liu Xiaolei
Published: August 2022

Objectives

The relationship between the number of teeth and sarcopenia remains poorly investigated. Although nutrition plays an important role in maintaining bone and muscle health, the complex relationship between number of teeth and nutrition in the pathogenesis of sarcopenia remains to be elucidated.

Methods

A large multi-ethnic sample of 4149 participants aged over 50 years old from West China Health and Aging Trend (WCHAT) study was analyzed. We examined the associations between number of teeth with nutritional status and sarcopenia, and the mediating role of nutrition in the association between number of teeth and sarcopenia. Sarcopenia was defined according to the Asian Working Group for Sarcopenia 2019. We assessed nutrition using Mini Nutrition Assessment-Short Form (MNA-SF) scale. Direct relationships between number of teeth, nutrition and sarcopenia were assessed using multiple linear regression. Mediation models and structural equation model (SEM) pathway analysis were used to test the mediating role of nutrition in the relationship between number of teeth and sarcopenia.

Results

Of 4149 participants aged 50 years old or older, the prevalence of sarcopenia was 22.5, 9.0% for moderate sarcopenia, and 13.5% for severe sarcopenia, respectively. Regression analysis indicated a total association between number of teeth (β = − 0.327, 95% CI − 0.471 to − 0.237, p < 0.001) and sarcopenia. After adjusted MNA-SF scores, the association between number of teeth and sarcopenia was still significant (β = − 0.269, 95% CI − 0.364 to − 0.175, p < 0.001), indicating a partial mediation effect of nutrition. Mediation analysis verified nutrition partially mediate the associations between number of teeth and sarcopenia (indirect effect estimate = − 0.0272, bootstrap 95% CI − 0.0324 to − 0.0222; direct effect estimate = − 0.0899, bootstrap 95% CI − 0.1049 to − 0.0738). And this mediation effect was through impacting SMI (indirect effect estimate = − 0.0283, bootstrap 95% CI − 0.0336 to − 0.0232) and grip strength (indirect effect estimate = − 0.0067, bootstrap 95% CI − 0.0094 to − 0.0043). Structural equation model (SEM) framework pathway analysis confirmed the association between number of teeth, nutrition, and sarcopenia.

Conclusions

Our findings indicated that sarcopenia was associated with number of teeth and poorer nutritional status, with nutrition partially mediating the association between number of teeth and sarcopenia. Our findings supported early nutritional assessment and intervention in oral health to mitigate the risk of sarcopenia.
LAP3 contributes to IFN-γ-induced arginine depletion and malignant transformation of bovine mammary epithelial cells
Authors: Li Li , Li Fengyang , Hu Xiuhong , Wu Zengshuai , Ren Wenbo , Wang Tingting , Ji Zhengchao , Li Na , Gu Jingmin , Sun Changjiang , Feng Xin , Han Wenyu , Huang Jing , Lei Liancheng
Published: August 2022

Background

IFN-γ has been traditionally recognized as an inflammatory cytokine that involves in inflammation and autoimmune diseases. Previously we have shown that sustained IFN-γ induced malignant transformation of bovine mammary epithelial cells (BMECs) via arginine depletion. However, the molecular mechanism underlying this is still unknown.

Methods

In this study, the amino acids contents in BMECs were quantified by a targeted metabolomics method. The acquisition of differentially expressed genes was mined from RNA-seq dataset and analyzed bioinformatically. Quantitative reverse transcription polymerase chain reaction (qRT-PCR), enzyme-linked immunosorbent assay (ELISA), western blotting, and immunohistochemistry (IHC) assay were performed to detect gene mRNA and protein expression levels. CCK-8 and would healing assays were used to detect cell proliferation and migration abilities, respectively. Cell cycle phase alternations were analyzed by flow cytometry.

Results

The targeted metabolomics analysis specifically discovered IFN-γ induced arginine depletion through accelerating arginine catabolism and inhibiting arginine anabolism in BMECs. Transcriptome analysis identified leucine aminopeptidase 3 (LAP3), which was regulated by p38 and ERK MAPKs, to downregulate arginine level through interfering with argininosuccinate synthetase (ASS1) as IFN-γ stimulated. Moreover, LAP3 also contributed to IFN-γ-induced malignant transformation of BMECs by upregulation of HDAC2 (histone deacetylase 2) expression and promotion of cell cycle proteins cyclin A1 and D1 expressions. Arginine supplementation did not affect LAP3 and HDAC2 expressions, but slowed down cell cycle process of malignant BMECs. In clinical samples of patients with breast cancer, LAP3 was confirmed to be upregulated, while ASS1 was downregulated compared with healthy control.

Conclusions

These results demonstrated that LAP3 mediated IFN-γ-induced arginine depletion to malignant transformation of BMECs. Our findings provide a potential therapeutic target for breast cancer both in humans and dairy cows.