bluuebunny/crossref_metadata_2025 huggingface dataset:
Causes of admissions and in-hospital mortality among patients admitted to critical care units in primary and secondary hospitals in Vietnam in 2018: a multicentre retrospective study
Authors: Dat Vu Quoc , Linh Bui Thi Khanh , Kim Giang Bao
Published: June 2022

Objective

The goal of this study was to describe the burden of disease and in-hospital mortality among patients admitted to the critical care units (CCUs) in Vietnam.

Design

Retrospective study.

Setting

The whole 1-year data of admissions to CCUs were collected from 34 hospitals from January to December 2018.

Participants

A total of 44 013 episodes of admission to CCUs were analysed.

Primary outcome

We used International Classification of Diseases-11 codes to assess the primary diagnosis associated with admissions and in-hospitals mortality. Years of life lost (YLL) measure was further used to estimate the burden of disease.

Results

The 0–5 years and ≥70 years age groups accounted for 14.8% (6508/44 013) and 26.1% (11 480/44 013) of all admissions, respectively. The most common diagnoses were diseases of the respiratory system (27.8% or 12 255/44 013), followed by unclassified symptoms, signs or clinical findings (13% or 5712/44 013), and diseases of the circulatory system (12.2% or 5380/44 013). Among 28 311 patients with available outcome data, 1681 individuals (5.9%) died during the hospitalisation. The in-hospital mortality rate increased with age, from 2.8% (86/3105) in under 5 years old age group to 23.1% (297/1288) in over 90-year age group. Diseases of the respiratory system was the leading causes of death in term of number of deaths (21.8% or 367/1681 of all deaths). Diagnosis of sepsis was associated with the highest in-hospital mortality (36.8%). The overall YLL under the age of 75 were 1287 per 1000 patients.

Conclusions

CCUs in Vietnam faced wide differences in the burden of diseases. Sufficient infrastructure and adequate multidisciplinary training are essential to ensure the appropriate response to the current needs of population.
‘I can’t understand why others don’t screen more’: a qualitative study exploring why Australian general practitioners screen for primary aldosteronism
Authors: Nainani Abhir Krishan , Yang Jun , Peters Sanne , Russell Grant
Published: June 2022

Objective

We sought to understand the factors that influence a general practitioner’s (GP’s) experience of screening for primary aldosteronism (PA) in hypertensive patients.

Design

A qualitative study, framed by phenomenology, using semistructured interviews that were audiorecorded, transcribed verbatim, entered into NVivo V.12.0 for coding and analysed for emerging themes.

Setting

Melbourne, Australia.

Participants

Eligible GPs had received education on PA as part of a previous study. We recruited a purposive sample of 16 GPs (6 females, 10 males) who varied in practice location, clinical experience and the number of patients screened for PA.

Results

Although GPs had been educated about PA, they found it challenging to explain the condition to patients and were uncertain about how to screen patients who were already taking antihypertensive medications. Most viewed the screening process to be practical, inexpensive and, by and large, acceptable to their patients. However, they found it inconvenient to alter antihypertensive medications before screening to allow for easier interpretation of the aldosterone-renin ratio. They were also less enthused about screening patients whom they thought fitted a clinical picture of essential hypertension. Knowledge of the screening process, cost and convenience of performing the aldosterone–renin ratio, conceptualisation of risk related to PA, and a desire to improve clinical care were influencing factors that modified the GPs’ screening experience.

Conclusion

Our findings suggest that knowledge gaps, practical limitations of the aldosterone–renin ratio, and errors in diagnostic reasoning were challenges of routine PA screening. Most of these practical barriers could be addressed by relatively simple educational and practice modifications to increase PA screening rates and optimise detection for the most common cause of secondary hypertension in primary care.
6α-hydroxylated bile acids mediate TGR5 signalling to improve glucose metabolism upon dietary fiber supplementation in mice
Authors: Makki Kassem , Brolin Harald , Petersen Natalia , Henricsson Marcus , Christensen Dan Ploug , Khan Muhammad Tanweer , Wahlström Annika , Bergh Per-Olof , Tremaroli Valentina , Schoonjans Kristina , Marschall Hanns-Ulrich , Bäckhed Fredrik
Published: June 2022

Objective

Dietary fibres are essential for maintaining microbial diversity and the gut microbiota can modulate host physiology by metabolising the fibres. Here, we investigated whether the soluble dietary fibre oligofructose improves host metabolism by modulating bacterial transformation of secondary bile acids in mice fed western-style diet.

Design

To assess the impact of dietary fibre supplementation on bile acid transformation by gut bacteria, we fed conventional wild-type and TGR5 knockout mice western-style diet enriched or not with cellulose or oligofructose. In addition, we used germ-free mice and in vitro cultures to evaluate the activity of bacteria to transform bile acids in the caecal content of mice fed with western-style diet enriched with oligofructose. Finally, we treated wild-type and TGR5 knockout mice orally with hyodeoxycholic acid to assess its antidiabetic effects.

Results

We show that oligofructose sustains the production of 6α-hydroxylated bile acids from primary bile acids by gut bacteria when fed western-style diet. Mechanistically, we demonstrated that the effects of oligofructose on 6α-hydroxylated bile acids were microbiota dependent and specifically required functional TGR5 signalling to reduce body weight gain and improve glucose metabolism. Furthermore, we show that the 6α-hydroxylated bile acid hyodeoxycholic acid stimulates TGR5 signalling, in vitro and in vivo, and increases GLP-1R activity to improve host glucose metabolism.

Conclusion

Modulation of the gut microbiota with oligofructose enriches bacteria involved in 6α-hydroxylated bile acid production and leads to TGR5-GLP1R axis activation to improve body weight and metabolism under western-style diet feeding in mice.
Malignant lymphoma and occupational exposure to extremely low frequency magnetic fields and electrical shocks: a nested case-control study in a cohort of four Nordic countries
Authors: Jalilian Hamed , Guxens Mònica , Heikkinen Sanna , Pukkala Eero , Huss Anke , Eshagh Hossaini Seyed Kamal , Kjærheim Kristina , Vermeulen Roel
Published: June 2022

Background

Exposure to extremely low frequency magnetic fields (ELF-MFs) and electric shocks is a common occupational risk factor in many workplaces. Recent investigations have highlighted a possible association between such exposures and lymphoma risk. This study was carried out to further explore the association between occupational exposure to ELF-MFs and electric shocks and risk of lymphoma in a large Nordic census-based cohort.

Methods

We included cases of non-Hodgkin's lymphoma (NHL, n=68 978), chronic lymphocytic leukaemia (CLL, n=20 615) and multiple myeloma (MM, n=35 467) diagnosed between 1961 and 2005 in Finland, Iceland, Norway and Sweden. Cases were matched to five controls by year of birth, sex and country. Lifetime occupational ELF-MF and electric shock exposures were assigned to jobs reported in population censuses using job-exposure matrices. The risk of cancer was assessed based on cumulative exposure to ELF-MF and electric shocks. ORs with 95% CIs were estimated using logistic models adjusted for occupational co-exposures relevant to lymphomas.

Results

Less than 7% of the cases experienced high levels of ELF-MF. We observed no increased risks among workers exposed to high levels of ELF-MF for NHL (OR: 0.93; CI 0.90 to 0.97), CLL (OR: 0.98; CI 0.92 to 1.05) or MM (OR: 0.96; CI 0.90 to 1.01).

Conclusion

Our results do not provide support for an association between occupational exposure to ELF-MFs and electric shocks and lymphoma risk.
Effects of temperature-dependent thermal conductivity with variable Biot number on a fully developedflow in a porous channel using LTNE (local thermal nonequilibrium) model
Authors: Kaur Rajvinder , Chandra Avinash , Sharma Sapna
Published: June 2022

The thermal conductivity of the porous materials is dependent on the temperature in a range of applications, including nuclear reactors and fossil fuel sources. The LTNE (local thermal nonequilibrium) model is widely used to study the thermal interactions between solid and fluid phases inside the porous media. The majority of the prior LTNE models assumed the constant thermal conductivities of both the fluid and solid phases, but in actual practice, the thermal conductivities depend on the temperature variations. In the current study, the effective thermal conductivities of the fluid and solid phases in the porous channel are considered as the functions of the respective temperatures by implementing the LTNE model. The Biot number is assumed to vary linearly, quadratically and sinusoidally along with the channel height. The thermal conductivity variation parameter [Formula: see text], porosity [Formula: see text] the ratio of fluid and solid phase thermal conductivities [Formula: see text] and heat generation parameter [Formula: see text] are considered as the main operating parameters. A system of ordinary differential equations has been derived and solved numerically under the above-mentioned conditions which is the generalization of the constant thermal conductivities of both the phases. The present results are validated with the already published results for the constant thermal conductivity and variable Biot number with the LTNE model. The obtained results show that the maximum heat transfer between the two phases is observed by taking [Formula: see text] as the linear increasing function of [Formula: see text] i.e., [Formula: see text] and correspondingly, it provides the highest values of Nusselt number. The Nusselt number increases with the decrement in thermal conductivity variation parameter [Formula: see text], heat generation parameter [Formula: see text] and ratio of fluid to solid phase conductivities [Formula: see text] A complex relationship has been observed between the porosity and the Nusselt number.
Adversarial Auto-encoder Domain Adaptation for Cold-start Recommendation with Positive and Negative Hypergraphs
Authors: Wu Hanrui , Long Jinyi , Li Nuosi , Yu Dahai , Ng Michael K.
Published: June 2022

This article presents a novel model named Adversarial Auto-encoder Domain Adaptation to handle the recommendation problem under cold-start settings. Specifically, we divide the hypergraph into two hypergraphs, i.e., a positive hypergraph and a negative one. Below, we adopt the cold-start user recommendation for illustration. After achieving positive and negative hypergraphs, we apply hypergraph auto-encoders to them to obtain positive and negative embeddings of warm users and items. Additionally, we employ a multi-layer perceptron to get warm and cold-start user embeddings called regular embeddings. Subsequently, for warm users, we assign positive and negative pseudo-labels to their positive and negative embeddings, respectively, and treat their positive and regular embeddings as the source and target domain data, respectively. Then, we develop a matching discriminator to jointly minimize the classification loss of the positive and negative warm user embeddings and the distribution gap between the positive and regular warm user embeddings. In this way, warm users’ positive and regular embeddings are connected. Since the positive hypergraph maintains the relations between positive warm user and item embeddings, and the regular warm and cold-start user embeddings follow a similar distribution, the regular cold-start user embedding and positive item embedding are bridged to discover their relationship. The proposed model can be easily extended to handle the cold-start item recommendation by changing inputs. We perform extensive experiments on real-world datasets for both cold-start user and cold-start item recommendations. Promising results in terms of precision, recall, normalized discounted cumulative gain, and hit rate verify the effectiveness of the proposed method.
MEGCF: Multimodal Entity Graph Collaborative Filtering for Personalized Recommendation
Authors: Liu Kang , Xue Feng , Guo Dan , Wu Le , Li Shujie , Hong Richang
Published: June 2022

In most E-commerce platforms, whether the displayed items trigger the user’s interest largely depends on their most eye-catching multimodal content. Consequently, increasing efforts focus on modeling multimodal user preference, and the pressing paradigm is to incorporate complete multimodal deep features of the items into the recommendation module. However, the existing studies
ignore the mismatch problem between multimodal feature extraction (MFE) and user interest modeling (UIM)
. That is, MFE and UIM have different emphases. Specifically, MFE is migrated from and adapted to upstream tasks such as image classification. In addition, it is mainly a content-oriented and non-personalized process, while UIM, with its greater focus on understanding user interaction, is essentially a user-oriented and personalized process. Therefore, the direct incorporation of MFE into UIM for purely user-oriented tasks, tends to introduce a large number of preference-independent multimodal noise and contaminate the embedding representations in UIM.

This paper aims at solving the mismatch problem between MFE and UIM, so as to generate high-quality embedding representations and better model multimodal user preferences. Towards this end, we develop a novel model,
m
ultimodal
e
ntity
g
raph
c
ollaborative
f
iltering, short for MEGCF. The UIM of the proposed model captures the semantic correlation between interactions and the features obtained from MFE, thus making a better match between MFE and UIM. More precisely, semantic-rich entities are first extracted from the multimodal data, since they are more relevant to user preferences than other multimodal information. These entities are then integrated into the user-item interaction graph. Afterwards, a symmetric linear
Graph Convolution Network (GCN)
module is constructed to perform message propagation over the graph, in order to capture both high-order semantic correlation and collaborative filtering signals. Finally, the sentiment information from the review data are used to fine-grainedly weight neighbor aggregation in the GCN, as it reflects the overall quality of the items, and therefore it is an important modality information related to user preferences. Extensive experiments demonstrate the effectiveness and rationality of MEGCF.

1
Photodissociation and X-Ray-Dominated Regions
Authors: Wolfire Mark G. , Vallini Livia , Chevance Mélanie
Published: June 2022

The radiation from stars and active galactic nuclei (AGNs) creates photodissociation regions (PDRs) and X-ray-dominated regions (XDRs), where the chemistry or heating is dominated by far-ultraviolet (FUV) radiation or X-ray radiation, respectively. PDRs include a wide range of environments, from the diffuse interstellar medium (ISM) to dense star-forming regions. XDRs are found in the center of galaxies hosting AGNs, in protostellar disks, and in the vicinity of X-ray binaries. In this review, we describe the dominant thermal, chemical, and radiation transfer processes in PDRs and XDRs, as well as give a brief description of models and their use for analyzing observations. We then present recent results from Milky Way, nearby extragalactic, and high-redshift observations.

Several important results include the following:

▪ Velocity-resolved PDR lines reveal the kinematics of the neutral atomic gas and provide constraints on the stellar feedback process. Their interpretation is, however, in dispute, as observations suggest a prominent role for stellar winds, whereas they are much less important in theoretical models. ▪ A significant fraction of molecular mass resides in CO-dark gas especially in low-metallicity and/or highly irradiated environments.

▪ The CO ladder and [Ci]/[Cii] ratios can determine if FUV or X rays dominate the ISM heating of extragalactic sources. ▪ With Atacama Large Millimeter/submillimeter Array, PDR and XDR tracers are now routinely detected on galactic scales over cosmic time. This makes it possible to link the star-formation history of the Universe to the evolution of the physical and chemical properties of the gas.
Use of core concepts of physiology can facilitate student transfer of learning
Authors: Michael Joel
Published: June 2022

Students often fail to utilize knowledge from prerequisite courses while learning physiology. They also fail to use what they know about one physiology topic when attempting to learn another topic. Much is known about the conditions that foster or promote transfer of learning. Applying this emerging knowledge and focusing on the core concepts of physiology can making learning physiology easier and provide students with tools to support lifelong learning.
Deep Learning-Based Magnetic Resonance Imaging in Diagnosis and Treatment of Intracranial Aneurysm
Authors: Lei Xiubing , Yang Yang
Published: June 2022

This study was focused on the positioning of the intracranial aneurysm in the magnetic resonance imaging (MRI) images using the deep learning-based U-Net model, to realize the computer-aided diagnosis of the intracranial aneurysm. First, a network was established based on the three-dimensional (3D) U-Net model, and the collected image data were input into the network to realize the automatic location and segmentation of the aneurysm. The 3D convolutional neural network (CNN) network can extract the aneurysm blood vessels to locate and identify the areas of possible aneurysms. Next, 40 patients highly suspected of intracranial aneurysm were selected as research subjects, and they were subjected to magnetic resonance angiography (MRA) and digital subtraction angiography (DSA) examinations. The results showed that based on the U-Net algorithm model, 40 patients’ hemangiomas were completely contained in the labeling bounding box, one patient’s hemangioma was at the edge of the labeling bounding box, and 4 patients’ hemangiomas were outside the labeling box. The final accuracy coefficient was 88.9%, and it was in good agreement with the doctor’s manual labelling results. Under the 3D CNN network test, the sensitivity, specificity, and accuracy of DSA for intracranial aneurysm were 91.46%, 86.01%, and 90.2%, respectively; the sensitivity, specificity, and accuracy of MRA for intracranial aneurysm were 95.87%, 100%, and 97.19%, respectively. In conclusion, the 3D CNN can successfully realize the positioning of intracranial aneurysm in MRA images, providing a certain theoretical basis for subsequent imaging diagnosis of aneurysm.
The Application of Motion Trajectory Acquisition and Intelligent Analysis Technology in Physical Education Teaching in Colleges and Universities
Authors: Wang Yun , Han Yong , Wang Qiang
Published: June 2022

Traditional classroom teaching analysis is mainly based on manual coding of time sampling, which has problems such as overreliance on experts, low analysis efficiency, and difficulty in large-scale services. Classroom teaching analysis based on artificial intelligence technology breaks through the predicament. With the continuous development of intelligent analysis technology, the research on physical education in colleges and universities becomes more and more meaningful. The task of physical education is to impart physical knowledge, technology, and skills to students, enhance their physical fitness, and cultivate their morality, will, and quality. It is one of the ways to implement sports goals. This article proposes how to change traditional teaching based on intelligent analysis technology. This article aims to study how to apply the emerging intelligent analysis technology to the physical education teaching process in colleges and universities; this enables students to be more personalized in the learning process, stimulates their enthusiasm for learning, and meets their basic requirements, breaking through traditional teaching methods, and making it possible to teach students in accordance with their aptitude. In the experimental analysis of this article, from the overall trend of the student evaluation data for 7 consecutive semesters, it can be found that the minimum value of the mean, median, and mode appears in the first semester of the 2016–2017 school year, and the maximum appears in the first semester of the 2019–2020 school year. The average score (mean) of students' evaluation of teaching fluctuates from 4.71 to 4.72, and the fluctuating range of the students' evaluation score (median) of the middlemost students is from 4.56 to 4.66. The results show that the intelligent analysis technology has played a stimulating effect on teachers' teaching and effectively mobilized teachers' teaching initiative. Therefore, the application of intelligent analysis technology is very necessary. Combine health education with moral education, intellectual education, physical education, aesthetic education, and labor education, and integrate it into the whole process of education, teaching, management and services, and build a health education system that is oriented to and responsible for everyone.
Effect Analysis of Lung Rehabilitation Training in 5A Nursing Mode for Elderly Patients with COPD Based on X-Ray
Authors: Xu Peihong , Zheng Wei , Zhu Yanjun
Published: June 2022

This study was aimed at evaluating the application effect of pulmonary rehabilitation training under 5A nursing mode based on X-ray in elderly patients with chronic obstructive pulmonary disease (COPD). Then, 84 elderly patients with chronic obstructive emphysema were selected as the research subjects. COPD knowledge level questionnaire, caregiver self-efficacy scale (CSES), COPD assessment test (CAT), and 6-minute walking experiment (6MWD) were adopted, and the clinical application effect of pulmonary rehabilitation training and conventional nursing under 5A nursing mode was comprehensively compared. The results show that after two and four months of intervention, the average score of COPD knowledge level questionnaire in the test group was 27.43 points and 30.08 points, respectively, higher than that in the control group (

P
<
0.05

). After two and four months of intervention, the number of patients with good compliance in the test group was remarkably improved, and the severity of airflow restriction in the test group was slower than that in the control group. In short, pulmonary rehabilitation training under 5A nursing mode based on X-ray can effectively improve the disease knowledge level, self-efficacy, and pulmonary rehabilitation training compliance of elderly COPD patients, which played an important role in improving the quality of life of patients and alleviating the degree of dyspnea of patients.
Antimicrobial Properties of Metal Nanoparticles and Their Oxide Materials and Their Applications in Oral Biology
Authors: Zhang Shujun , Lin Linghuang , Huang Xuanhao , Lu You-Guang , Zheng Da-Li , Feng Yan
Published: June 2022

Some scholars have shown that metal nanoparticles have excellent antibacterial properties and can be used as a new type of antibacterial agent. In recent years, with the in‐depth research on nanomaterials, its applications in the medical field have gradually increased. The oral cavity has a unique anatomical structure, and for oral infections, the current clinically commonly used treatment measures are oral or topical antibiotics. However, due to bacterial resistance and the special structure of dental plaque, the effect of antibiotics is not ideal. Metal and metal oxide nanoparticles have become the research hotspot of new antibacterial materials due to their small particles, large specific surface area, physical, mechanical, and chemical properties, and antibacterial properties. This article describes the antibacterial effect, antibacterial mechanism, biological toxicity, and application progress of metal nanomaterials in the oral cavity.
Fundamental Structure of General Stochastic Dynamical Systems: High‐Dimension Case
Authors: Wang Haoyu , Gan Xiaoliang , Hu Wenqing , Ao Ping
Published: June 2022

No one has proved that mathematically general stochastic dynamical systems have a special structure. Thus, we introduce a structure of a general stochastic dynamical system. According to scientific understanding, we assert that its deterministic part can be decomposed into three significant parts: the gradient of the potential function, friction matrix and Lorenz matrix. Our previous work proved this structure for the low‐dimension case. In this paper, we prove this structure for the high‐dimension case. Hence, this structure of general stochastic dynamical systems is fundamental.
Analysis of the Association between Teachers’ Classroom Teaching Behaviors and Students’ Knowledge Acceptance Based on Psychological Data Analysis
Authors: Yao Tianjin , Yang Xiuye
Published: June 2022

This paper adopts the method of psychological data analysis to conduct in-depth research and analysis on the correlation between teachers’ classroom teaching behaviors and students’ knowledge acceptance. Firstly, this paper proposes a health factor prediction model, which is specifically divided into clustering and then classification model and a clustering and classification synthesis model. The classroom learning process is coded, sampled, and quantified to obtain data on students’ learning behaviors, and a visualization system based on classroom students’ learning behaviors is designed and developed to record and analyze students’ behaviors in the classroom learning process and grasp students’ classroom learning. These two models use algorithms to fine-grained divide the dataset from the perspective of subject users and mental health factors, respectively, and then use decision tree algorithms to classify and predict the mental health factor information by the subject user base information. Second, based on the collected datasets, we designed comparison experiments to validate the clustering-then-classification model and the integrated clustering-classification model and selected the optimal model for comparison. Teachers should increase effective praise and encouragement behaviors; teachers should increase meaningful teacher-student interaction behaviors; teachers should be proficient in teaching media technology to reduce unnecessary time wastage. Strategies to enhance teachers’ TPACK include enriching teachers’ knowledge base of CK, TK, and PK; developing teachers’ integration thinking; and enriching teachers’ types of activities for integrating technology.
A Study on the Integration of Business English Teaching and Intercultural Communication Skills Cultivation Model Based on Intelligent Algorithm
Authors: Liu Wenjun
Published: June 2022

With the current prevalence of economic globalization, English is still the international language of choice. The definition of cross-cultural: have a full and correct understanding of cultural phenomena, customs, and habits that are different or conflicting with the national culture, and accept and adapt to it with an inclusive attitude on this basis. Therefore, for Chinese universities, the focus is on cultivating highly qualified talents with intercultural communication skills for the country’s economic development. Intercultural communication skills are an important part of students’ language communication skills. China’s business English teaching has also begun to focus on the cultivation of students’ cross-cultural communication skills, but the effect is not satisfactory. In business English teaching, the most important thing is to improve students’ professional competence and business English expertise, and to cultivate foreign language talents with cross-cultural quality and global awareness. Based on the above reasons, this paper proposes a research on the integration of business English teaching and intercultural communication competence cultivation based on intelligent algorithms. First, this paper adopts the literature method to understand the difficulties in traditional business English teaching and the problems in the process of cultivating intercultural communication competence; then, it adopts the inductive-deductive method of intelligent algorithm and action research method to study the mode of cultivating intercultural communication competence and comprehensive experimental research. Finally, after comprehensive analysis, it was concluded that: the number of domestic literature on intercultural communication competence cultivation increased by 11.98%, and the number of literature was generally on the rise; there were significant differences in test results; the experimental students who were satisfied with the cultivation model studied in this paper reached 45.6%. This article attempts to investigate and analyze the needs of English majors for the cultivation of business English intercultural communicative competence, so as to provide a reference for cultivating students’ intercultural communicative competence. The above data fully indicate that the use of contextual teaching method to cultivate intercultural communication skills in business English courses is effective, attracting students’ enjoyment, cultivating their intercultural communication skills, enhancing their understanding of business etiquette, and improving their ability to conduct business conversations. Intercultural communicative competence refers to the ability to communicate when two parties from different cultural backgrounds communicate in the same situation.
Synthesis and Characterization of Novel [2 + 1] Tricarbonyl Rhenium Complexes with the Hydrophilic Phosphine Ligands PTA and CAP
Authors: Roupa Ioanna , Flampouraris Charalampos , Shegani Antonio , Ischyropoulou Myrto , Makrypidi Konstantina , Raptopoulou Catherine , Pirmettis Ioannis , Papadopoulos Minas S. , Psycharis Vassilis , Chiotellis Aristeidis
Published: June 2022

In the pursuit of hydrophilic model fac‐[Re(CO)3]+ complexes for (radio) pharmaceutical applications, six novel [2 + 1] mixed‐ligand complexes of the general type fac‐[Re(CO)3(bid)P] were synthesized and characterized, where bid is a bidentate ligand bearing either (N, O) or (S, S′) donor atom sets and P is the hydrophilic phosphine 1,3,5‐triaza‐7‐phosphoadamantane (PTA) or its macrocyclic homologue 1,4,7‐triaza‐9‐phosphatricyclo[5.3.2.1]tridecane (CAP). The (N, O) ligands used in this study were picolinic and quinaldic acid, while the (S, S′) ligand was diethyldithiocarbamate. The complexes were synthesized in generally high yields and purity and the characterization was performed by spectroscopic methods, IR, NMR, and elemental analysis. Detailed X‐ray crystallographic study of molecular packing by using Hirshfeld analysis tools revealed a plethora of intermolecular interactions such as hydrogen bond, π⋯π, C‐H⋯π, and carbonyl‐carbonyl interactions. To our knowledge, the CAP complexes reported herein are the first example of [2 + 1] mixed‐ligand fac‐[Re(CO)3]+ complexes with CAP. The new complexes might have the potential to serve as platforms for the design of target‐specific complexes with favorable pharmacokinetics.
Integration of Multiple Models with Hybrid Artificial Neural Network‐Genetic Algorithm for Soil Cation‐Exchange Capacity Prediction
Authors: Shahabi Mahmood , Ghorbani Mohammad Ali , Naganna Sujay Raghavendra , Kim Sungwon , Hadi Sinan Jasim , Inyurt Samed , Farooque Aitazaz Ahsan , Yaseen Zaher Mundher
Published: June 2022

The potential of the soil to hold plant nutrients is governed by the cation‐exchange capacity (CEC) of any soil. Estimating soil CEC aids in conventional soil management practices to replenish the soil solution that supports plant growth. In this study, a multiple model integration scheme supervised with a hybrid genetic algorithm‐neural network (MM‐GANN) was developed and employed to predict the accuracy of soil CEC in Tabriz plain, an arid region of Iran. The standalone models (i.e., artificial neural network (ANN) and extreme learning machine (ELM)) were implemented for incorporation into the MM‐GANN. In addition, it was tested to enhance the prediction accuracy of the standalone models. The soil parameters such as clay, silt, pH, carbonate calcium equivalent (CCE), and soil organic matter (OM) were used as model inputs to predict soil CEC. With the use of several evaluation criteria, the results showed that the MM‐GANN model involving the predictions of ELM and ANN models calibrated by considering all the soil parameters (e.g., Clay, OM, pH, silt, and CCE) as inputs provided superior soil CEC estimates with a Nash Sutcliffe Efficiency (NSE) = 0.87, Root Mean Square Error (RMSE) = 2.885, Mean Absolute Error (MAE) = 2.249, Mean Absolute Percentage Error (MAPE) = 12.072, and coefficient of determination (R2) = 0.884. The proposed MM‐GANN model is a reliable intelligence‐based approach for the assessment of soil quality parameters intended for sustainability and management prospects.
Resting-State Functional Magnetic Resonance Image to Analyze Electrical Biological Characteristics of Major Depressive Disorder Patients with Suicide Ideation
Authors: He Cui , Wang Yeyan , Bai Hanping , Li Ruiting , Fang Xiangming
Published: June 2022

The study was aimed to explore the brain imaging characteristics of major depressive disorder (MDD) patients with suicide ideation (SI) through resting-state functional magnetic resonance imaging (rs-fMRI) and to investigate the potential neurobiological role in the occurrence of SI. 50 MDD patients were selected as the experimental group and 50 healthy people as the control group. The brain images of the patients were obtained by MRI. Extraction of EEG biological features was from rs-fMRI images. Since MRI images were disturbed by noise, the initial clustering center of FCM was determined by particle swarm optimization algorithm so that the noise of the collected images was cleared by adaptive median filtering. Then, the image images were processed by the optimized model. The correlation between brain mALFF and clinical characteristics was analyzed. It was found that the segmentation model based on the FCM algorithm could effectively eliminate the noise points in the image; that the zALFF values of the right superior temporal gyrus (R-STG), left middle occipital gyrus (L-MOG), and left middle temporal gyrus (L-MTG) in the observation group were significantly higher than those in the control group (

P
<
0.05

); and that the average zALFF values of left thalamus (L-THA) and left middle frontal gyrus (L-MFG) decreased. The mean zALFF values of L-MFG and L-SFG demonstrated good identification value for SI in MDD patients. In summary, MRI images based on FCM had a good convergence rate, and electrical biological characteristics of brain regions were abnormal in MDD patients with SI, which can be applied to the diagnosis and treatment of patients with depression in clinical practice.
Research on the Optimization of Agricultural Industry Structure Based on Genetic Algorithm
Authors: Liu Lingxiao
Published: June 2022

Due to the complexity and importance of optimizing and adjusting the crop planting structure in the Jianghuai hilly Tangba irrigation area between the upper reaches of the Huaihe River from Xinyang to the lower reaches of the Huaihe River in China, and based on experimental results from the Feidong Badou Irrigation Experiment Station, the farmland was modeled using rainfall and runoff data from the Tangba irrigation area. By examining the water balance of submerged irrigation, an optimization model of the agricultural industry structure was developed using genetic algorithms, and the model was solved using an accelerated genetic algorithm. Developing the research findings may provide scientific and technological support for adjusting the planting structure and formulation of irrigation systems in the Jianghuai Hills and Tangba irrigation area between the upper reaches of the Huaihe River and Xinyang, as well as significant practical guiding significance and application value.
Land Suitability Assessment for Apple (Malus domestica) Production in Sentele Watershed in Hadiya Zone, Southern Ethiopia
Authors: Beyene Getachew , Dechassa Nigussie , Regasa Alemayehu , Wogi Lemma
Published: June 2022

Apple (Malus domestica) is cultivated in Southern Ethiopia. However, the crop is being grown in without affirming the suitability of the land for its cultivation. Therefore, this research was conducted to assess the suitability of the land of Sentele Watershed for apple production in Southern Ethiopia. Integrating GIS and analytic hierarchy process (AHP) method, which is widely used in multi-criteria decision-making for tackling multi-attribute decision-making problems in real situations, was used in this study. In the application techniques, most attributes that determine apple growth, climate, edaphic, topography, and current land use/land cover were combined. In determining the weights of the attributes, the opinions of experts and experienced apple orchard workers were considered, and an agricultural land suitability map was produced as highly suitable, moderately suitable, marginally suitable, and least suitable. The methodology was based on the land evaluation developed by FAO (1976) that suggests biophysical diagnostic factors, which most strongly influenced the cultivation of apples. Criteria were defined, background information was gathered, and a raster surface was created. The layers are reclassified, weighed, and then the output layers are overlaid with the background information such as a map of topography to see the best potential sites and to prepare the final suitability map. The final apple suitability map showed that only 2.2% of the total land is highly suitable, 32% is moderately suitable, and 52.1% is marginally suitable, and it requires detailed investigation and careful decision over other land uses to invest in it. 13.7% is the least suitable for apple cultivation. It is concluded that about 34% of the total land of the study area is suitable for apple production, and about 66% is unsuitable. The results imply that it is necessary to take improvement measures such as irrigation, species selection, removing leaves (defoliation), and appropriate land-use planning in most of the land of the watershed before investing in apple cultivation and production, and it is necessary to expand apple production in the future only in areas that are highly and moderately suitable for producing the crop in the study area.
Evaluation of the Degradation Process of Diethyl (3H-1-Ethoxy-3-phenoxazinylidene) Ammonium Chloride in Water, after Exposure to Nonthermal Plasma at Atmospheric Pressure
Authors: Alarcón Hernández Fidel Benjamín , Fuentes Albarrán María del Carmen , Gadea Pacheco José Luis , Tlatelpa Becerro Ángel , Cañete Cabrera Víctor Aristeo
Published: June 2022

The present study characterizes the degradation of diethyl dye (3H-1-ethoxy-3-phenoxazinylidene) ammonium chloride in water (concentration of 20.00 mg/L), after its exposure to nonthermal plasma of air at atmospheric pressure. The exposure time of the solution of interest to the plasma was 250 minutes per treatment. Four different nonthermal plasma generation conditions were considered (15, 20, 25, and 30 mA) at a voltage of 2000 V. The change in dilution was determined by UV/VIS spectrophotometry (absorbance and concentration), chemical oxygen demand (COD), pH, and bioassays with lettuce seeds (Lactuca sativa). Given the increase in temperature of the sample under study due to exposure to plasma, the change in each of the measured parameters was also explored as an exclusive function of the increase in temperature (27°C to 44°C). The measurements did not show the influence of temperature on the changes observed in the parameters of interest in this experiment. In general, the maximum degradation obtained from the samples analyzed at the end of the treatments corresponds to the 30 mA treatment. For this, reductions of 70.4% in absorbance, 71.5% of dye concentration, 81.6% of COD, and 51.85% of pH were achieved. The germination percentage of the lettuce seeds obtained was 74%. The degradation of the dye in the solution of interest depends on the plasma generating parameters high power and the high degradation rate.
Activated Sawdust-Based Adsorbent for the Removal of Basic Blue 3 and Methylene Green from Aqueous Media
Authors: Rahman Najeeb Ur , Bahadar Wasim , Alam Sultan , Zahoor Muhammad , Zekker Ivar , Khan Farhat Ali , Ullah Riaz , Ali Essam A. , Murthy H. C. Ananda
Published: June 2022

Dye pollution is a serious threat to aquatic environment and human health. Although activated carbon is an efficient adsorbent for dye reclamation from effluents, its expressive nature renders its use on large commercial scales. On the other hand, waste biomasses are not effectively used for any beneficial purposes. Sawdust is a waste biomass of wood mills, and due to its small particle sizes, it has the potential to be used as adsorbent. In spite of its uses for cooking purposes, it is sometimes used as adsorbent as such or converted into activated carbon. In raw form, it is not a good adsorbent; however, its adsorption capacity can be increased by applying chemical modifications. In the present study, sawdust of paper mulberry ( Broussonetia papyrifera) was used as adsorbent for the removal of basic blue 3 and methylene green from water after chemical modification with NaOH and HCl in 1 : 1. The prepared adsorbent was characterized by SEM and FTIR, whereas the surface area was estimated through an already reported method in literature. Batch experiments were performed to determine the isothermal and kinetic parameters of the selected dyes adsorption on activated sawdust. The effect of adsorbent dosage and temperature on adsorption were also evaluated. The best fit of the kinetic data was achieved with pseudosecond-order model for which [Formula: see text] values were approximately equal to 1 whereas Langmuir model was most suitable model to explain the isothermal data. The optimum adsorbent dosage was 0.05 g for both of the selected dyes. Different thermodynamic parameters, such as enthalpy ([Formula: see text] and 8.334 kJ/mol respectively for basic blue 3 and methylene green), entropy ([Formula: see text] and 29.22 kJ/molK respectively for basic blue 3 and methylene green), and Gibbs free energy ([Formula: see text], -410, and -1658 kJ/mol (basic blue)/-65, -519, and -1139 kJ/mol (methylene green), were estimated, and the process was found to be endothermic, spontaneous, and feasible. The increase in [Formula: see text] with increase in temperature indicates that the adsorption process is favorable at high temperature. The prepared adsorbent could be effectively used in the reclamation of water loaded with other contaminants; however, further experiments are needed to increase the adsorption capacity of the adsorbent.
Regression Based Price Prediction of Staple Food Materials Using Multivariate Models
Authors: Venkateswara Rao K. , Srilatha D. , Jagan Mohan Reddy D. , Desanamukula Venkata Subbaiah , Kejela Mandefro Legesse
Published: June 2022

Profit margins for essential foodstuffs could be a demand rising problem. There are several variables influencing currency fluctuations. For example, the various variables of commodity food prices are climate, crude prices, and so on. Forecasting the fluctuating prices of basic foodstuffs is also relevant even for the government, producers, and customers. The article will use ARCH (autoregressive conditional heteroskedasticity) to forecast the essential food market considering external conditions. The findings agree well enough with the assessment price in the industry by employing two main approaches, ARCH and GARCH (generalized autoregressive conditional heteroskedasticity). For jalapeno, the best result (96.87%) in estimating the cost of employing ARCH is achieved. In the meantime, the best result (99.94%) for the basic food tomato is observed using GARCH. Proportionally, the ARCH is stronger than GARCH, since GARCH is very consistent without disrupting current information.
Effect of Parecoxib Sodium Preemptive Analgesia on the Recovery Period of General Anesthesia in Patients Undergoing Glioma Resection
Authors: Zhu Lijuan , Guo Hui , Zheng Tao , Zhu Jing
Published: June 2022

Objective. To investigate the effect of parecoxib sodium preemptive analgesia on postoperative complications and postoperative recovery of patients undergoing glioma resection. Methods. A total of 200 eligible patients with low-grade gliomas in the functional brain area scheduled for an awake craniotomy between January 2017 and December 2020 were reviewed. The subjects were divided into two groups: the study group (n = 100) given dexmedetomidine plus parecoxib sodium for pre-emptive analgesia 30 minutes preoperatively, and the control group (n = 100) receiving dexmedetomidine alone. Venous blood was collected before surgery, at the time of postoperative recovery, and 24 hours after operation, mean artery pressure (MAP) and heart rate (HR) were recorded during surgery. Sedation satisfaction, agitation rate, numerical pain score (NRS), postoperative complications, minimental state examination (MMSE) scores, quality of life (QoL) scores, and incidence of adverse events were also investigated after the surgery. Results. There were no significant differences in operation time, awakening time, intraoperative awakening time, and extubation time between the two groups (

P
>
0.05

). Compared with the control group, the ΔMAP (7.26 ± 2.21 versus 5.78 ± 2.36 mmHg) and the ΔHR (11.35 ± 3.66 versus 8.84 ± 2.47 beats/min) were significantly lower in the study group (

P
<
0.05

). Compared with the control group, the satisfaction was higher and agitation rate was lower in the study group (

P
<
0.05

). The incidence of intracranial infection and pulmonary infection decreased after operation (

P
<
0.05

). The NRS of the study group was remarkably lower than the control group at 12 hours postoperatively Preoperative MMSE score and QoL score showed no statistical difference (

P
>
0.05

), while postoperative MMSE and QoL scores showed statistical difference (

P
<
0.05

). Conclusion. This study suggests that parecoxib sodium can significantly improve the level of sedation and analgesia in patients undergoing glioma resection, reduce the incidence of intracranial infection and pulmonary infection.