bluuebunny/crossref_metadata_2025 huggingface dataset:
HIV-related stress predicts depression over five years among people living with HIV
Authors: Liu Zongyan , Chen Xi , Li Jie , Xie Zhi , Huang Yunxiang , Luo Dan
Published: June 2023

Introduction

Extant literature has demonstrated significant associations between HIV-related stress, social support, and depression among PLWH. However, little research has been conducted on the changes in such associations over time. Our study aims to explore the longitudinal relationship between HIV-related stress, social support, and depression among PLWH over five years.

Methods

320 PLWH were recruited from Changsha Center for Disease Control and Prevention (CDC), Hunan Province, China. They were assessed for depressive symptoms, HIV-related stress, and social support within 1 month of HIV diagnosis, 1 year after diagnosis, and five years after diagnosis, respectively. Relationships between these variables were examined using a fixed effect model.

Result

The prevalence of depressive symptoms within the first month, first year, and fifth years of HIV diagnosis was 35, 12.2, and 14.7%, respectively. Emotional stress (β: 0.730, 95% CI: 0.648, 0.811), social stress (β: 0.066, 95% CI: 0.010, 0.123), instrumental stress (β: 0.133, 95% CI:0.046, 0.221) positively predicted depression, while social support utilization (β: −0.176, 95% CI: −0.303, −0.049) negatively predicted depression.

Conclusion

Our study suggests that HIV-related stress and social support predict depressive symptoms over time among PLWH and that reducing HIV-related stress and improving social support in the early stages of diagnosis is extremely important in preventing depressive symptoms among PLWH.
Relationships between dental fluorosis and fluoride concentrations in bottled water and groundwater in low-income children in Mexico
Authors: Irigoyen-Camacho Maria Esther , Perez-Perez Nora , Zepeda-Zepeda Marco Antonio , Velazquez-Alva Maria Consuelo , Castaño-Seiquer Antonio , Barbero-Navarro Ignacio , Sanchez-Perez Leonor
Published: June 2023

Introduction

The aim of the current study was to investigate associations between dental fluorosis in children living in low socioeconomic areas in Mexico, and fluoride concentrations in tap water, fluoride concentrations and in bottled water, and body mass index (BMI).

Methods

A cross-sectional study involving 585 schoolchildren aged 8–12 years was conducted in communities in a southern state of Mexico with >0.7 parts per million (ppm) fluoride in the groundwater. The Thylstrup and Fejerskov index (TFI) was used to evaluate dental fluorosis, and the World Health Organization growth standards were used to calculate age-adjusted and sex-adjusted BMI Z-scores. A BMI Z-score ≤ −1 SD was used as the cut-off point for thinness, and multiple logistic regression models for dental fluorosis (TFI ≥ 4) were constructed.

Results

The mean fluoride concentration in tap water was 1.39 ppm (SD 0.66), and the mean fluoride concentration in bottled water was 0.32 ppm (SD 0.23). Eighty-four children (14.39%) had a BMI Z-score ≤ −1 SD. More than half (56.1%) of the children presented with dental fluorosis in TFI categories ≥ 4. Children living in areas with higher fluoride concentrations in the tap water [odds ratio (OR) 1.57, p = 0.002] and bottled water (OR 3.03, p < .001) were more likely to have dental fluorosis in the severe categories (TFI ≥ 4). BMI Z-score was associated with the probability of dental fluorosis (TFI ≥ 4; OR 2.11, p < 0.001), and the effect size was 29.3%.

Discussion

A low BMI Z-score was associated with a higher prevalence of dental fluorosis in the severe category. Awareness of the fluoride concentrations in bottled water may help prevent dental fluorosis, particularly in children exposed to several high fluoride content sources. Children with a low BMI may be more vulnerable to dental fluorosis.
Development of Multiplex RT-PCR Assay for the Simultaneous Detection of Four Systemic Diseases Infecting Citrus
Authors: Yao Shun-Min , Wu Meng-Ling , Hung Ting-Hsuan
Published: June 2023

The citrus systemic diseases, including citrus Huanglongbing (caused by Candidatus Liberibacter asiaticus (CLas)), citrus tristeza (caused by citrus tristeza virus (CTV)), citrus tatter leaf (caused by citrus tatter leaf virus (CTLV)), and citrus exocortis (caused by citrus exocortis viroid (CEVd)), are threats to citrus production in Taiwan. Reliable diagnostic methods are important for the management of these systemic diseases. In this study, we developed a multiplex reverse transcription–polymerase chain reaction (RT-PCR) assay to detect four pathogens simultaneously. Herein, the specific amplicons from each pathogen (295 bp for CLas, 468 bp for CTV, 120 bp for CTLV, and 196 bp for CEVd) were successfully produced using the optimized multiplex RT-PCR described here. The sensitivity evaluation showed that low titers of pathogens could be detected using this multiplex RT-PCR. Compared with the published simplex assays, the detection of field samples using the multiplex RT-PCR developed in this study showed a better performance. The detections using multiplex RT-PCR revealed that these four citrus systemic pathogens were commonly found in fields, and 30.0% of field samples were mix-infected. To our knowledge, this is the first study of a survey of the four important citrus systemic diseases in Taiwan, and it provides insights for improving disease management. Therefore, the multiplex RT-PCR assay provides a useful method for routine disease surveying and the production of pathogen-free citrus plants.
Design of an Automatic Ground Cleaning Machine for Dedusting Rooms of Chicken Houses
Authors: Yin Yiting , Diao Ailin , Li Ziyi , Wang Qi , Liu Shuguang
Published: June 2023

In this paper, we designed an automatic ground cleaning machine for the dedusting rooms of chicken houses to replace the manual daily cleaning of dust particles and fluff. The machine mainly comprised a power system, control system, frame and walking structure, ground cleaning system, and dedusting system. The automatic movement of the machine body in two vertical directions without turning, lifting, and lowering of the sweeper; the retraction and expansion of the sweeper support arm; the reciprocating movement of the sweeper relative to the machine body; and the timely separation of the dust particles and fluff from gas mixtures were achieved. Parameter optimization experiments on the machine were performed using a quadratic general rotary combination design considering the movement speed, rotation speed of the sweeper, and distance between the suction head nozzle and ground as experimental factors. The regression equations describing the relationship between the three experimental factors and the dust particle removal rate and fluff removal rate were obtained using Design-Expert 12 software, adequately reflecting the impact of the three experimental factors on the two experimental indexes. Further parameter optimization was conducted to obtain the optimized parameter combination at the same weight as the two experimental indexes: movement speed of 0.1 m/s, rotation speed of the sweeper of 198 r/min, and distance between the suction head nozzle and ground of 12 mm. The performance experiment on the machine was conducted using the optimized parameter combination, yielding a dust particle removal rate of 90.7% and fluff removal rate of 91.7%. The experimental results show that the machine exhibits good performance and stable operation, meeting the daily cleaning needs of large-, medium-, and small-scale rectangular dedusting rooms of chicken houses.
Cutibacterium acnes KCTC 3314 Growth Reduction with the Combined Use of Bacteriophage PAP 1-1 and Nisin
Authors: Han Min-Hui , Khan Shehzad Abid , Moon Gi-Seong
Published: June 2023

Severe acne has high psychological impacts recorded worldwide, from depression to suicide. To control acne infection, bacteriophage could be used in synergy or combination with antibiotics/antimicrobials. Bacteriophages are specific to their hosts without interfering with the normal skin microbes and have the ability to lyse bacterial cells. In this current study, the bacteriophage PAP 1-1 was isolated, characterized, and tested against the pathogenic acne-causing bacterium Cutibacterium acnes. Examination under transmission electron microscopy (TEM) revealed that the newly isolated phage has a morphology typical of siphoviruses. Phylogenetic analysis, utilizing the maximum likelihood (ML) algorithm based on complete genome sequences, revealed that PAP 1-1 clustered together with bacteriophages active to Propionibacterium acnes (now known as C. acnes), forming a distinct evolutionary lineage. The genomic analysis further identified the presence of an endolysin gene in PAP 1-1, suggesting its potential to regulate the growth of C. acnes. Subsequent experiments conducted in RCM broth confirmed the ability of PAP 1-1 to effectively control the proliferation of C. acnes. In combination with bacteriocin from Lactococcus lactis CJNU 3001 and nisin, PAP 1-1 greatly decreased the viable cell counts of C. acnes in the broth.
Genomic Characterization of Aeromonas veronii Provides Insights into Taxonomic Assignment and Reveals Widespread Virulence and Resistance Genes throughout the World
Authors: Maia José Cleves da Silva , Silva Gabriel Amorim de Albuquerque , Cunha Letícia Stheffany de Barros , Gouveia Gisele Veneroni , Góes-Neto Aristóteles , Brenig Bertram , Araújo Fabrício Almeida , Aburjaile Flávia , Ramos Rommel Thiago Jucá , Soares Siomar Castro , Azevedo Vasco Ariston de Carvalho , Costa Mateus Matiuzzi da , Gouveia João José de Simoni
Published: June 2023

Aeromonas veronii is a Gram-negative bacterial species that causes disease in fish and is nowadays increasingly recurrent in enteric infections of humans. This study was performed to characterize newly sequenced isolates by comparing them with complete genomes deposited at the NCBI (National Center for Biotechnology Information). Nine isolates from fish, environments, and humans from the São Francisco Valley (Petrolina, Pernambuco, Brazil) were sequenced and compared with complete genomes available in public databases to gain insight into taxonomic assignment and to better understand virulence and resistance profiles of this species within the One Health context. One local genome and four NCBI genomes were misidentified as A. veronii. A total of 239 virulence genes were identified in the local genomes, with most encoding adhesion, motility, and secretion systems. In total, 60 genes involved with resistance to 22 classes of antibiotics were identified in the genomes, including mcr-7 and cphA. The results suggest that the use of methods such as ANI is essential to avoid misclassification of the genomes. The virulence content of A. veronii from local isolates is similar to those complete genomes deposited at the NCBI. Genes encoding colistin resistance are widespread in the species, requiring greater attention for surveillance systems.
Antibiotic Prophylaxis for the Prevention of Urinary Tract Infections in Children: Guideline and Recommendations from the Emilia-Romagna Pediatric Urinary Tract Infections (UTI-Ped-ER) Study Group
Authors: Autore Giovanni , Bernardi Luca , Ghidini Filippo , La Scola Claudio , Berardi Alberto , Biasucci Giacomo , Marchetti Federico , Pasini Andrea , Capra Maria Elena , Castellini Claudia , Cioni Vera , Cantatore Sante , Cella Andrea , Cusenza Francesca , De Fanti Alessandro , Della Casa Muttini Elisa , Di Costanzo Margherita , Dozza Alessandra , Gatti Claudia , Malaventura Cristina , Pierantoni Luca , Parente Giovanni , Pelusi Gabriella , Perrone Serafina , Serra Laura , Torcetta Francesco , Valletta Enrico , Vergine Gianluca , Antodaro Francesco , Bergomi Andrea , Chiarlolanza Jennifer , Leoni Laura , Mazzini Franco , Sacchetti Roberto , Suppiej Agnese , Iughetti Lorenzo , Pession Andrea , Lima Mario , Esposito Susanna ,   The UTI-Ped-ER Study Group
Published: June 2023

Background: Urinary tract infection (UTI) represents one of the most common infectious diseases and a major cause of antibiotic prescription in children. To prevent recurrent infections and long-term complications, low-dose continuous antibiotic prophylaxis (CAP) has been used. However, the efficacy of CAP is controversial. The aim of this document was to develop updated guidelines on the efficacy and safety of CAP to prevent pediatric UTIs. Methods: A panel of experts on pediatric infectious diseases, pediatric nephrology, pediatric urology, and primary care was asked clinical questions concerning the role of CAP in preventing UTIs in children. Overall, 15 clinical questions were addressed, and the search strategy included accessing electronic databases and a manual search of gray literature published in the last 25 years. After data extraction and narrative synthesis of results, recommendations were developed using the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) methodology. Results: The use of CAP is not recommended in children with a previous UTI, with recurrent UTIs, with vesicoureteral reflux (VUR) of any grade, with isolated hydronephrosis, and with neurogenic bladder. CAP is suggested in children with significant obstructive uropathies until surgical correction. Close surveillance based on early diagnosis of UTI episodes and prompt antibiotic therapy is proposed for conditions in which CAP is not recommended. Conclusions: Our systematic review shows that CAP plays a limited role in preventing recurrences of UTI in children and has no effect on its complications. On the other hand, the emergence of new antimicrobial resistances is a proven risk.
Rational Design of Multifunctional Ferulic Acid Derivatives Aimed for Alzheimer’s and Parkinson’s Diseases
Authors: Guzmán-López Eduardo Gabriel , Reina Miguel , Hernández-Ayala Luis Felipe , Galano Annia
Published: June 2023

Ferulic acid has numerous beneficial effects on human health, which are frequently attributed to its antioxidant behavior. In this report, many of them are reviewed, and 185 new ferulic acid derivatives are computationally designed using the CADMA-Chem protocol. Consequently, their chemical space was sampled and evaluated. To that purpose, selection and elimination scores were used, which are built from a set of descriptors accounting for ADME properties, toxicity, and synthetic accessibility. After the first screening, 12 derivatives were selected and further investigated. Their potential role as antioxidants was predicted from reactivity indexes directly related to the formal hydrogen atom transfer and the single electron transfer mechanisms. The best performing molecules were identified by comparisons with the parent molecule and two references: Trolox and α-tocopherol. Their potential as polygenic neuroprotectors was investigated through the interactions with enzymes directly related to the etiologies of Parkinson’s and Alzheimer’s diseases. These enzymes are acetylcholinesterase, catechol-O-methyltransferase, and monoamine oxidase B. Based on the obtained results, the most promising candidates (FA-26, FA-118, and FA-138) are proposed as multifunctional antioxidants with potential neuroprotective effects. The findings derived from this investigation are encouraging and might promote further investigations on these molecules.
Modulation of Alveolar Macrophage Activity by Eugenol Attenuates Cigarette-Smoke-Induced Acute Lung Injury in Mice
Authors: Barbosa-de-Oliveira Maria Clara , Oliveira-Melo Paolo , Gonçalves da Silva Marcos Henrique , Santos da Silva Flávio , Andrade Carvalho da Silva Felipe , Silva de Araujo Bruno Vinicios , Franco de Oliveira Moacir , Tadeu Correia Aristides , Miyoshi Sakamoto Sidnei , Valença Samuel Santos , Lanzetti Manuella , Schmidt Martina , Kennedy-Feitosa Emanuel
Published: June 2023

This study investigates the role of eugenol (EUG) on CS-induced acute lung injury (ALI) and how this compound is able to modulate macrophage activity. C57BL/6 mice were exposed to 12 cigarettes/day/5days and treated 15 min/day/5days with EUG. Rat alveolar macrophages (RAMs) were exposed to CSE (5%) and treated with EUG. In vivo, EUG reduced morphological changes inflammatory cells, oxidative stress markers, while, in vitro, it induced balance in the oxidative stress and reduced the pro-inflammatory cytokine release while increasing the anti-inflammatory one. These results suggest that eugenol reduced CS-induced ALI and acted as a modulator of macrophage activity.
Experimental Study on the Soil–Structure Responses Induced by Tunnelling in Limited Space
Authors: Guo Jian , Liu Guobin
Published: June 2023

As the economy develops rapidly, newly built tunnels in congested urban areas are becoming more and more common. Based on similarity theory, this study conducted a laboratory model test to investigate the soil–structure responses induced by the construction of a new tunnel in limited space which was formed by the existing underground infrastructures. The soil movement, convergence of the tunnel and distribution of the soil stress were explored. The test results revealed that the limited space could have a significant shielding effect on the soil movement. The maximum ground subsidence and the range of ground settlement induced by the construction of the tunnel in limited space were 60% and 40%, respectively, smaller than those induced by the construction of a tunnel at a “greenfield” site. The deformation of the tunnel was also restrained distinctly. Moreover, a soil settlement trough appeared below the bottom slab of the underground structure. The findings can shed some light on the surrounding responses induced by tunnelling in limited space in soft clay and can offer the valuable guidance for the similar projects.
Ozone Generation by Surface Dielectric Barrier Discharge
Authors: Tański Mateusz , Reza Agnieszka , Przytuła Daria , Garasz Katarzyna
Published: June 2023

Surface dielectric barrier discharge (SDBD) is used in a variety of different applications; however, the ozone generated in the discharge can be toxic to people in the vicinity. In this paper, we study the SDBD (using generators with smooth-edge, serrated and thin-wire high-voltage electrodes) in terms of ozone generation. The electrical measurements and the time-resolved plasma imaging revealed differences in the discharge current, dissipated power and plasma morphology for the different types of SDBD generators and showed significant suppression of the streamer formation from the thin-wire electrode. We determined the amount of ozone produced by each generator and found that despite the observed differences in discharge between the generators, the ozone production yield and the maximum volumetric concentration of ozone for all three generators is a linear function of only one parameter—the discharge active power. We also found that the ozone production efficiency of 9.66 g/kWh is constant for all three generators. Our results show that SDBD generators can be safely used in the enclosed space if the SDBD discharge operates with relatively low active power (the SDBD generator working with the active power of 1.7 W did not exceed the ozone concentration of 0.1 ppm in the 60 m3 room).
Robust Optimization Design of the Aerodynamic Shape and External Ballistics of a Pulse Trajectory Correction Projectile
Authors: Xing Bingnan , Du Chengxin , Du Zhonghua , Yang Wenxin
Published: June 2023

To improve the tactical and technical performance of pulse correction projectiles while maintaining stability in uncertain conditions and considering practical engineering constraints, this study performs a multi-objective robust optimization design of the aerodynamic shape and external ballistics of a projectile. The study utilizes an aerodynamic force engineering algorithm and numerical trajectory calculations to obtain the projectile’s performance responses within the Latin hypercube design space. To enhance optimization efficiency, a stochastic Kriging surrogate model is established to capture the inherent uncertainty of limited input data. Ultimately, a Pareto optimal solution for the projectile is obtained using a non-dominated sorting multi-objective sparrow search algorithm. The results of this study demonstrate that the consideration of design uncertainty in the robust optimization of pulse correction projectiles leads to significant enhancements in both lateral correction ability and range while satisfying flight stability requirements. Moreover, when compared to deterministic optimization, the performance variability of the design is markedly improved. This research methodology provides valuable insights for optimizing the performance of pulse correction projectiles.
An Attention-Based CNN-LSTM Method for Effluent Wastewater Quality Prediction
Authors: Li Yue , Kong Bin , Yu Weiwei , Zhu Xingliang
Published: June 2023

Wastewater treatment is a pivotal step in water resource recycling. Predicting effluent wastewater quality can help wastewater treatment plants (WWTPs) establish efficient operations so as to save resources. We propose CNN-LSTM-Attention (CLATT), an attention-based effluent wastewater quality prediction model, which uses a convolutional neural network (CNN) as an encoder and a long short-term memory network (LSTM) as a decoder. An attention mechanism is used to aggregate the information at adjacent sampling times. A sliding window method is proposed to solve the problem of the prediction performance of the model decreasing with time. We conducted the experiment using data collected from a WWTP in Fujian, China. Our results show that the accuracy of prediction is improved, with MSE decreasing by 0.25, MAPE decreasing by 5% and LER decreasing by 7%, after using the sliding window method. Compared with other methods, CLATT achieves the fastest prediction speed among all the methods based on LSTM and the most accurate prediction performance, with MSE increasing up to 0.92, MAPE up to 0.08 and LER up to 0.11. Furthermore, we performed an ablation study on the proposed method to validate the rationality of the major part of the model, and the results show that the LSTM significantly improves the predictive performance of the model, and the CNN and the attention mechanism also improve the accuracy of the prediction.
A Novel Guided Box Filter Based on Hybrid Optimization for Medical Image Denoising
Authors: Gautam Divya , Khare Kavita , Shrivastava Bhavana P.
Published: June 2023

Medical image denoising is a crucial pre-processing task in the medical field to ensure accurate analysis of anomalies or sicknesses in the human body. Digital filters are popular for reducing undesired noise as they provide reliability, high accuracy, and reduced sensitivity to component tolerances compared to analog filters. However, conventional digital filter design approaches lack efficiency in achieving global optimization robustness. To overcome these incapabilities, this paper adopted bio-inspired optimization algorithms to offer viable digital filter designing tools because of their simple implementation and requirement of a few parameters to control their convergence. This research article explores a hybrid strategy that combines a novel guided decimation box filter (GDBF) with a hybrid cuckoo particle swarm optimization (HCPSO) algorithm to design a denoising filter for medical images. It is the first time a decimation box filter has been used for denoising, leading to novelty. The HCPSO algorithm is applied to obtain the filter parameters optimally. Medical images mostly suffer from four types of noises. The performance of the proposed filter is analyzed for these types of noise. To highlight the importance of parameter selection, the results of the proposed method are compared with other recently utilized bio-inspired genetic algorithms, such as PSO (particle swarm optimization), CS (cuckoo search), and FF (firefly). The superiority (potency) of the proposed method has been established by calculating the improvement in quality parameters such as the peak signal-to-noise ratio (PSNR), structure similarity index (SSIM), and feature similarity index (FSIM). The proposed filter achieved the highest PSNR (~35.7 dB), SSIM (~0.95), and FSIM (~0.92) and proved its numerical and visual quality efficacy over state-of-the-art models.
Quasi-Static Lineshape Theory for Rydberg Excitations in High-Density Media
Authors: Scheuing Trevor , Pérez-Ríos Jesús
Published: June 2023

This work presents a theoretical approach for lineshapes of Rydberg excitations in high-density media. In particular, we introduce the quasi-static lineshape theory, leading to a methodic and general approach, and its validity is studied. Next, using 84Sr as a prototypical scenario, we discuss the role of the thermal atoms and core–perturber interactions, generally disregarded in Rydberg physics. Finally, we present a characterization of the role of Rydberg–core perturber interactions based on the density and principal quantum number that, beyond affecting the lineshape, could potentially apply to chemi-ionization reactions responsible for the decay of Rydberg atoms in high-density media.
Involvement of Matrix Metalloproteinases in COVID-19: Molecular Targets, Mechanisms, and Insights for Therapeutic Interventions
Authors: Salomão Rebecca , Assis Victoria , de Sousa Neto Ivo Vieira , Petriz Bernardo , Babault Nicolas , Durigan João Luiz Quaglioti , de Cássia Marqueti Rita
Published: June 2023

MMPs are enzymes involved in SARS-CoV-2 pathogenesis. Notably, the proteolytic activation of MMPs can occur through angiotensin II, immune cells, cytokines, and pro-oxidant agents. However, comprehensive information regarding the impact of MMPs in the different physiological systems with disease progression is not fully understood. In the current study, we review the recent biological advances in understanding the function of MMPs and examine time-course changes in MMPs during COVID-19. In addition, we explore the interplay between pre-existing comorbidities, disease severity, and MMPs. The reviewed studies showed increases in different MMP classes in the cerebrospinal fluid, lung, myocardium, peripheral blood cells, serum, and plasma in patients with COVID-19 compared to non-infected individuals. Individuals with arthritis, obesity, diabetes, hypertension, autoimmune diseases, and cancer had higher MMP levels when infected. Furthermore, this up-regulation may be associated with disease severity and the hospitalization period. Clarifying the molecular pathways and specific mechanisms that mediate MMP activity is important in developing optimized interventions to improve health and clinical outcomes during COVID-19. Furthermore, better knowledge of MMPs will likely provide possible pharmacological and non-pharmacological interventions. This relevant topic might add new concepts and implications for public health in the near future.
Selective Inhibition of Soluble Tumor Necrosis Factor Alters the Neuroinflammatory Response following Moderate Spinal Cord Injury in Mice
Authors: Lund Minna Christiansen , Ellman Ditte Gry , Nielsen Pernille Vinther , Raffaele Stefano , Fumagalli Marta , Guzman Raphael , Degn Matilda , Brambilla Roberta , Meyer Morten , Clausen Bettina Hjelm , Lambertsen Kate Lykke
Published: June 2023

Clinical and animal model studies have implicated inflammation and glial and peripheral immune cell responses in the pathophysiology of spinal cord injury (SCI). A key player in the inflammatory response after SCI is the pleiotropic cytokine tumor necrosis factor (TNF), which exists both in both a transmembrane (tmTNF) and a soluble (solTNF) form. In the present study, we extend our previous findings of a therapeutic effect of topically blocking solTNF signaling after SCI for three consecutive days on lesion size and functional outcome to study the effect on spatio-temporal changes in the inflammatory response after SCI in mice treated with the selective solTNF inhibitor XPro1595 and compared to saline-treated mice. We found that despite comparable TNF and TNF receptor levels between XPro1595- and saline-treated mice, XPro1595 transiently decreased pro-inflammatory interleukin (IL)-1β and IL-6 levels and increased pro-regenerative IL-10 levels in the acute phase after SCI. This was complemented by a decrease in the number of infiltrated leukocytes (macrophages and neutrophils) in the lesioned area of the spinal cord and an increase in the number of microglia in the peri-lesion area 14 days after SCI, followed by a decrease in microglial activation in the peri-lesion area 21 days after SCI. This translated into increased myelin preservation and improved functional outcomes in XPro1595-treated mice 35 days after SCI. Collectively, our data suggest that selective targeting of solTNF time-dependently modulates the neuroinflammatory response by favoring a pro-regenerative environment in the lesioned spinal cord, leading to improved functional outcomes.
Functionality Loss and Recovery Time Models for Structural Elements, Non-Structural Components, and Delay Times to Estimate the Seismic Resilience of Mexican School Buildings
Authors: González Carlos , Niño Mauro , Ayala Gustavo
Published: June 2023

Concerns about prolonged downtime and functionality losses observed after recent seismic events have made it clear that seismic design is heading towards a resilience-based approach. However, there is still currently no clear consensus on how to quantify and interpret resilience. In this document, a probabilistic approach to estimate recovery times and functionality loss in buildings is presented, which allows for the estimation of seismic resilience through consideration of delay times and the behavior of non-structural elements. To achieve these goals, simple models that associate structural response and the resilience parameters (recovery time and functionality) are defined. The proposed approach was implemented in a database for public school buildings in Puebla City, where the expected times and functionality were obtained, thus allowing for quantification of the seismic resilience of each structure. Furthermore, target values for low and high resilience are proposed, which helps to identify the weakest elements in the educative Mexican infrastructure. The results showed that the inclusion of delay times and non-structural elements in resilience quantification is mandatory if an overestimation of resilience values is to be avoided. At the same time, the target values allow for the different structures to be categorized according to the resilience values obtained, finding that a significant portion of Mexican school buildings are underprepared in a resilience context.
Spectroscopic and Crystallographic Characterization of Two Hydrochloride Cathinones: 1-(4-fluoro-3-methylphenyl)-2-(pyrrolidin-1-yl)pentan-1-one (4-F-3-Me-α-PVP) and N-ethyl-2-amino-1-phenylheptan-1-one (N-ethylheptedrone)
Authors: Rojkiewicz Marcin , Kuś Piotr , Kusz Joachim , Książek Maria , Staszek Dorota
Published: June 2023

In this paper, two cathinone derivatives, 4F-3Me-α-PVP and N-ethylheptedrone, seized on the illegal drug market in Poland, were described and characterized by various instrumental analytical methods. The compounds were characterized by electrospray ionization mass spectrometry, high-resolution mass spectrometry, gas chromatography–mass spectrometry, infrared spectroscopy, X-ray crystallography, thermogravimetric analysis, differential scanning calorimetry and nuclear magnetic resonance spectroscopy. The two tested compounds were confirmed as 1-(4-fluoro-3-methylphenyl)-2-(pyrrolidin-1-yl)pentan-1-one and N-ethyl-2-amino-1-phenylheptan-1-one hydrochlorides; both are cathinone derivatives available on the market for new psychoactive substances (NPS). The obtained analytical data should be useful for forensic and toxicological purposes in the rapid and reliable identification of compounds.
Artificial Intelligence-Based Software with CE Mark for Chest X-ray Interpretation: Opportunities and Challenges
Authors: Fanni Salvatore Claudio , Marcucci Alessandro , Volpi Federica , Valentino Salvatore , Neri Emanuele , Romei Chiara
Published: June 2023

Chest X-ray (CXR) is the most important technique for performing chest imaging, despite its well-known limitations in terms of scope and sensitivity. These intrinsic limitations of CXR have prompted the development of several artificial intelligence (AI)-based software packages dedicated to CXR interpretation. The online database “AI for radiology” was queried to identify CE-marked AI-based software available for CXR interpretation. The returned studies were divided according to the targeted disease. AI-powered computer-aided detection software is already widely adopted in screening and triage for pulmonary tuberculosis, especially in countries with few resources and suffering from high a burden of this disease. AI-based software has also been demonstrated to be valuable for the detection of lung nodules detection, automated flagging of positive cases, and post-processing through the development of digital bone suppression software able to produce digital bone suppressed images. Finally, the majority of available CE-marked software packages for CXR are designed to recognize several findings, with potential differences in sensitivity and specificity for each of the recognized findings.
A Systematic Review of INGARCH Models for Integer-Valued Time Series
Authors: Liu Mengya , Zhu Fukang , Li Jianfeng , Sun Chuning
Published: June 2023

Count time series are widely available in fields such as epidemiology, finance, meteorology, and sports, and thus there is a growing demand for both methodological and application-oriented research on such data. This paper reviews recent developments in integer-valued generalized autoregressive conditional heteroscedasticity (INGARCH) models over the past five years, focusing on data types including unbounded non-negative counts, bounded non-negative counts, Z-valued time series and multivariate counts. For each type of data, our review follows the three main lines of model innovation, methodological development, and expansion of application areas. We attempt to summarize the recent methodological developments of INGARCH models for each data type for the integration of the whole INGARCH modeling field and suggest some potential research topics.
How Expert and Inexpert Instructors Talk about Teaching
Authors: Reding Tracie , Moore Christopher
Published: June 2023

Using mixed-method social network analysis, we explored the discussions happening between instructors within a teaching-related network and how instructional expertise correlated with the content of those discussions. Instructional expertise, defined by the extent to which effective teaching practices were implemented, was measured for 82 faculty teaching at a Midwestern research university in the USA using the Faculty Inventory of Methods and Practices Associated with Competent Teaching (F-IMPACT). Eight instructors from this population were interviewed after being selected from a stratified random sample having varied disciplines, positions, years of teaching experience, number of network alters, and quartile F-IMPACT score. Network Canvas was used to design, capture, and export network data during the interview process, and a deductive qualitative analysis approach was used for coding and analysis. In general, expert instructors had larger networks that also consisted of expert alters and greater frequency of discussions throughout the semester (both formal and informal) and participated in discussions centered around best practices and education research. Inexpert instructors had smaller teaching networks that consisted of other inexpert instructors, lower frequency of interactions, and had discussions that centered around sharing course-specific, surface-level advice.
Optimizing Health Professions Education through a Better Understanding of “School-Supported Clinical Learning”: A Conceptual Model
Authors: Stoffels Malou , Peerdeman Saskia M. , Daelmans Hester E. M. , van der Burgt Stephanie M. E. , Kusurkar Rashmi A.
Published: June 2023

Interventions connecting school and clinical practice can align requirements and enhance learning outcomes. Current models and theories of clinical learning leave gaps in our knowledge about how learning processes and outcomes can be optimized by schools. In this paper, we discuss findings about threats and opportunities in the use of school standards, tools, and support in clinical learning, including underlying mechanisms, in the context of nursing education. Opportunities include competency frameworks that can challenge students to push their limits despite a task-oriented ward culture. Assignments and tools can deepen students’ understanding of patient care, help them compare different experiences and stimulate self-regulated learning. Threats include rigid performance criteria that guide students’ selection of learning opportunities, extensive written formats, and individualization of self-regulated learning. These threats can lead to added workload and disengagement. Based on the critically constructed argument that the role of schools in clinical learning should be acknowledged in the literature, we present a conceptual model to do so. The use of this model provides design principles for learning environments at the interface of school and practice within health professions education. Eventually, learning outcomes can be achieved efficiently without unnecessary interference with students’ engagement in patient care and student-supervisor interactions.
Evaluation of IoT-Based Smart Home Assistance for Elderly People Using Robot
Authors: Alshdadi Abdulrahman A.
Published: June 2023

In the development of Internet-of-things (IoT)-based technology, there is a pre-programmed robot called Cyborg which is used for assisting elderly people. It moves around the home and observes the surrounding conditions. The Cyborg is developed and used in the smart home system. The features of a smart home system with IoT technology include temperature control, lighting control, surveillance, security, smart electricity, and water sensors. Nowadays, elderly people may not be able to maintain their homes appropriately and may feel uncomfortable performing day-to-day activities. Therefore, Cyborg can be used to carry out the activities of elderly people. Such activities include switching off unnecessary lights, watering plants, gas control, monitoring intruders or unknown persons, alerting elderly people in emergency situations, etc. These activities are controlled by web-based platforms as well as smartphone applications. The issues with the existing algorithms include that they are inefficient, require a long time for implementation, and have high storage space requirements. This paper proposes the k-nearest neighbors (KNN) with an artificial bee colony (ABC) algorithm (KNN-ABC). In this proposed work, KNN-ABC is used with wireless sensor devices for perceiving the surroundings of the smart home. This work implements the automatic control of electronic appliances, alert signal processors, intruder detection, and performs day-to-day activities automatically in an efficient way. GNB for intruder detection in the smart home environment system using the Cyborg human intervention robot achieved an accuracy rate of 88.12%, the Artificial Bee Colony algorithm (ABC) achieved 90.12% accuracy on the task of power saving in smart home electronic appliances, the KNN technique achieved 91.45% accuracy on the task of providing a safer pace to the elderly in the smart home environment system, and our proposed KNN-ABC system achieved 93.72%.
Hardware Implementation of an Approximate Simplified Piecewise Linear Spiking Neuron
Authors: Liu Hao , Wang Mingjiang , Yao Longxin , Liu Ming
Published: June 2023

Artificial intelligence has revolutionized image and speech recognition, but the neural network fitting method has limitations. Neuromorphic chips that mimic biological neurons can better simulate the brain’s information processing mechanism. As the basic computing component of the new neuromorphic network, the new neural computing unit’s design and implementation have important significance; however, complex dynamical features come with a high computational cost: approximate computing has unique advantages, in terms of optimizing the computational cost of neural networks, which can solve this problem. This paper proposes a hardware implementation of an approximate spiking neuron structure, based on a simplified piecewise linear model (SPWL), to optimize power consumption and area. The proposed structure can achieve five major neuron spiking generation patterns. The proposed design was synthesized and compared to similar designs, to evaluate its potential advantages and limitations. The results showed that the approximate spiking neuron had the lowest computational cost and the fastest computation speed. A typical spiking neural network was constructed, to test the usability of the SPWL model. The results showed that the proposed approximate spiking neuron could work normally in the spiking neural network, and achieved an accuracy of 94% on the MNIST dataset.
Modelling Electro-Mechanical Behaviour of an XLPE Insulation Layer for Hi-Voltage Composite Power Cables: Effect of Voids on Onset of Coalescence
Authors: Miceli Michele , Carvelli Valter , Drissi-Habti Monssef
Published: June 2023

The harshness of the submarine environment represents a serious threat for immersed high voltage power cables, extensively used for offshore wind farms, which in turn are supposed to last for at least 20 years for their total investment to be economically viable. The Crosslinked Polyethylene (XLPE) used for the insulating layer of the cables may suffer different degradation phenomena, leading to unexpected breakdowns and rises in costs. In this work, numerical simulations have been developed to study the mechanisms by which micrometric pores inside XLPE can enlarge and coalesce (namely, water treeing) when the insulation is subjected to the intense electric field generated by hi-voltage wires. The study aim is to predict material plasticization next to voids, which is supposed to represent the onset of coalescence of neighboring pores. A microscale-level finite element coupled electro-mechanics model has been developed to describe the interactions between the intense electric fields and the subsequent Maxwell stresses in a dielectric. The roles of different influencing parameters such as distance, relative volumes, and the shape of two neighboring voids in a representative unit volume are considered. Finally, the behavior of a generic microstructure characterized by randomly distributed voids immersed in an electric field is simulated.
The Reliability and Exploitation Analysis Method of the ICT System Power Supply with the Use of Modelling Based on Rough Sets
Authors: Stawowy Marek , Rosiński Adam , Paś Jacek , Duer Stanisław , Harničárová Marta , Perlicki Krzysztof
Published: June 2023

The article describes a new approach to the reliability–exploitation analysis of the critical information and communications technology (ICT) system power supply. A classic approach based on statistical indicators and a new one founded on uncertainty modelling based on the rough set method is presented. The main advantage of the uncertainty modelling approach is the simplification of the calculations and the fact that, unlike statistical analysis, uncertainty modelling does not require complete information on the used data sets. An extensive study of world publications was carried out, proving that this is an entirely innovative approach to solving the problem of reliability and exploitation analysis. Calculations, analyses and syntheses are also exhibited in a specific example. A sample of the ICT system power supply was simulated, and the simulation results are shown. The simulations were prepared by one of the co-authors for the purposes of this article.
Influence of Cooling Management to Transformer Efficiency and Ageing
Authors: Janic Zarko , Gavrilov Nebojsa , Roketinec Ivica
Published: June 2023

Transformer efficiency is a key concern for both transformer operators and regulators, particularly with regards to new transformers. Cooling is a critical factor in preventing overheating and controlling the ageing of transformer insulation. This paper aims to analyse how different cooling setups can influence efficiency. Transformer losses depend on the winding temperature, which is affected by load, ambient temperature, and cooling power. In this study, we will take all of these factors into consideration to examine their impact on transformer losses. Using a 520 MVA transformer as an example, we will calculate the loss levels under different realistic ambient temperature and load profiles. We will also apply different cooling system settings to determine the optimization possibilities. Our calculations will consider different turn-on temperatures of the fans and cooling stages and will use steady state calculations over a period of 12 months. Additionally, a novel approach to control cooling by using the loading of the transformer is present, as are the possibilities of using variable speed fans. Finally, we will estimate the influence of cooling settings on transformer ageing by examining their impact on temperature.
Experimental Development of the Horizontal Drain Water Heat Recovery Unit
Authors: Kordana-Obuch Sabina , Starzec Mariusz
Published: June 2023

The increase in energy demand, the scarcity of resources, as well as the adverse environmental impact of burning fossil fuels make it necessary to diversify the energy sources used. This also applies to the residential sector, which accounts for a significant proportion of global energy consumption. Particular attention should be paid to water heating, as the importance of this process in the energy balance of buildings is steadily increasing. One of the methods used to decrease energy consumption for heating water is to recover heat from greywater. However, commercially available horizontal drain water heat recovery (DWHR) units are characterized by low effectiveness, which creates a need for further research to improve it. The aim of the paper was to evaluate the possibility of improving the effectiveness of a circular horizontal DWHR unit through the use of baffles. Six different baffle models for installation in the greywater section of the heat exchanger were analyzed. The tests were conducted under the assumption of the installation of the DWHR unit on the horizontal shower waste pipe. They showed that the effectiveness of the unit equipped with baffles was higher by several to as much as 40% compared to the DWHR unit without baffles. This is tantamount to an increase in annual financial savings resulting from greywater heat recovery, as well as a reduction in CO2 emissions into the atmosphere. However, it was not possible to clearly identify the optimum baffle model. In any case, the selection should consider the hydraulic conditions in the heat exchanger before installing the baffles. The results can provide guidance for companies interested in bringing new equipment and technologies to the market.