bluuebunny/crossref_metadata_2025 huggingface dataset:
Asociación entre lengua materna originaria con el nivel educativo alcanzado en la población peruana, 2022
Authors: Guevara-Tirado Alberto , Mendoza-Merino Marisol
Published: August 2023

El objetivo fue determinar si el tipo de lengua materna practicado en la población peruana está asociado al nivel educativo, nivel de alfabetización, edad, sexo y dominio geográfico. Se realizó un estudio descriptivo, retrospectivo, transversal proveniente de la encuesta nacional de hogares-2022. El muestreo fue probabilístico, de áreas, estratificado. Se realizó la prueba de Chi-cuadrado. Las variables fueron: lengua materna, edad, nivel educativo, dominio geográfico, sexo y alfabetización. 4.2% y 0.5% de hablantes de lenguas originarias alcanzaron el nivel universitario y postgrado, respectivamente, en contraste con los hablantes de español con un 12.4% y 1.3% respectivamente. 65.2% de practicantes de lenguas originarias pertenecen a la Sierra, 48.7% de hablantes de lenguas originarias no sabe leer ni escribir, los adolescentes son el grupo etario que más habla español mientras que los adultos intermedios y mayor predominan hablan principalmente lenguas originarias. Se halló asociación estadísticamente significativa en todos los grupos (p=0.000) a excepción de con el sexo (p=0,126). En conclusión, el tipo de lengua materna está asociado con el nivel educativo alcanzado y otras barreras sociodemográficas en la población peruana, Es preciso reducir de forma más comprometida las brechas de desigualdad de oportunidades en educación en la población afectada.
Teoría social del riesgo, una deliberación desde los estudios urbanos: relación sociedad y territorio
Authors: García-Hernández Dalila , Adame-Martínez Salvador , Pérez-Ramírez. Carlos A. , Álvarez-Arteaga Gustavo
Published: August 2023

Los cambios que se presentan en la sociedad contemporánea manifiestan la complejidad de sus construcciones, reflejadas en los diferentes riesgos, consecuencia de las acciones humanas y el manejo de los recursos naturales, es por ello, que el objetivo del artículo es analizar la teoría social del riesgo considerando la relación sociedad y territorio en el marco de los estudios urbanos. Se presenta en una discusión teórica conceptual desde el análisis crítico de diversos autores cobrando relevancia al mostrar la manera en la cual las acciones generan una transformación a través de la creación y reproducción de las situaciones que se construyen bajo los escenarios de vulnerabilidad en el territorio considerando la relación con la sociedad. Se concluye que, respecto a los fenómenos sociales y sus componentes territoriales, la relación sociedad y territorio responde a una dinámica en los condicionantes del desarrollo de la teoría social del riesgo, facilitando el entendimiento del actuar humano.
Protein structural and sequence analysis of human ACE2 using prediction and modeling bioinformatics tools for diagnostics biomarkers and drug design features: an opinion study path
Authors: Ozurumba-Dwight Leo , Dalton Dalton , Ebenso Eno , Tonukari Nyerhowo , Tebo to Anne , Ogbonna Chinedu , Enwerre Okezie , Govender Algasan , Iyevhobu Kenneth , Ndams Iliya , Bello Mohammad , Yinusa Titus , Okpoghono Joel , Obeagu Emmanuel , Okeke Malachy , Muller Claude , Osuya Innocent
Published: August 2023

Angiotensin converting enzyme-2 receptor (ACE2) present on human cell membrane surfaces is a critical receptor for binding of SARS-CoV-2 to invade cells. Severe burden of recent COVID-19 pandemic was of global public health importance. Using bioinformatics tools, protein sequence and structural features of ACE2 protein can be obtained. Protein sequences can be compared with structures of ACE2 proteins from same individuals (or patients) of different clinical status. This can either be from data obtained from disease states or already deposited annotated data. Then assess for effectiveness of a pool of bio-molecular attributes such structural neighbor profiles which help describe micro-environment of single amino polymorphisms (SAPs). Then engage predictive and modeling tools to predict key mutational loci- particularly involving SAPs and their functions in relation to disease states. Generated data can contribute to ontology, screens to identify biomarkers and open up paths to development of research protocols in therapeutics and diagnostics.
Probiotic dairy dessert from camel milk – A review
Authors: Darani Kianoush Khosravi , Jahadi Mahshid , Tripathi Abhishek Dutt , Nandan Alisha , Paul Veena , Chakraborty Adrija , Verma Tarun , Agarwal Aparna
Published: August 2023

A staple food in many regions of the world, especially in the arid and semi-arid regions, is camel’s milk. Health-promoting ingredients found in camel’s milk include lactoferrin, zinc, lactoactive peptides, and mono- and polyunsaturated fatty acids. Some significant human ailments, such as TB, asthma, gastrointestinal disorders, and jaundice, may be treated with the use of these drugs. Compared to cow’s milk, camel’s milk has amore varied composition. In camels, nutrition, breed, age, and lactation stage have a greater impact on milk composition. The percentage of components in camel’s milk varies greatlydepending on the region and season. These whey proteins have distinctive qualities, such as physical, chemical, physiological, functional, and technical traits that are advantageous in the food application, in addition to their high nutritional value. Camel’s milk proteins are hydrolyzed to create bioactive peptides, which have an impact on the body’s primary organ systems and provide them physiological activities. The antidiabetic, antibacterial, antioxidant, and anti-cholesterol properties of camel milk are highlighted in this article
Prevalence and risk factors for depression and anxiety in patients with nasolacrimal duct obstruction
Authors: Guo Yining , Wu Defu , Jin Yu , Tian Yanjie , Li Xuemin
Published: August 2023

Objective

To investigate the prevalence and risk factors for depression and anxiety in patients with nasolacrimal duct obstruction (NLDO).

Methods

We conducted a telephone-based survey of patients with NLDO who underwent dacryocystorhinostomy (DCR) at the Department of Ophthalmology of Peking University Third Hospital in China between January 2016 and January 2021. Depression and anxiety were assessed with the PHQ-9 (range 0–25) and STAI (range 20–80) scales. PHQ-9 ≥ 5 and STAI ≥ 55 were considered clinically significant. Logistic regression and linear regression were performed to determine the factors related to depression and anxiety.

Results

Of 565 patients approached, 344 (60.9%) completed the survey. A total of 13.1% of patients had mild-severe depression and 63.4% had severe anxiety. Univariate logistic regression revealed that hypertension, dry eye, and cataract were associated with mild to severe depression (P = 0.018, 0.045, 0.035, respectively). Dry eye was associated with severe anxiety (P = 0.007). Univariate linear regression revealed that male and income levels were significantly negatively correlated with PHQ-9 scores (P = 0.011, 0.010, respectively). Hypertension and dry eye were significantly positively correlated with PHQ-9 scores (P = 0.030, P < 0.001, respectively). Male, income levels, and educational levels were significantly negatively correlated with STAI scores (P = 0.022, P < 0.001, P = 0.005, respectively). Dry eye was significantly positively correlated with STAI scores (P < 0.001).

Conclusion

Prevalence of depression and anxiety disorders was relatively high among NLDO patients. Our results demonstrate the importance of depression and anxiety screening and psychosocial support for patients with NLDO, which can improve their quality of life and compliance with medical appointments.
Ensemble Transfer Learning for Distinguishing Cognitively Normal and Mild Cognitive Impairment Patients Using MRI
Authors: Grover Pratham , Chaturvedi Kunal , Zi Xing , Saxena Amit , Prakash Shiv , Jan Tony , Prasad Mukesh
Published: August 2023

Alzheimer’s disease is a chronic neurodegenerative disease that causes brain cells to degenerate, resulting in decreased physical and mental abilities and, in severe cases, permanent memory loss. It is considered as the most common and fatal form of dementia. Although mild cognitive impairment (MCI) precedes Alzheimer’s disease (AD), it does not necessarily show the obvious symptoms of AD. As a result, it becomes challenging to distinguish between mild cognitive impairment and cognitively normal. In this paper, we propose an ensemble of deep learners based on convolutional neural networks for the early diagnosis of Alzheimer’s disease. The proposed approach utilises simple averaging ensemble and weighted averaging ensemble methods. The ensemble-based transfer learning model demonstrates enhanced generalization and performance for AD diagnosis compared to traditional transfer learning methods. Extensive experiments on the OASIS-3 dataset validate the effectiveness of the proposed model, showcasing its superiority over state-of-the-art transfer learning approaches in terms of accuracy, robustness, and efficiency.
An Overview of Privacy Dimensions on the Industrial Internet of Things (IIoT)
Authors: Demertzi Vasiliki , Demertzis Stavros , Demertzis Konstantinos
Published: August 2023

The rapid advancements in technology have given rise to groundbreaking solutions and practical applications in the field of the Industrial Internet of Things (IIoT). These advancements have had a profound impact on the structures of numerous industrial organizations. The IIoT, a seamless integration of the physical and digital realms with minimal human intervention, has ushered in radical changes in the economy and modern business practices. At the heart of the IIoT lies its ability to gather and analyze vast volumes of data, which is then harnessed by artificial intelligence systems to perform intelligent tasks such as optimizing networked units’ performance, identifying and correcting errors, and implementing proactive maintenance measures. However, implementing IIoT systems is fraught with difficulties, notably in terms of security and privacy. IIoT implementations are susceptible to sophisticated security attacks at various levels of networking and communication architecture. The complex and often heterogeneous nature of these systems makes it difficult to ensure availability, confidentiality, and integrity, raising concerns about mistrust in network operations, privacy breaches, and potential loss of critical, personal, and sensitive information of the network's end-users. To address these issues, this study aims to investigate the privacy requirements of an IIoT ecosystem as outlined by industry standards. It provides a comprehensive overview of the IIoT, its advantages, disadvantages, challenges, and the imperative need for industrial privacy. The research methodology encompasses a thorough literature review to gather existing knowledge and insights on the subject. Additionally, it explores how the IIoT is transforming the manufacturing industry and enhancing industrial processes, incorporating case studies and real-world examples to illustrate its practical applications and impact. Also, the research endeavors to offer actionable recommendations on implementing privacy-enhancing measures and establishing a secure IIoT ecosystem.
Plant Protection and Fertilizer Use Efficiency in Farms in a Context of Overinvestment: A Case Study from Poland
Authors: Zmyślona Jagoda , Sadowski Arkadiusz , Genstwa Natalia
Published: August 2023

The purpose of this study was to determine the relationship between plant protection and fertilizer use efficiency, on one side, and overinvestment in Polish agriculture, on the other. This is an important topic because of a number of essential issues, such as the concern for the environment, the development of sustainable agriculture, or the need to ensure food security which can only be achieved by keeping production volumes at least at the same level. Reconciling these goals often requires investment which, however, involves the risk of overinvesting, i.e., a situation where the value of assets grows without a proportional increment in labor productivity. This paper uses the author’s own method of farm classification by overinvestment level. The study revealed some differences in the cost intensity of fertilizing and using plant-protection products between investment levels. The most rational results were found in farms at optimum investment levels, whereas the greatest cost intensity was recorded in farms affected by overinvestment.
Instance Segmentation of Lotus Pods and Stalks in Unstructured Planting Environment Based on Improved YOLOv5
Authors: Lu Ange , Ma Lingzhi , Cui Hao , Liu Jun , Ma Qiucheng
Published: August 2023

Accurate segmentation of lotus pods and stalks with pose variability is a prerequisite for realizing the robotic harvesting of lotus pods. However, the complex growth environment of lotus pods causes great difficulties in conducting the above task. In this study, an instance segmentation model, LPSS-YOLOv5, for lotus pods and stalks based on the latest YOLOv5 v7.0 instance segmentation model was proposed. The CBAM attention mechanism was integrated into the network to improve the model’s feature extraction ability. The scale distribution of the multi-scale feature layer was adjusted, a 160 × 160 small-scale detection layer was added, and the original 20 × 20 large-scale detection layer was removed, which improved the model’s segmentation accuracy for small-scale lotus stalks and reduced the model size. On the medium-large scale test set, LPSS-YOLOv5 achieved a mask mAP0.5 of 99.3% for all classes. On the small-scale test set, the mAP0.5 for all classes and AP0.5 for stalks were 88.8% and 83.3%, which were 2.6% and 5.0% higher than the baseline, respectively. Compared with the mainstream Mask R-CNN and YOLACT models, LPSS-YOLOv5 showed a much higher segmentation accuracy, speed, and smaller size. The 2D and 3D localization tests verified that LPSS-YOLOv5 could effectively support the picking point localization and the pod–stalk affiliation confirmation.
Germination Response of Different Castor Bean Genotypes to Temperature for Early and Late Sowing Adaptation in the Mediterranean Regions
Authors: Cafaro Valeria , Alexopoulou Efthymia , Cosentino Salvatore Luciano , Patanè Cristina
Published: August 2023

Germination of castor seeds of seven dwarf hybrid genotypes, compared to a ‘Local’ genotype, selected from a Tunisian population by the University of Catania well adapted to the Mediterranean environment, were studied at six different temperatures (8, 12, 16, 25, 32, and 40 °C). The results indicate that the optimal temperature (25 °C) and near-optimal temperature (32 °C) are the best temperatures for ensuring castor germination (final germination percentage (FGP) ≥ 82.81%). Furthermore, these temperatures positively influenced the vigour index (VI) and the radicle elongation. At a temperature of 8 °C, no germination occurred, while temperatures of 12 and 40 °C negatively affected the seed germination, which, in some genotypes, was null or negligible (<21.25%). A temperature of 16 °C allowed good results to be reached for the FGP and the other considered parameters. Overall, the dwarf hybrids performed better at high temperatures than at low temperatures, thus, making them suitable for late sowings, with the exception of the genotype ‘C1020’, which resulted the best performance at 16 and 40 °C, being suitable for both early and late sowings. On the other hand, the ‘Local’ castor genotype, being the best-performing genotype at 12 and 16 °C, and the most tolerant to low temperature (base temperature (Tb) 12.1 °C), could be used in the early sowing in spring.
Straw Return Decomposition Characteristics and Effects on Soil Nutrients and Maize Yield
Authors: Yang Yun , Long Yun , Li Shiwei , Liu Xiaohong
Published: August 2023

Straw return benefits soil nutrient circulation and avoids the environmental pollution caused by incineration. The straw return effect is determined by many factors, such as the returning mode and tillage method. To find the most suitable straw return mode in the hilly areas of south China, we conducted experiments with preceding maize straw in Nanchong (Sichuan Province, China) for three years. Five treatments were tested: (A) rotary tillage without straw return (RT), (B) crushed straw return with rotary tillage (CRT), (C) crushed straw return without rotary tillage (CSR), (D) whole straw return with rotary tillage (WRT), and (E) whole straw return without rotary tillage (WSR). The results indicated that CRT had the fastest decomposition rate, followed by CSR. Moreover, CRT had the fastest nutrient release rates for nitrogen, phosphorus, potassium, cellulose, hemicellulose, and lignin, as well as the highest maize yield (6.62% higher than RT). CRT increased the content of organic matter, total nitrogen, total phosphorus, and total potassium in the soil, as well as improved the soil pH. Furthermore, the numbers of bacteria, Actinomycetes, and fungi in the soil under CRT, CSR, and WSR treatments were higher than those under the other two treatments. This study has important reference value for exploring the most favourable straw return method for improving farmland fertility.
Back to the Future: What Is Trending on Precision Agriculture?
Authors: Andujar Dionisio
Published: August 2023

The Industrial Revolution changed the way of cropping with new machinery [...]
Selenium and Iodine Biofortification Interacting with Supplementary Blue Light to Enhance the Growth Characteristics, Pigments, Trigonelline and Seed Yield of Fenugreek (Trigonella foenum-gracum L.)
Authors: Ramezani Sadrollah , Yousefshahi Behnaz , Farrokhzad Yusuf , Ramezan Dariush , Zargar Meisam , Pakina Elena
Published: August 2023

Fenugreek (Trigonella foenum-graecum) is an annual plant belonging to the family Fabaceae and has fodder, medicinal and spice uses, and is also used as an organic fertilizer. A total of 18 treatments including the combination of two light environments (with and without supplementary blue light), three concentrations of potassium iodate (0, 2 and 4 mg L−1) and four concentrations of sodium selenate (0, 2 and 4 mg L−1) were organized in a three-way factorial experiment to evaluate the growth characteristics, pigments, trigonelline and seed yield of fenugreek in a greenhouse. The application of 4 mg L−1 of Se resulted in the highest carotenoid, anthocyanin, plant length, fresh weight, chlorophyll and relative water content. The fresh and dry weight of the shoot and the anthocyanin increased with the 2 h supplementation of sunlight with a blue spectrum; however, the fresh root decreased. The interaction of blue light with 0 mg L−1 of Se significantly reduced the plant length. The content of trigonelline was significantly improved with the application of blue light supplementation without negatively affecting the seed yield. In general, 2 h supplementing of sunlight with blue light and feeding with 4 mg L−1 of selenium and iodine are recommended to improve various traits, including trigonelline content.
PsFT, PsTFL1, and PsFD Are Involved in Regulating the Continuous Flowering of Tree Peony (Paeonia × lemoinei ‘High Noon’)
Authors: Zhang Limei , Cheng Fangyun , Huang He , Geng Ziwen , He Chaoying
Published: August 2023

Tree peonies are an economically important crop with flowers of high ornamental value. Most tree peony cultivars in gardens are once-flowering, and the continuous flowering (CF) trait has been revealed only in a few tree peony cultivars, such as ‘High Noon’ (‘HN’). However, the molecular mechanism underlying its CF remains unclear. Here, we demonstrated that PsTFL1 functions as a floral inhibitor via the ectopic expression of PsTFL1 in transgenic Arabidopsis thaliana plants. Our findings suggest that PsFT and PsTFL1 interact with PsFD, and the detected interactions may occur in the nucleus. Compared with the non-CF variety, the gene expression patterns of PsFT, PsTFL1, and PsFD during the flower development indicate that these three genes may be related to the CF habit in tree peony ‘HN’. These findings will aid future investigations of CF behavior and promote the breeding of tree peonies and other perennial woody plants.
Polymorphisms at Candidate Genes for Fat Content and Fatty Acids Composition: Effects on Sheep Milk Production and Fatty Acid Profile Using Two Dietary Supplementations
Authors: Tumino Serena , Bognanno Matteo , Chessari Giorgio , Tolone Marco , Bordonaro Salvatore , Mangano Fabrizio , Marletta Donata , Avondo Marcella
Published: August 2023

The nutritional value of sheep’s milk and its derivatives is influenced by the lipid fraction, which is affected by diet and genetics. This study aimed to explore the genetic variations in the DGAT1 and SCD genes and assessed the impact of the DGAT1 genotype on milk quality in Valle del Belìce sheep, considering diet supplementation with carob pulp and barley grain. Among the potentially polymorphic sites, only DGAT1 g.127 C > A and SCD g.87 C > A showed variability. The DGAT1 genotype did not significantly impact milk yield and composition, except for higher urea content in the CA genotypes than in the CC ones. Carob pulp increased the milk fat content compared to barley grain. Genetic variation in DGAT1 was associated with changes in the milk fatty acid profile; specifically, the CA genotype exhibited higher levels of short-chain fatty acids and lower levels of polyunsaturated fatty acids compared to the CC genotype. Carob pulp supplementation increased saturated fatty acids and reduced unsaturated fractions, leading to milk with higher atherogenic and thrombogenic indices. No significant interaction was found between genotype and diet. This study provides insights into the genetic and dietary factors influencing sheep’s milk composition. Further research is needed to understand the impact of these genetic variations on milk production and composition, as well as to determine optimal levels of carob pulp for improving fat percentage and promoting sustainable sheep breeding practices.
The Effects of Acute Exposure to Ammonia on Oxidative Stress, Hematological Parameters, Flesh Quality, and Gill Morphological Changes of the Large Yellow Croaker (Larimichthys crocea)
Authors: Guo Meijie , Xu Zhenkun , Zhang Hongzhi , Mei Jun , Xie Jing
Published: August 2023

Ammonia is considered to be the major chemical pollutant causing fish poisoning in aquaculture. This research aimed to evaluate the impact of acute ammonia exposure on the large yellow croaker’s meat quality, gill morphology, liver oxidative stress, and hematological parameters. The fish were exposed to total ammonia nitrogen concentrations of 0, 2.96, 5.92, and 8.87 mg/L for 48 h, respectively. The findings demonstrated that all ammonia-exposed fish had higher liver lactate dehydrogenase and glutamic oxalate transaminase activities. The glucose, blood urea nitrogen, and creatinine levels in 8.87 mg/L total ammonia nitrogen (TAN) were higher than other samples. The total protein, albumin, and triglyceride levels in serum decreased significantly in ammonia-exposed samples. After 48 h of ammonia exposure, superoxide dismutase activities showed a 76.1%, 118.0%, and 156.8% increase when fish were exposed to 2.96, 5.92, and 8.87 mg/L TAN, respectively. Catalase activities and glutathione contents were considerably higher (p < 0.05) in all ammonia-treated samples compared to 0 mg/L TAN. The ammonia-treated gill lamellae become thicker, shorter, and curved. Additionally, the ammonia exposure resulted in the accumulation of free amino acids and the loss of nucleotides. The inosine monophosphate and adenosine monophosphate contents in the flesh were decreased after 12 h of exposure to 2.96, 5.92, and 8.87 mg/L ammonia compared to the control group. Overall, large yellow croakers exposed to ammonia for 6 h presented not only changes in serum composition but also oxidative stress, liver and gill tissue damage and flesh quality deterioration.
Breeding Substrate Containing Distillation Residues of Mediterranean Medicinal Aromatic Plants Modulates the Effects of Tenebrio molitor as Fishmeal Substitute on Blood Signal Transduction and WBC Activation of Gilthead Seabream (Sparus aurata)
Authors: Antonopoulou Efthimia , Kolygas Markos , Panteli Nikolas , Gouva Evangelia , Kontogeorgiou Panagiota , Feidantsis Konstantinos , Chatzopoulos Achilleas , Bitchava Konstantina , Zacharis Christos , Bonos Eleftherios , Giannenas Ilias , Skoufos Ioannis , Andreadis Stefanos S. , Skoulakis Georgios , Athanassiou Christos G. , Nathanailides Cosmas
Published: August 2023

This work assesses the dietary use of two insect meals of Tenebrio molitor (TM) larvae reared in conventional (TM-10) or MAP-enriched substrates (MAP-TM-10) as fish meal replacements (10%) in the diets of gilthead seabream (Sparus aurata). Fish (n = 4500; 207.19 ± 1.47 g) were divided into three groups with triplicates: control (fed conventional diet), TM-10, and MAP-TM-10 groups. The fish were reared in floating cages for 12 weeks and the dietary effects on white blood cell activation, heat shock proteins, MAPKs, and apoptosis of the fish were evaluated. The MAP-TM-10 group exhibited the highest eosinophilic induction. Phosphorylated levels of p38 MAPK, p44/42 MAPK, HSP70, and HSP90 increased in the TM-10 and MAP-TM-10 groups. In terms of apoptosis, Bax levels were lower in the TM groups compared to the control, and the MAP-TM-10 group showed even lower levels than the TM-10 group. Bcl-2 levels increased in the TM-10 group compared to the control, and further increased in the MAP-TM-10 group. The Bax/Bcl-2 ratio, an apoptosis indicator, decreased in the TM groups, with the MAP-TM-10 group showing a further decrease compared to TM-10. These findings suggest that insects’ breeding substrate being enriched with MAPs modulated the effect of TM on cellular stress and apoptosis.
Mastitis in Dairy Cattle: On-Farm Diagnostics and Future Perspectives
Authors: Tommasoni Chiara , Fiore Enrico , Lisuzzo Anastasia , Gianesella Matteo
Published: August 2023

Mastitis is one of the most important diseases in dairy cattle farms, and it can affect the health status of the udder and the quantity and quality of milk yielded. The correct management of mastitis is based both on preventive and treatment action. With the increasing concern for antimicrobial resistance, it is strongly recommended to treat only the mammary quarters presenting intramammary infection. For this reason, a timely and accurate diagnosis is fundamental. The possibility to detect and characterize mastitis directly on farm would be very useful to choose the correct management protocol. Some on-field diagnostic tools are already routinely applied to detect mastitis, such as the California Mastitis Test and on-farm culture. Other instruments are emerging to perform a timely diagnosis and to characterize mastitis, such as Infra-Red Thermography, mammary ultrasound evaluation and blood gas analysis, even if their application still needs to be improved. The main purpose of this article is to present an overview of the methods currently used to control, detect, and characterize mastitis in dairy cows, in order to perform a timely diagnosis and to choose the most appropriate management protocol, with a specific focus on on-farm diagnostic tools.
Artificial Intelligence to Improve Antibiotic Prescribing: A Systematic Review
Authors: Amin Doaa , Garzόn-Orjuela Nathaly , Garcia Pereira Agustin , Parveen Sana , Vornhagen Heike , Vellinga Akke
Published: August 2023

Introduction: The use of antibiotics leads to antibiotic resistance (ABR). Different methods have been used to predict and control ABR. In recent years, artificial intelligence (AI) has been explored to improve antibiotic (AB) prescribing, and thereby control and reduce ABR. This review explores whether the use of AI can improve antibiotic prescribing for human patients. Methods: Observational studies that use AI to improve antibiotic prescribing were retrieved for this review. There were no restrictions on the time, setting or language. References of the included studies were checked for additional eligible studies. Two independent authors screened the studies for inclusion and assessed the risk of bias of the included studies using the National Institute of Health (NIH) Quality Assessment Tool for observational cohort studies. Results: Out of 3692 records, fifteen studies were eligible for full-text screening. Five studies were included in this review, and a narrative synthesis was carried out to assess their findings. All of the studies used supervised machine learning (ML) models as a subfield of AI, such as logistic regression, random forest, gradient boosting decision trees, support vector machines and K-nearest neighbours. Each study showed a positive contribution of ML in improving antibiotic prescribing, either by reducing antibiotic prescriptions or predicting inappropriate prescriptions. However, none of the studies reported the engagement of AB prescribers in developing their ML models, nor their feedback on the user-friendliness and reliability of the models in different healthcare settings. Conclusion: The use of ML methods may improve antibiotic prescribing in both primary and secondary settings. None of the studies evaluated the implementation process of their models in clinical practices. Prospero Registration: (CRD42022329049).
Role of Hydrogen Sulfide in Inflammatory Bowel Disease
Authors: Stummer Nathalie , Feichtinger René G. , Weghuber Daniel , Kofler Barbara , Schneider Anna M.
Published: August 2023

Hydrogen sulfide (H2S), originally known as toxic gas, has now attracted attention as one of the gasotransmitters involved in many reactions in the human body. H2S has been assumed to play a role in the pathogenesis of many chronic diseases, of which the exact pathogenesis remains unknown. One of them is inflammatory bowel disease (IBD), a chronic intestinal disease subclassified as Crohn’s disease (CD) and ulcerative colitis (UC). Any change in the amount of H2S seems to be linked to inflammation in this illness. These changes can be brought about by alterations in the microbiota, in the endogenous metabolism of H2S and in the diet. As both too little and too much H2S drive inflammation, a balanced level is needed for intestinal health. The aim of this review is to summarize the available literature published until June 2023 in order to provide an overview of the current knowledge of the connection between H2S and IBD.
Effect of Dietary Supplementation with a Mixture of Natural Antioxidants on Milk Yield, Composition, Oxidation Stability and Udder Health in Dairy Ewes
Authors: Karageorgou Agori , Tsafou Maria , Goliomytis Michael , Hager-Theodorides Ariadni , Politi Katerina , Simitzis Panagiotis
Published: August 2023

Due to the limitations in the use of antibiotic agents, researchers are constantly seeking natural bioactive compounds that could benefit udder health status but also milk quality characteristics in dairy animals. The aim of the current study was therefore to examine the effects of a standardized mixture of plant bioactive components (MPBC) originated from thyme, anise and olive on milk yield, composition, oxidative stability and somatic cell count in dairy ewes. Thirty-six ewes approximately 75 days after parturition were randomly allocated into three experimental treatments, which were provided with three diets: control (C); without the addition of the mixture, B1; supplemented with MPBC at 0.05% and B2; supplemented with rumen protected MPBC at 0.025%. The duration of the experiment was 11 weeks, and milk production was weekly recorded, while individual milk samples for the determination of composition, oxidative stability, somatic cell count (SCC), pH and electric conductivity were collected. Every two weeks, macrophage, lymphocyte, and polymorphonuclear leukocyte counts were also determined in individual milk samples. It was observed that milk yield was the greatest in the B2 group, with significant differences within the seventh and ninth week (p < 0.05), whereas no significant differences were found for milk composition, with the exception of the seventh week, when protein, lactose and non-fat solid levels were lower in MPBC groups (p < 0.05). Oxidative stability was improved in the groups that received the MPBC, with significant differences at the third, seventh, tenth and eleventh week (p < 0.05). SCC was also significantly lower at the second, eighth and ninth week in B2 compared to the other groups (p < 0.05), while no significant effects on the macrophage, lymphocyte, and polymorphonuclear leukocyte counts were observed. In conclusion, the MPBC addition had a positive effect on sheep milk yield, oxidative stability and somatic cell count, without any negative effect on its composition.
A Comprehensive Review of the Impact of Chromium Picolinate on Testicular Steroidogenesis and Antioxidant Balance
Authors: Moreira Rúben , Martins Ana D. , Alves Marco G. , de Lourdes Pereira Maria , Oliveira Pedro F.
Published: August 2023

Low testosterone (T) levels are a major cause of male infertility, as this hormone is crucial for several processes throughout the entire male reproductive tract. Leydig cells (LC) produce T through testicular steroidogenesis. Disrupted LC function can hinder steroid production and fertility. Among the factors that affect steroidogenesis, endocrine-disrupting chemicals (EDCs) raise concerns, as they disturb hormonal signaling. Chromium is classified as an EDC, and its main forms are hexavalent (Cr(VI)) and trivalent chromium (Cr(III)). While Cr(III) is controversially regarded as an essential metal, its compound Cr(III) picolinate (CrPic3) is used as a nutritional supplement due to its antidiabetic and antioxidant properties. This review aims to identify the possible effects of CrPic3 on testicular steroidogenesis and thus, on male fertility. The detriments caused by CrPic3 in LC include the inhibition of enzymes involved in steroidogenesis, and, as in other cells, the induction of mutagenesis and apoptosis. Remarkably, CrPic3 impacts male fertility through the alteration of reactive oxygen species (ROS), T levels, and sperm parameters (sperm motility and abnormal sperm count). However, gaps and inconsistencies exist in the literature concerning its effects on male fertility. Thus, further research is imperative to comprehend the underlying mechanisms of CrPic3 in the physiological processes relevant to male fertility, ensuring the supplement’s safety for use by men.
Antioxidant Activities, Phenolic Compounds, and Sensory Acceptability of Kombucha-Fermented Beverages from Bamboo Leaf and Mulberry Leaf
Authors: Xiong Ruo-Gu , Wu Si-Xia , Cheng Jin , Saimaiti Adila , Liu Qing , Shang Ao , Zhou Dan-Dan , Huang Si-Yu , Gan Ren-You , Li Hua-Bin
Published: August 2023

Kombucha is traditional drink made from the fermentation of a black tea infusion, and is believed to offer a variety of health benefits. Recently, exploring kombucha made from alternative substrates has become a research hotspot. In this paper, two novel kombucha beverages were produced with bamboo leaf or mulberry leaf for the first time. Moreover, the effects of fermentation with leaf residues (infusion plus residues) or without leaf residues (only infusion) on the antioxidant properties of kombucha were compared. The ferric-reducing antioxidant power assay, Trolox equivalent antioxidant capacity assay, Folin–Ciocalteu method, and high-performance liquid chromatography were utilized to measure the antioxidant capacities, total phenolic contents, as well as some compound concentrations of the kombucha. The results showed that two types of kombucha had high antioxidant capacities. Moreover, kombucha fermented with bamboo leaf residues (infusion plus residues) significantly enhanced its antioxidant capabilities (maximum increase 83.6%), total phenolic content (maximum increase 99.2%), concentrations of some compounds (luteolin-6-C-glucoside and isovitexin), and sensory acceptability, compared to that without residues (only infusion). In addition, fermentation with leaf residues had no significant effect on mulberry leaf kombucha. Overall, the bamboo leaf was more suitable for making kombucha with residues, while the mulberry leaf kombucha was suitable for fermentation with or without residues.
Impact of Partial Replacement of Cement with a Blend of Marble and Granite Waste Powder on Mortar
Authors: Nega Daniel Mulat , Yifru Begashaw Worku , Taffese Woubishet Zewdu , Ayele Yalew Kassa , Yehualaw Mitiku Damtie
Published: August 2023

The purpose of this study is to examine the effects of partially replacing cement with a blend of marble waste powder (MWP) and granite waste powder (GWP) in mortar, with the goal of reducing the environmental harm caused by cement. The investigation included an analysis of the distinctive properties of the two waste powders individually, as well as initial tests with various ratios to determine the optimal combination that yields the highest strength. It was observed that a 50% MWP to 50% GWP blend produced the most substantial strength. Subsequently, the effect of partial replacement of cement with the blend of marble and granite waste powder (MGWP) at various increments of 5%, ranging from 0% to 30%, was evaluated by subjecting the mortar to numerous tests to assess its workability, physical, mechanical, durability, and microstructural properties. The analysis of the employed waste powders confirmed that the GWP can be classified as a natural pozzolan material belonging to Class N. As the proportion of MGWP increased, the workability of the mortar mixes decreased. However, incorporating MGWP up to 15% resulted in enhancements in bulk density, compression strength, and homogeneity, with the best performance observed at a 10% MGWP content. Microstructure analysis confirmed that the addition of MGWP enhanced the bonding of C–S–H and C–H, leading to a denser morphological structure in the mixes, particularly at a 10% MGWP content. The utilization of MGWP not only significantly reduced the carbon footprint associated with cement production but also fostered sustainability.
Vision-Based System for Black Rubber Roller Surface Inspection
Authors: Nguyen Thanh-Hung , Nguyen Huu-Long , Bui Ngoc-Tam , Bui Trung-Hieu , Vu Van-Ban , Duong Hoai-Nam , Hoang Hong-Hai
Published: August 2023

This paper proposes a machine vision system for the surface inspection of black rubber rollers in manufacturing processes. The system aims to enhance the surface quality of the rollers by detecting and classifying defects. A lighting system is installed to highlight surface defects. Two algorithms are proposed for defect detection: a traditional-based method and a deep learning-based method. The former is fast but limited to surface defect detection, while the latter is slower but capable of detecting and classifying defects. The accuracy of the algorithms is verified through experiments, with the traditional-based method achieving near-perfect accuracy of approximately 98% for defect detection, and the deep learning-based method achieving an accuracy of approximately 95.2% for defect detection and 96% for defect classification. The proposed machine vision system can significantly improve the surface inspection of black rubber rollers, thereby ensuring high-quality production.
Propeller-Induced Jet Impact on Vegetated Flow Fields: Complex Coupled Effect towards the Velocity Profile
Authors: Pu Jaan H.
Published: August 2023

The failure of swirling ship propellers in marine environments can lead to huge repair costs. One of the main causes of such failure is when propellers tangle with vegetation, especially in shallow flow environments like ports, harbours, or shipyards. In order to understand the above-mentioned issue, this study proposes an analytical approach to explore efficient predictions and provide a flow guideline with respect to the co-existence of vegetation and propeller swirling effects. More specifically, we intend to investigate the full-depth theoretical velocity profile to represent propeller-induced flow under submerged vegetation conditions. This paper first investigates the modified logarithmic law approach to determine its suitability to represent the regional vegetated flow zone before implementing it into a three-layer analytical model. It was found, using the benchmark of literature measurements, that the modified log law improved the near-bed velocity calculation by nearly 70% when compared to an existing model. A propeller jet impact computation coupled into the vegetation analytical model was then investigated in different locations within the vegetated flow, i.e., at free-flow, water–vegetation interface, and vegetation-hindered zones, to study their complex velocity distribution patterns. The results demonstrate adequate validation with the vegetated flow and measured propeller jet data from the literature. This proves the potential of the proposed analytical approach in representing a real-world propeller jet event submerged in water flow with the existence of vegetation. The proposed novel method allows costless computation, i.e., as compared to conventional numerical models, in representing the complex interaction of the propeller jet and vegetated flow.
Evaluating the Facial Esthetic Outcomes of Digital Smile Designs Generated by Artificial Intelligence and Dental Professionals
Authors: Ceylan Gülsüm , Özel Gülsüm Sayın , Memişoglu Gözde , Emir Faruk , Şen Sevgin
Published: August 2023

This study evaluates the preference rates for smile designs created by professionals or by Artificial Intelligence (AI) among dentists, dentistry students, and laypeople. Four cases with symmetrical and asymmetrical features were selected based on the Facial Flow (FF) concept from the database of the Smile Designer app regarding anatomical facial points. Two smile designs were created for each selected case: one using Artificial Intelligence (AI) and one created manually. An online survey assessed participants’ preferences for the different smile designs. The chi-square test “Pearson’s and Fisher’s exact test (P)” was used to analyze the survey data. A total of 628 people completed the study. Dentists preferred the manually-created smile design for the first three cases. For Case 4, dentists who used the Smile Designer program preferred the manually-created design (55.88%), while those who did not use the program preferred the AI-generated design (55.84%). There was a significant difference in esthetic perception between dentists and dental students (p = 0.001) and between dentists and laypeople (p = 0.001) for Case 1, only between dentists and dental students (p = 0.003) for Case 2, and only between dentists and laypeople (p = 0.001) for Case 3. Furthermore, we found that females (p = 0.007) and orthodontists (p = 0.025) had a higher preference for the AI-generated design in this case compared to males and other dental specialties for Case 3. While age, education level, and clinical experience did not significantly impact dentists’ preference for manually-created or AI-generated smile designs (p > 0.05), our results suggest that there were some differences in preference for Case 3. Overall, our findings suggest that the use of AI-generated smile designs for symmetric faces is acceptable to both dentists and laypeople and can offer time-saving benefits for clinicians.
ATOSE: Audio Tagging with One-Sided Joint Embedding
Authors: Lee Jaehwan , Moon Daekyeong , Kim Jik-Soo , Cho Minkyoung
Published: August 2023

Audio auto-tagging is the process of assigning labels to audio clips for better categorization and management of audio file databases. With the advent of advanced artificial intelligence technologies, there has been increasing interest in directly using raw audio data as input for deep learning models in order to perform tagging and eliminate the need for preprocessing. Unfortunately, most current studies of audio auto-tagging cannot effectively reflect the semantic relationships between tags—for instance, the connection between “classical music” and “cello”. In this paper, we propose a novel method that can enhance audio auto-tagging performance via joint embedding. Our model has been carefully designed and architected to recognize the semantic information within the tag domains. In our experiments using the MagnaTagATune (MTAT) dataset, which has high inter-tag correlations, and the Speech Commands dataset, which has no inter-tag correlations, we showed that our approach improves the performance of existing models when there are strong inter-tag correlations.
The Effectiveness and Privacy Preservation of IoT on Ubiquitous Learning: Modern Learning Paradigm to Enhance Higher Education
Authors: El-Haggar Nahla , Amouri Lobna , Alsumayt Albandari , Alghamedy Fatemah H. , Aljameel Sumayh S.
Published: August 2023

The progress made in Information and Communication Technologies (ICT) has played a crucial role in turning the Internet of Things (IoT) into a reality. IoT is an emerging technology that refers to networks of interconnected and Internet-enabled objects equipped with sensors, processors, and actuators that interact with each other to create significant collaboration and interaction environments. The field of education is one of the areas where IoT can be applied. However, the implementation of IoT poses security and privacy risks, such as unauthorized access, denial-of-service (DoS) attacks, and interference with wireless signals where IoT devices collect a significant amount of data, including user’s personal information like identity, location, and daily behavior. Therefore, it is crucial to protect users’ privacy in IoT applications. The innovative Ubiquitous Learning Environments (ULEs) have been created by ubiquitous computing technologies (mobile, wireless, network), which provide learners with learning experiences beyond the traditional classroom in both the real and virtual worlds. Ubiquitous learning (U-learning) is an emerging technology as a result of the tremendous technological revolution of ICT. U-learning is a novel learner-centered approach that aims to enhance learning, motivation, and creativity by utilizing innovative technology and IoT. U-learning enables learners to access the appropriate learning content, collaborate with the right learning partners, and engage in self-learning at the right time and place in a ubiquitous computing environment. To support learners in developing their social skills, in this study a framework for implementing the ULE based on the Internet of Things is designed, which consists of three main layers: perception, network, and application. The article explores the effects of IoT on education and how U-learning, which incorporates IoT to enhance learning experiences, has the potential to replace traditional classroom learning. Furthermore, the article addresses privacy preservation measures for different layers within the IoT environment and ULE. A framework for implementing the ULE model is in progress, which is a part of our future work.
VLSI-Friendly Filtering Algorithms for Deep Neural Networks
Authors: Cariow Aleksandr , Papliński Janusz P. , Makowska Marta
Published: August 2023

The paper introduces a range of efficient algorithmic solutions for implementing the fundamental filtering operation in convolutional layers of convolutional neural networks on fully parallel hardware. Specifically, these operations involve computing M inner products between neighbouring vectors generated by a sliding time window from the input data stream and an M-tap finite impulse response filter. By leveraging the factorisation of the Hankel matrix, we have successfully reduced the multiplicative complexity of the matrix-vector product calculation. This approach has been applied to develop fully parallel and resource-efficient algorithms for M values of 3, 5, 7, and 9. The fully parallel hardware implementation of our proposed algorithms achieves approximately a 30% reduction in embedded multipliers compared to the naive calculation methods.