Miracle-dz/UniFAR-FTUs huggingface dataset:
Land use impact on soil gas and soil water transport properties

OF DISSERTATION LAND USE IMPACT ON SOIL GAS AND SOIL WATER TRANSPORT PROPERTIES The consequences of land use choices on soil water and gas transport properties are significant for gas and water flux in agricultural environments. Spatial and temporal patterns and associations of soil water and soil gas characteristics and processes in different land uses are not well understood. The objectives of this study were to 1) characterize soil structure under crop and grass systems, 2) quantify spatial patterns and associations of soil physical characteristics in crop and grass systems, and 3) quantify spatial and temporal patterns and associations of CO2 and N2O fluxes. The research was conducted in a 60 by 80 m field divided into grass and crop systems. Sixty sampling points were distributed in four transects with 5and 1-m spatial intervals between measurement points. Gas fluxes were measured, at two-week time intervals, 22 times during a year. Pore size distribution was more homogeneous and more continuous pores were found in the grass than in the crop system. The spatial variability of most selected soil physical characteristics was more structured in the crop than in the grass system, which reflected the impact of land use and soil structure on their spatial patterns. CO2 flux was dependent for a longer distance in the grass than in the crop system, however, the two land-use systems exhibited similar spatial ranges of N2O flux. Gas fluxes were temporally dependent for a longer period in the grass than in the crop system. The spatial associations between CO2 and N2O fluxes and selected biochemical and physical factors depended on the flux sampling season and land use. Soil temperature was the dominant controlling factor on the temporal variability of CO2 and N2O fluxes but not on the spatial behavior. Considering the spatial and temporal ranges and dependency strength of soil variables helps identify efficient sampling designs that can result in better time and resource management. Spatial and temporal relationships between the selected soil variables also improve understanding soil management and sampling soil variables. This study provides the baseline and recommendations for future investigations specifically for sampling designs, soil management, and predictions of different soil processes related to gas fluxes.
Delivery of Therapeutic miRNA via Plasma-Polymerised Nanoparticles Rescues Diabetes-Impaired Endothelial Function

MicroRNAs (miRNAs) are increasingly recognised as key regulators of the development and progression of many diseases due to their ability to modulate gene expression post-translationally. While this makes them an attractive therapeutic target, clinical application of miRNA therapy remains at an early stage and in part is limited by the lack of effective delivery modalities. Here, we determined the feasibility of delivering miRNA using a new class of plasma-polymerised nanoparticles (PPNs), which we have recently isolated and characterised. We showed that PPN-miRNAs have no significant effect on endothelial cell viability in vitro in either normal media or in the presence of high-glucose conditions. Delivery of a miRNA inhibitor targeting miR-503 suppressed glucose-induced miR-503 upregulation and restored the downstream mRNA expression of CCNE1 and CDC25a in endothelial cells. Subsequently, PPN delivery of miR-503 inhibitors enhanced endothelial angiogenesis, including tubulogenesis and migration, in culture conditions that mimic diabetic ischemia. An intramuscular injection of a PPN-miR-503 inhibitor promoted blood-perfusion recovery in the hindlimb of diabetic mice following surgically induced ischemia, linked with an increase in new blood vessel formation. Together, this study demonstrates the effective use of PPN to deliver therapeutic miRNAs in the context of diabetes.
Ileal Dysbiosis Is Associated with Increased Acoustic Startle in the 22q11.2 Microdeletion Mouse Model of Schizophrenia

Recent studies involving transplantation of feces from schizophrenia (SCZ) patients and their healthy controls into germ-free mice have demonstrated that the gut microbiome plays a critical role in mediating SCZ-linked physiology and behavior. To date, only one animal model (a metabotropic glutamate receptor 5 knockout) of SCZ has been reported to recapitulate SCZ-linked gut dysbiosis. Since human 22q11.2 microdeletion syndrome is associated with increased risk of SCZ, we investigated whether the 22q11.2 microdeletion (“Q22”) mouse model of SCZ exhibits both SCZ-linked behaviors and intestinal dysbiosis. We demonstrated that Q22 mice display increased acoustic startle response and ileal (but not colonic) dysbiosis, which may be due to the role of the ileum as an intestinal region with high immune and neuroimmune activity. We additionally identified a negative correlation between the abundance of a Streptococcus species in the ilea of Q22 mice and their acoustic startle response, providing early evidence of a gut–brain relationship in these mice. Given the translational relevance of this mouse model, our work suggests that Q22 mice could have considerable utility in preclinical research probing the relationship between gut dysbiosis and the gut–brain axis in the pathogenesis of SCZ.
SIMULATION OF TRACK STRUCTURES AS THE BASIS OF BIOSENSORS

The main factor determining the functioning of the track biosensor is the influence of the composition of an ionic liquid flowing through the track on the ion current density at a certain external voltage. When any contamination enters the ionic liquid flowing through the track, the current density changes. This change determines the sensitivity of the biosensor. The amplifying electronic circuit of the device makes it possible to vary the sensitivity parameter over a wide range. In this work, it was found that the sensitivity of the biosensor depends on the mode in which it is operated. This means that the mode of operation must be selected depending on what sensitivity is required in each particular case.
Bat behavioral immune responses in social contexts: current knowledge and future directions

Animals often mount complex immune responses to infections. Aside from cellular and molecular defense mechanisms, animals can alter their behavior in response to infection by avoiding, resisting, or tolerating negative effects of pathogens. These behaviors are often connected to cellular and molecular immune responses. For instance, sickness behaviors are a set of behavioral changes triggered by the host inflammatory response (e.g., cytokines) and could aid in resisting or tolerating infection, as well as affect transmission dynamics if sick animals socially withdraw or are being avoided by others. To fully understand the group and population level transmission dynamics and consequences of pathogen infections in bats, it is not only important to consider cellular and molecular defense mechanisms, but also behavioral mechanisms, and how both interact. Although there has been increasing interest in bat immune responses due to their ability to successfully cope with viral infections, few studies have explored behavioral anti-pathogen defense mechanisms. My main objective is to explore the interaction of cellular and molecular defense mechanisms, and behavioral alterations that results from infection in bats, and to outline current knowledge and future research avenues in this field.
Pain Management in Children Admitted to the Emergency Room: A Narrative Review

Pain is a biopsychosocial experience characterized by sensory, physiological, cognitive, affective, and behavioral components. Both acute and chronic pain can have short and long-term negative effects. Unfortunately, pain treatment is often inadequate. Guidelines and recommendations for a rational approach to pediatric pain frequently differ, and this may be one of the most important reasons for the poor attention frequently paid to pain treatment in children. This narrative review discusses the present knowledge in this regard. A literature review conducted on papers produced over the last 8 years showed that although in recent years, compared to the past, much progress has been made in the treatment of pain in the context of the pediatric emergency room, there is still a lot to do. There is a need to create guidelines that outline standardized and easy-to-follow pathways for pain recognition and management, which are also flexible enough to take into account differences in different contexts both in terms of drug availability and education of staff as well as of the different complexities of patients. It is essential to guarantee an approach to pain that is as uniform as possible among the pediatric population that limits, as much as possible, the inequalities related to ethnicity and language barriers.
Prevalence of High-dose Antipsychotic Prescribing in Schizophrenia: A Clinical Audit in a Regional Queensland Mental Health Service

Background: Antipsychotic medication is widely recognized as a critical intervention in both acute and ongoing treatments of schizophrenia. Guidelines endorse the routine practice of monotherapy with antipsychotic medication at the minimum effective dose. Despite the recommendations, high-dose antipsychotic prescribing and polytherapy appear to be common practice. Objective: The objective of this study was to determine the prevalence of high-dose antipsychotic prescribing in adult patients with schizophrenia in a regional Queensland hospital and to know if the prescribing practices are in keeping with the international guidelines and with the local policy introduced in December 2017. Methods: This was a cross-sectional survey/clinical audit of 358 adult patients with schizophrenia open to the service in both community and inpatient settings. The individual prescribing practices of psychiatrists were also examined. Results: A minority (15%) were prescribed high doses (high-dose single agent and high dose by polytherapy) and 20% were prescribed polytherapy (including high dose and within normal dose range). Conclusion: Eighty-five percent of the patients with the diagnosis of schizophrenia open to the service were prescribed antipsychotic within the dose range. In this respect, prescribing was aligned with current evidence-based guidelines.
A Hybrid Model for Vehicle Acceleration Prediction

Accurate prediction of vehicle acceleration has significant practical applications. Deep learning, as one of the methods for acceleration prediction, has shown promising applications in acceleration prediction. However, due to the influence of multiple factors on acceleration, a single data model may not be suitable for various driving scenarios. Therefore, this paper proposes a hybrid approach for vehicle acceleration prediction by combining clustering and deep learning techniques. Based on historical data of vehicle speed, acceleration, and distance to the preceding vehicle, the proposed method first clusters the acceleration patterns of vehicles. Subsequently, different prediction models and parameters are applied to each cluster, aiming to improve the prediction accuracy. By considering the unique characteristics of each cluster, the proposed method can effectively capture the diverse acceleration patterns. Experimental results demonstrate the superiority of the proposed approach in terms of prediction accuracy compared to benchmarks. This paper contributes to the advancement of sensor data processing and artificial intelligence techniques in the field of vehicle acceleration prediction. The proposed hybrid method has the potential to enhance the accuracy and reliability of acceleration prediction, enabling applications in various domains, such as autonomous driving, traffic management, and vehicle control.
Adherence to a healthy sleep pattern is associated with lower risks of incident falls and fractures during aging

Background Autoimmune diseases are more common among people with unhealthy sleep behaviors, and these conditions have been linked to aging-related bone health. However, there have been few studies that examined the correlation between recently developed sleep patterns based on sleep duration, sleepiness, chronotype, snoring, insomnia, and the incidence of falls and fractures. Methods We used a newly developed sleep pattern with components of sleep 7 to 8 h per day, absence of frequent excessive daytime sleepiness, early chronotype, no snoring, and no frequent insomnia as healthy factors to study their relationship with the incidence of falls and fractures. The analysis was conducted among 289,000 participants from the UK Biobank. Results The mean follow-up period was 12.3 years (3.5 million person-years of follow-up), and 12,967 cases of falls and 16,121 cases of all fractures were documented. Compared to participants exhibiting an unfavorable sleep pattern, those adhering to a healthy sleep pattern experienced a 17% and 28% reduction in the risks of incident falls (hazard ratio [HR], 0.83; 95% CI, 0.74–0.93) and all fractures (HR, 0.72; 95% CI, 0.66–0.79) during follow-up. In addition, participants exhibiting a healthy sleep pattern, together with a high genetically determined bone mineral density (BMD), showed the lowest risks of falls and fractures. Conclusion A healthy sleep pattern was significantly linked to decreased risks of incident falls and fractures. The protective association was not modified by genetically determined BMD.
Town scale response of water viral communities to town source surface water contamination with hydrochemical parameters

This study aims to explore the relationship between human enteric viruses found in town-scale surface water sources and certain chemical contaminants present in the water. From October 2010 to April 2012, water samples were collected and analyzed using a combination of biophysical and molecular techniques to detect the presence of human adenoviruses (HAdV) and human enteroviruses (HEV) as well as chemical parameters as predictors for virus survival. The concentrations of 12 chemical contaminants were found to be within WHO-recommended limits. The study found positive and negative associations between viral genome detection and four out of the 12 metal and nonmetal analytes. Specifically, there was a correlation between Cd and HAdV genome detection (rho = 0.146, p = 0.032) and between Pb and Fe with HEV (rho = 0.156, p = 0.022) and (rho = 0.148, p = 0.029), respectively. For nonmetals, phosphates were slightly negatively correlated to HEV (rho = 0.174, p = 0.010). The results of the study did not provide support for the hypothesis of an association between the presence of human enteric viruses and the levels of twelve chemical contaminants.
Discrimination of Anari Cheese Samples in Comparison with Halloumi Cheese Samples Regarding the Origin of the Species by FTIR Measurements and Chemometrics

Nowadays, adulteration of traditional food products is a very important field in the general food authenticity sector. Moreover, it is important to create databases with authentic traditional products. In Cyprus, research about the traditional dairy products is scarce. Anari is predominantly made from goat’s and sheep’s milk, but milk from cows can also be used. It is produced during the process of Halloumi cheese making. Classification of Halloumi and Anari cheese took place in two classes, thus per cheese type, and after that in milk species subclasses such as cow and goat-sheep origins for each cheese type. This research study aims to enlighten the field of food authenticity in terms of traditional Cypriot dairy products. The first step of the methodology is the freeze-drying process for lyophilization of samples. Forty-four samples have been analyzed thus far, including both Halloumi and Anari cheese. Measurements for each sample were obtained by using Fourier Transformed Infrared (FTIR) Spectroscopy. Interpretation of the extensive data was undertaken via Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA), and through the SIMCA chemometrics package. Characterization of Anari cheese by applying FTIR took place. In terms of cheese type, Halloumi and Anari cheese samples were classified correctly. In addition, Anari samples were classified correctly regarding the milk species’ origin. The proposed experimental procedure along with chemometrics allow the detection of the milk species’ origin of traditional Anari samples, highlighting the importance of FTIR spectroscopy in combination with chemometrics in food authenticity. Creation of a database with Anari samples from Cyprus has started, and this is a very important step towards authenticity of traditional dairy products of Cyprus.
Natural selection in the field and the classroom

Translocations are a key conservation strategy for many imperiled fish species, but important questions about what maximizes the success of these projects remain unanswered. For example, how much does it matter which populations contribute individuals? We used an experimental translocation to look for evidence of genetic differences among three wild and two hatchery populations of westslope cutthroat trout. We translocated embryos into six locations within a fishless watershed containing prime cutthroat habitat. We examined relative survival, annual growth rates, and condition at ages 1 and 2. All three wild populations performed similarly. Little evidence of local adaptation to stream temperature existed and no evidence existed of decreased population fitness that could be caused by inbreeding depression. The hatchery populations performed as well or better than the wild populations. A translocation project using any of these five populations would have had a similar outcome. Further research should examine reproductive success to directly compare fitness among these populations.
Sagitta: An Energy-Efficient Sparse 3D-CNN Accelerator for Real-Time 3-D Understanding

Three-dimensional (3-D) understanding or inference has received increasing attention, where 3-D convolutional neural networks (3D-CNNs) have demonstrated superior performance compared to 2D-CNNs, since 3D-CNNs learn features from all three dimensions. However, 3D-CNNs suffer from intensive computation and data movement. In this article, Sagitta, an energy-efficient low-latency on-chip 3D-CNN accelerator, is proposed for edge devices. Locality and small differential value dropout are leveraged to increase the sparsity of activations. A full-zero-skipping convolutional microarchitecture is proposed to fully utilize the sparsity of weights and activations. A hierarchical load-balancing scheme is also introduced to increase the hardware utilization. Specialized architecture and computation flow are proposed to enhance the effectiveness of the proposed techniques. Fabricated in a 55-nm CMOS technology, Sagitta achieves 3.8 TOPS/W for C3D at a latency of 0.1 s and 4.5 TOPS/W for 3D U-Net at a latency of 0.9 s at 100 MHz and 0.91-V supply voltage. Compared to the state-of-the-art 3D-CNN and 2D-CNN accelerators, Sagitta enhances the energy efficiency by up to <inline-formula> <tex-math notation="LaTeX">$379.6\times $ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$11\times $ </tex-math></inline-formula>, respectively.
Adaptive coupled discrete/continuous approach for the forming of materials

During the manufacturing process of train wheels, industries encounter limitations to study the fatigue cracking problem with the finite element method (FEM). Another method, the discrete element method (DEM), is more adapted to study these types of problems, but it is very expensive. This paper shows a strategy to switch from an initially purely FEM computation to a combined FEM-DEM computation. This switching made it possible to take advantage of both methods. To achieve this strategy, a coupling method and a field transfer method between FEM and DEM have been developed. To validate these methods, numerical test cases are carried out.
Fatigue Estimation Using Peak Features from PPG Signals

Fatigue is a prevalent subjective sensation, affecting both office workers and a significant global population. In Taiwan alone, over 2.6 million individuals—around 30% of office workers—experience chronic fatigue. However, fatigue transcends workplaces, impacting people worldwide and potentially leading to health issues and accidents. Gaining insight into one’s fatigue status over time empowers effective management and risk reduction associated with other ailments. Utilizing photoplethysmography (PPG) signals brings advantages due to their easy acquisition and physiological insights. This study crafts a specialized preprocessing and peak detection methodology for PPG signals. A novel fatigue index stems from PPG signals, focusing on the dicrotic peak’s position. This index replaces subjective data from the brief fatigue index (BFI)-Taiwan questionnaire and heart rate variability (HRV) indices derived from PPG signals for assessing fatigue levels. Correlation analysis, involving sixteen healthy adults, highlights a robust correlation (R > 0.53) between the new fatigue index and specific BFI questions, gauging subjective fatigue over the last 24 h. Drawing from these insights, the study computes an average of the identified questions to formulate the evaluated fatigue score, utilizing the newfound fatigue index. The implementation of linear regression establishes a robust fatigue assessment system. The results reveal an impressive 91% correlation coefficient between projected fatigue levels and subjective fatigue experiences. This underscores the remarkable accuracy of the proposed fatigue prediction in evaluating subjective fatigue. This study further operationalized the proposed PPG processing, peak detection method, and fatigue index using C# in a computer environment alongside a PPG device, thereby offering real-time fatigue indices to users. Timely reminders are employed to prompt users to take notice when their index exceeds a predefined threshold, fostering greater attention to their physical well-being.
Analyses on Research Status of CSR in the World

Based on the web of Science database, such as the countries, research institutes, core authors, key journals and the distribution of research fields, the number of corporate social responsibility(CSR), articles published during 20 years (1994 to 2013 ) in the world were analyzed by bibliometric method. The total of 1,544 articles and their top 20 countries, research institutes, core authors, key journals and research fields for the literature types, the number of annual articles was retrieved globally. Analyses of status and trends of CSR researches in the world based on bibliometrics were performed for providing information to CSR researchers and decision makers.