Miracle-dz/UniFAR-FTUs huggingface dataset:
A Framework for Interpretation of the Compressibility Behavior of Soils

This paper aims at the development of a regression-aided analytical framework for modeling and analyzing the compressibility behavior of over-consolidated soils. A three-parameter rectangular hyperbola function (3P-RH) was proposed for describing the void ratio-effective stress relationship. Validation of the 3P-RH was carried out by a compiled database gathered from the literature. Simple analytical solutions were then proposed for determining the compressibility curve variables including the compression (C-c) and recompression (C-r) indices and the preconsolidation pressure (P-c), which are intended to replace the current subjective graphical method by providing consistent results. Equations for the preconsolidation pressure were derived in accordance with four common graphical constructions covering various levels of geometrical complexity (slightly to highly subjective). A probabilistic comparison among the graphical constructions was then carried out. Furthermore, a sensitivity analysis with respect to the proposed preconsolidation pressure functions was considered to evaluate the influence of the 3P-RH fitting parameters (alpha and beta) on the preconsolidation pressure value. The proposed 3P-RH compressibility model accompanied by the suggested analytical solutions for solving the compressibility curve variables construct a unique framework for modeling the compressibility behavior of soils with an acceptable degree of accuracy and, more importantly, by a simple objective approach.
13 Spending Time in the Forest Responses of Cavity-Nesters to Temporal Changes in Forest Health in Interior British Columbia

An ongoing major outbreak of mountain pine beetle (Dendroctonus ponderosae) and other bark beetles and forest insects in British Columbia has resulted in large-scale increases in the availability of dead and dying trees. Using point count data from a long-term study on cavity-nesting birds and mammals, we describe how individual populations of cavity-nesting species, and the cavity- nesting community as a whole, have responded to the outbreak. We fit a linear trend model to 100 species observed during point counts, 21 of which showed a significant decline in abundance over the study period, 21 showed an increase in abundance, and 58 showed no trend. These concurrent declines and increases in abundance mean that community-level measures (species richness and abundance within cavity-nesting guild) have not changed following the outbreak, indicating the community structure has remained stable during the large increase in resource availability. These results suggest that species' responses to the availability of resources may thus also depend on the current status of competitors, predators and facilitators.
Rolling Bearing Fault Diagnosis Using Deep Transfer Learning Based on Joint Generalized Sliced Wasserstein Distance

The big data of rolling bearings for on-site monitoring usually contains very few failure samples and easily affected by noise and monitoring errors, so it is difficult to extract and identify useful fault information in normal samples. In addition, the rolling bearing samples of field test are un-labeled dataset of unknown fault types. If the existing fault diagnosis approaches are directly used for extraction and identification, it is easy to cause misjudgment or missing judgment. To solve this problem, a novel intelligent fault diagnosis approach using deep transfer learning based on joint generalized sliced Wasserstein distances (JGSWD) deep transfer learning is proposed. Firstly, the joint discrepancy between the data from real-case scenarios (DRS) and the data from laboratory equipment (DLE) is minimized by calculating the generalized sliced Wasserstein distances. Following, the marginal and conditional dataset distribution between source domain and target domain is balanced by using the dynamic domain alignment. Then, the top K correlated pseudo labels are calculated for reducing the conditional distribution and improving better transfer capability. Finally, the deep transfer learning from laboratory bearing dataset to field bearing dataset is carried out. The result shows that the proposed JGSWD method can achieve 97.56% fault diagnosis accuracy, which is higher than the other methods. Therefore, it is a practical semi-supervised learning approach for bearing fault diagnosis with small samples.
Recommendations for post-rehabilitation care of maxillofacial prostheses

Aim: This study aimed to review the scientific literature to describe the main care and hygiene protocols for different types of maxillofacial prostheses (MFP). Methods: A bibliographic search on the PubMed / Medline database using the following keywords: [“maxillofacial prosthesis” OR “ocular prostheses” OR “palatal obturators”] AND [“Cleaning” OR “disinfection”] AND [“care”] AND [“color stability”] OR [“denture cleansers” OR “cleansing agents”]. Articles addressing materials, cleaning and disinfection protocols, and care related to MFP were included. The following exclusion criteria were applied: no adequate methodology, incompatibility with the area of interest, and unavailability for reading in full. Results: The papers were grouped into the following topics: facial prostheses, ocular prostheses, maxillofacial intraoral prostheses, and retention systems. Conclusion: Despite the MFP changes over time, its degradation decreases upon following the recommendations and post-adaptation care. The guidelines for cleaning and disinfection must be individualized to guarantee the longevity of the prosthesis and the patient health.
NON-INVASIVE PPG-BASED ESTIMATION OF BLOOD GLUCOSE LEVEL

This paper focuses on non-invasive blood glucose determination using photoplethysmographic (PPG) signals, which is crucial for managing diabetes. Diabetes stands as one of the world’s major chronic diseases. Untreated diabetes frequently leads to fatalities. Current self-monitoring techniques for measuring diabetes require invasive procedures such as blood or bodily fluid sampling, which may be very uncomfortable. Hence, there is an opportunity for non-invasive blood glucose monitoring through smart devices capable of measuring PPG signals. The primary goal of this research was to propose methods for glycemic classification into two groups (low and high glycemia) and to predict specific glycemia values using machine learning techniques. Two datasets were created by measuring PPG signals from 16 individuals using two different smart devices – a smart wristband and a smartphone. Simultaneously, the reference blood glucose levels were invasively measured using a glucometer. The PPG signals were preprocessed, and 27 different features were extracted. With the use of feature selection, only 10 relevant features were chosen. Numerous machine learning models were developed. Random Forest (RF) and Support Vector Machine (SVM) with the radial basis function (RBF) kernel performed best in classifying PPG signals into two groups. These models achieved an accuracy of 76% (SVM) and 75% (RF) on the smart wristband test dataset. The functionality of the proposed models was then verified on the smartphone test dataset, where both models achieved similar accuracy: 74% (SVM) and 75% (RF). For predicting specific glycemia values, RF performed best. Mean Absolute Error (MAE) was 1.25 mmol/l on the smart wristband test dataset and 1.37 mmol/l on the smartphone test dataset.
Grass-tree interactions and the ecology of African savannas under current and future climates

Two important questions in savanna ecology are (1) how do grasses and trees manage to coexist in savannas while excluding each other in grasslands or rainforests and (2) how do savannas respond to anticipated climate change. This thesis presents two different savanna models to explore these questions. It is shown that a heuristic and deterministic model can explain grass-tree coexistence on a rainfall gradient between 200 mm and 1200 mm mean annual precipitation and that vegetation dynamics are stable on this gradient. The thesis further presents a dynamic and process-based vegetation simulation model for savannas that can simulate observed vegetation patterns in Africa from a small number of environmental input data. Simulation results show that fire suppression in Africa would increase biomass by about 13%. Simulations under IPCC climate change scenarios predict a significant shift towards tree dominated biomes. With these results, this thesis contributes to the current savanna and climate change research.
Nucleation and Arrest of Dynamic Rupture Induced by Reservoir Depletion

Seismic events induced by the depletion of hydrocarbon reservoirs can cause damage to housing and cause societal and economic unrest. However, the factors controlling the nucleation and size of production‐induced seismic events are not well understood. Here we used geomechanical modeling of production‐induced stresses and dynamic rupture modeling to assess the conditions controlling down‐dip rupture size. A generic model of (offset) depleting reservoir compartments separated by a fault was modeled in 2‐D using the Finite Element package DIANA FEA. Linear slip‐weakening was used to control fault friction behavior. Fault reactivation was computed in a quasi‐static analysis simulating stresses during reservoir depletion, followed by a fully dynamic analysis simulating seismic rupture. The sensitivity of reactivation and rupture size to in situ stress, dynamic friction, critical slip distance, and reservoir offset was evaluated. After reactivation, a critical fault length was required to slip before seismic instability could occur. In a subsequent fully dynamic analysis the propagation and arrest of dynamic rupture was simulated. Rupture remained mostly confined to the reservoir interval but could also propagate into the overburden and underburden or sometimes transition into a run‐away rupture. Propagation outside the reservoir interval was promoted by a critical in situ stress, a large stress drop, a small fracture energy, and no or little reservoir offset. With increasing offset (up to the reservoir thickness), reactivation was promoted but dynamic rupture size decreased.
Studies in Second Language Learning and Teaching

English has become an international language (EIL) as speakers around the world use it as a universal means of communication. Accordingly, scholars have investigated different aspects of EIL affecting communicative success. Speech scholars have been interested in speech constructs like accentedness, comprehensibility, and acceptability (e.g., Kang et al., 2023). On the other hand, pragmatic researchers have examined lexico-grammatical features of EIL that contribute to first language (L1) English listeners’ perceptions of appropriateness in speech acts (e.g., Taguchi, 2006). However, little is known about: a) how appropriateness is perceived by users of EIL of diverse L1s and b) how those appropriateness perceptions are related to lexico-grammatical and phonological features. Therefore, the present study had 184 listeners (L1 = English, Spanish, Chinese, and Indian languages) evaluate 40 speech acts performed by 20 speakers (L1 English and Chinese, 50% each) in terms of appropriateness on a 9-point numerical scale. Results from linear mixed-effects regressions suggested that: a) listener L1 did not contribute to listener ratings and b) speakers’ rhythm and lexico-grammatical features (i.e., use of different pragmatic strategies) significantly contributed to listener appropriateness ratings
Visual and Non-visual Quantities of Self-luminous Signboards in Residential Areas in China

This study explores quantitative influences of commercial lightbox signboards from both visual and non-visual perspectives by integrating measurements and simulations. First, 41 self-luminous signboards are individually measured and simulated. The relative root mean squared errors by using Radiance or Lark are 3.8% and 4.3%, respectively, which demonstrate the applicability and reliability of this integrated method. Over 70% of the measured signboards are greater than the maximum permitted average luminance threshold recommended by the national code. While achieving the same photopic luminance, the order of circadian luminance values from low to high for commonly used colours is: red, yellow, green, white, and blue. Secondly, a pedestrian shopping street is used as an example for context simulation. Although great luminance values concentrate on signboards, lights inside stores also contribute to scene-based lighting distributions. By integrating both field measurement and simulation, lighting pollutions caused by commercial signboards can be better understood and controlled from both visual and non-visual perspectives.
Assessing the Effect of Enzymatic Debridement on the Scar Quality in Partial-Thickness Burns to Deep Dermal Burns of the Hand: A Long-Term Evaluation

Background and Objectives: Burn surgery on the hands is a difficult procedure due to the complex anatomy and fragility of the area. Enzymatic debridement has been shown to effectively remove burn eschar while minimizing damage to the surrounding tissue and has therefore become a standard procedure in many burn centers worldwide over the past decade. However, surprisingly, our recent literature review showed limited valid data on the long-term scarring after the enzymatic debridement of the hands. Therefore, we decided to present our study on this topic to fill this gap. Materials and Methods: This study analyzed partial-thickness to deep dermal burns on the hands that had undergone enzymatic debridement at least 12 months prior. Objective measures, like flexibility, trans-epidermal water loss, erythema, pigmentation, and microcirculation, were recorded and compared intraindividually to the uninjured skin in the same area of the other hand to assess the regenerative potential of the skin after EDNX. The subjective scar quality was evaluated using the patient and observer scar assessment scale (POSAS), the Vancouver Scar Scale (VSS), and the “Disabilities of the Arm, Shoulder, and Hand” (DASH) questionnaire and compared interindividually to a control group of 15 patients who had received traditional surgical debridement for hand burns of the same depth. Results: Between January 2014 and December 2015, 31 hand burns in 28 male and 3 female patients were treated with enzymatic debridement. After 12 months, the treated wounds showed no significant differences compared to the untreated skin in terms of flexibility, trans-epidermal water loss, pigmentation, and skin surface. However, the treated wounds still exhibited significantly increased blood circulation and erythema compared to the untreated areas. In comparison to the control group who received traditional surgical debridement, scarring was rated as significantly superior. Conclusions: In summary, it can be concluded that the objective skin quality following enzymatic debridement is comparable to that of healthy skin after 12 months and subjectively fares better than that after tangential excision. This confirms the superiority of enzymatic debridement in the treatment of deep dermal burns of the hand and solidifies its position as the gold standard.
Lifestyle Medicine for the Prevention and Treatment of Pancreatitis and Pancreatic Cancer

The incidence of pancreatitis and pancreatic cancer is on the upswing in the USA. These conditions often lead to higher healthcare costs due to the complex nature of diagnosis and the need for specialized medical interventions, surgical procedures, and prolonged medical management. The economic ramification encompasses direct healthcare expenses and indirect costs related to productivity losses, disability, and potential long-term care requirements. Increasing evidence underscores the importance of a healthy lifestyle in preventing and managing these conditions. Lifestyle medicine employs evidence-based interventions to promote health through six key pillars: embracing a whole-food, plant-predominant dietary pattern; regular physical activity; ensuring restorative sleep; managing stress effectively; removing harmful substances; and fostering positive social connections. This review provides a comprehensive overview of lifestyle interventions for managing and preventing the development of pancreatitis and pancreatic cancer.
An Energy-Efﬁcient FPGA-based Convolutional Neural Network Implementation

—Convolutional Neural Networks (CNNs) are a very popular class of artiﬁcial neural networks. Current CNN models provide remarkable performance and accuracy in image processing applications. However, their computational complexity and memory requirements are discouraging for embedded real-time applications. This paper proposes a highly optimized CNN accelerator for FPGA platforms. The accelerator is designed as a LeNet CNN architecture focusing on minimizing resource usage and power consumption. Moreover, the proposed accelerator shows more than 2x higher throughput in comparison with other FPGA LeNet accelerators with reaching up 14 K images/sec. The proposed accelerator is implemented on the Nexys DDR 4 board and the power consumption is less than 700 mW which is 3x lower than the current LeNet architectures. Therefore, the proposed solution offers higher energy efﬁciency without sacriﬁcing the throughput of the CNN.
Evidence of a Mixed Infection of Candidatus Phytoplasma Trifolii’ and a Begomovirus in Eggplant ( Solanum melongena )

Symptoms associated with eggplant little leaf and leaf curl disease of eggplant was observed in the fields of Meerut district of Western Uttar Pradesh, India. Total DNA extracted from symptomatic and asymptomatic plants was subjected to nested-PCR assay using phytoplasma 16S rDNA primers and generic PCR with universal begomovirus coat-protein (CP) gene primers. Amplicons of expected size were obtained from symptomatic plants in both PCR assays. No PCR amplifications were observed for asymptomatic plants. A multiplex nested PCR assay was also developed by optimizing reaction components and reaction cycling parameters for simultaneous detection of Tomato leaf curl virus (ToLCV) and a phytoplasma. The eggplant infecting phytoplasma was identified as a member of group 16SrVI, ‘‘ Candidatus Phytoplasma trifolii’’, while the begomovirus showed 99% of CP gene identity with other whitefly transmitted begomoviruses including Solanum nigrum and Tomato leaf curl virus (ToLCV). Results indicate that both phytoplasma and begomovirus can co-infect the same host plant and the multiplex PCR provides a sensitive, rapid and low
Access and Participation: The use of Technologies as tools for Inclusion by Spanish University Lecturers

Spanish face-to-face universities experience constant challenges that threaten the inclusion of students with disabilities. Adopting inclusive pedagogies can support universities to develop a more inclusive approach. This paper explores the extent to which the use of technology influences the inclusive pedagogies of Spanish university lecturers. In particular, we focus on how lecturers use technologies to promote student participation and accessibility in Spanish institution. A qualitative methodology involving semi-structured in-depth interviews with 42 Spanish face-to-face universities experience constant challenges that threaten the inclusion of students with disabilities. Adopting inclusive pedagogies can support universities to develop a more inclusive approach. This paper explores the extent to which the use of technology influences the inclusive pedagogies of Spanish university lecturers. In particular, we focus on how lecturers use technologies to promote student participation and accessibility in Spanish institution. A qualitative methodology involving semi-structured in-depth interviews with 42 Spanish university lecturers regarding their inclusive practices and use of technology was employed. The results contribute four fundamental findings: (a) Lecturers who practise inclusive pedagogy can be differentiated as proactive or reactive; (b) University lecturers place greater emphasis on the use of technology as a promoter of accessibility rather than as a tool to promote participation; (c) There is a disconnect between knowledge of universal design for learning and the use of the technologies; and (d) The full transformative potential of technologies to facilitate the inclusion of learners with disabilities is not being harnessed. All these results allow us to highlight some key points about the use of technological tools in the application of inclusive pedagogy in university classrooms. Implications for practice or policy: • Spanish face-to-face universities still need to harness the full transformative potential of technologies to facilitate student inclusion. • There is a need for more professional development programmes within higher education institutions that focus on the potential of technologies to promote inclusion. • Universities have an important role to play in promoting the use of technological tools to ensure accessibility and participation of all students, especially students with disabilities.
Calibration of Hypoplastic Parameters – Two Different Aspects

Numerical modeling serves as a widely utilized method for addressing geotechnical concerns. A pivotal aspect of this modeling process is the accurate characterization of material behavior. The connection between stress and strain tensors within soil is explicated by the soil constitutive equation, which is reliant on factors like soil type and deformation circumstances. One notable model is hypoplasticity, which has been in use for more than three decades. This research aims to calibrate the hypoplastic parameters for Danube sand using the SoilTest Module of PLAXIS. The constitutive hypoplastic model for Danube sand was fine-tuned through a series of numerical simulations. The parameter calibration occurred twice: initially according to 5 cycles of hysteresis loop of stress–strain diagram of cyclic triaxial testing, and then subsequently in accordance with strain trends observed after ten thousand cycles. A comparison was drawn between parameters determined from the overall strain trends and those calibrated based on the five cycles. The findings indicate that while the model calibrated during a specific segment of testing can accurately predict strain values during compression and extension, it falls short in forecasting the accumulated settlement following prolonged cyclic loading. This suggests the model’s limited capability in anticipating long-term cyclic load effects on settlement behavior.
Sociotherapy in Day Care Facilities: Examining Sociotherapeutic Day Rooms in Gdańsk, Katowice and Poznań

: Sociotherapy as a form of helping practice is rapidly evolving. Sociotherapeutic day care facilities are places dedicated to conducting sociotherapeutic activities for children and youth. Therefore, the analysis aims to confront the definition of sociotherapy with the information about this form of therapy that individuals seeking assistance in a sociotherapy day facility can obtain from websites, social media profiles, and telephone conversations with staff members. The data collection method in this project is desk research supplemented with information from the statements of people working in the researched facilities. The method of data analysis is template analysis. The analyses covered 40 socio-therapeutic day care facilities in Gdańsk, Katowice, and Poznań. The information on how the establishments communicate about their work largely coincides with how sociotherapy is defined in the literature. The data obtained indicate, however, that sociotherapy, understood as a form of work with a small group based on a group process, is not the only form of help realized in day care facilities (and perhaps not the most important one) and that in-depth therapeutic work may not be realized in all centers due to the way work is organized.