Miracle-dz/UniFAR-FTUs huggingface dataset:
Quantifying the Accessibility of Sustainable Seafood in Southeast Queensland, Australia

Seafood is a nutritious source of protein for billions of people around the world and is generally more sustainable than other animal-based protein sources. As the human population grows, seafood will continue to play an important role in feeding the world. The sustainability of seafood products differs, depending on the species consumed, origin, and production/fishing method. Having access to sustainable seafood products is essential to ensure future generations can continue to consume seafood. We aimed to determine the accessibility of sustainable seafood products to consumers in southeast Queensland, Australia. We surveyed 52,447 fresh, cooked, and processed (packaged) seafood products across southeast Queensland from 2110 establishments (restaurants, supermarket, takeaway shops). We investigated the species, origin and catch method of seafood products and used this information to determine their sustainability according to the Good Fish Guide developed by the Australian Marine Conservation Society. We found enough information to determine the level of sustainability for 36% (n= 18,709) of surveyed products: 4.9% were sustainable, 4.1% were classified as ‘Eat Less’, and 27% were classified as ‘Say No’. The 64% (n=33,737) of products that we could not assess was due to the lack of information at point of sale (16%) or the product was not included in the Good Fish Guide (48%). The top three most accessible sustainable products were Australian farmed barramundi, oysters and prawns. The three most common products to ‘Say No’ were Australian farmed Atlantic salmon, imported prawns and basa. We found that 44% (n= 12,040) of products listed in the Good Fish Guide were lacking origin information. Improving the labelling of species, origin, and catch method of seafood products at the point of sale, especially detailed information about a product’s origin, is essential to improving the accessibility of sustainable seafood.
Diabetes Care in India: A Descriptive Study

Context: Diabetes is a chronic illness that requires continuing medical care and patient self-management education to prevent and reduce the risk of long-term complications. It requires an array of investigations to provide an accurate picture of the condition and its management accordingly by a qualified doctor. Aims: This study was conducted to understand the treatment received by type 2 diabetes (T2DM) patients from various categories of health care professionals and awareness about diabetes reversal by lifestyle modification and prevention of complications. Settings and Design: This was a community-based cross-sectional study. Subjects and Methods: The link of the semi-structured questionnaire in Google form with e-consent was sent to all members in the selected groups of “World free of obesity and diabetes” campaign on their personal WhatsApp account. Statistical Analysis Used: A total of 3082 participants were included, and the data obtained were analyzed using SPSS v26. Results: The mean age of the participants was 50.26 ± 9.78 years ranging from 18 to 81 years. A total of 35.8% of the study population was diabetic for 1–5 years. A total of 54.9% were started with antidiabetic medication on the same day of diagnosis. Only 1.5% of the patients had complete investigation profile for T2DM, 50.2% of the patients were briefed about hypoglycemia, and only 15.8% of the patients were checked for retinopathy. Conclusions: Most doctors, qualified as well as nonqualified, did not follow the standard guidelines for diagnosis, treatment, and patient education regarding T2DM; therefore, it is necessary to train all medical practitioners regarding these guidelines. Diabetes reversal by lifestyle modification must be prescribed as the first line of treatment in patients with T2DM.
Genome-Wide Identification of the MYB Gene Family in Cymbidium ensifolium and Its Expression Analysis in Different Flower Colors

MYB transcription factors of plants play important roles in flavonoid synthesis, aroma regulation, floral organ morphogenesis, and responses to biotic and abiotic stresses. Cymbidium ensifolium is a perennial herbaceous plant belonging to Orchidaceae, with special flower colors and high ornamental value. In this study, a total of 136 CeMYB transcription factors were identified from the genome of C. ensifolium, including 27 1R-MYBs, 102 R2R3-MYBs, 2 3R-MYBs, 2 4R-MYBs, and 3 atypical MYBs. Through phylogenetic analysis in combination with MYB in Arabidopsis thaliana, 20 clusters were obtained, indicating that these CeMYBs may have a variety of biological functions. The 136 CeMYBs were distributed on 18 chromosomes, and the conserved domain analysis showed that they harbored typical amino acid sequence repeats. The motif prediction revealed that multiple conserved elements were mostly located in the N-terminal of CeMYBs, suggesting their functions to be relatively conserved. CeMYBs harbored introns ranging from 0 to 13 and contained a large number of stress- and hormone-responsive cis-acting elements in the promoter regions. The subcellular localization prediction demonstrated that most of CeMYBs were positioned in the nucleus. The analysis of the CeMYBs expression based on transcriptome data showed that CeMYB52, and CeMYB104 of the S6 subfamily may be the key genes leading to flower color variation. The results lay a foundation for the study of MYB transcription factors of C. ensifolium and provide valuable information for further investigations of the potential function of MYB genes in the process of anthocyanin biosynthesis.
Intrusion Detection Method Based on Sparse Expression for SVM

This paper presents an intrusion detection method based on the sparse SVM (support vector machines). This algorithm is to achieve sparse expression for the network data by constructing a sparse base, which could reduce the number of data to be processed, and then use the SVM algorithm to carry out the classification, thus achieving the efficient intrusion detection for the network access behavior.
MOTIVATION AGENDA FOR SOCIAL EMPOWERMENT AND RESPECT FOR PEOPLE DURING THE DRAFTING OF CONSTRUCTION CONTRACTS

Collaboration is a key element of the UK Government’s current construction strategy. Contracts in the UK are evolving to incorporate an increasing number of collaborative features. In construction literature, there are calls for a more robust approach to the selection of such features relating to overall clients’ performance requirements, with clients wishing to improve the overall performance of supply chains. The output of the supply chain is dependent on their workforce, with a key element of performance relating to motivation. There is work in psychology that provides an element of generalisation to human motivation, which establishes enablers of intrinsic motivation that improves workplace vitality, health and wellbeing. The aim of this paper is to provide a framework to assist practitioners make decisions that enable intrinsic motivation. The work establishes the basis of the hierarchy from robust work in psychology (self-determination theory); and relates the hierarchy to suites of contracts operating in the UK including the JCT, NEC, FIDIC and ACA suites. Document and summative content analysis evaluates different contractual mechanisms. The research establishes a critical approach to the incorporation of collaborative features in contracts that links to autonomy, competence and relatedness. Further research should be undertaken to explore construction contracts as enablers for social empowerment and respect for people.
Robust Control for Non-Minimum Phase Systems with Actuator Faults: Application to Aircraft Longitudinal Flight Control

This study is concerned with developing a robust tracking control system that merges the optimal control theory with fractional-order-based control and the heuristic optimization algorithms into a single framework for the non-minimum phase pitch angle dynamics of Boeing 747 aircraft. The main control objective is to deal with the non-minimum phase nature of the aircraft pitching-up action, which is used to increase the altitude. The fractional-order integral controller (FIC) is implemented in the control loop as a pre-compensator to compensate for the non-minimum phase effect. Then, the linear quadratic regulator (LQR) is introduced as an optimal feedback controller to this augmented model ensuring the minimum phase to create an efficient, robust, and stable closed-loop control system. The control problem is formulated in a single objective optimization framework and solved for an optimal feedback gain together with pre-compensator parameters according to an error index and heuristic optimization constraints. The fractional-order integral pre-compensator is replaced by a fractional-order derivative pre-compensator in the proposed structure for comparison in terms of handling the non-minimum phase limitations, the magnitude of gain, phase-margin, and time-response specifications. To further verify the effectiveness of the proposed approach, the LQR-FIC controller is compared with the pole placement controller as a full-state feedback controller that has been successfully applied to control aircraft dynamics in terms of time and frequency domains. The performance, robustness, and internal stability characteristics of the proposed control strategy are validated by simulation studies carried out for flight conditions of fault-free, 50%, and 80% losses of actuator effectiveness.
Multiperiod optimal power flow using Benders decomposition

This paper addresses a multiperiod optimal power flow, properly modeling the start-up and shut-down of thermal units, the transmission network in terms of line capacity limits and line losses, and the constraints of hydroelectric plants integrated in river systems. The generalized Benders decomposition is used to solve this large-scale multiperiod problem. Spot prices are obtained as a byproduct of the decomposition procedure. A realistic case study based on the electric energy system of mainland Spain is analyzed and the results obtained are reported.
Piezoelectric energy harvesting using a series synchronized switch technique

An alternative switching technique for piezoelectric energy harvesting is presented. The energy harvester based on piezoelectric elements is a promising method to scavenge ambient energy. Several non-linear techniques such as SSHI have been implemented to improve the global harvested energy. However, these techniques are sensitive to load and should be tuned to obtain optimal power output. This technique, called Series Synchronized Switch Harvesting (S3H), has both the advantage of easy implementation and independence of the harvested power with the load impedance. The harvesting circuit simply consists of a switch in series with the piezoelement and the load. The switch is nearly always open and is triggered-on each time the piezoelectric voltage reaches an extremum. It is opened back after an arbitrary on-time t0. The energy scavenging process happens when switch is closed. Based on linear motion assumption, the harvester structure is modeled as a “Mass-Spring-Damper” system. The analysis of S3H technique is considered with harmonic excitation. An analytical model of S3H is presented and discussed. The main advantage of this approach compared with the usual standard technique is that the extracted power is independent of the load within a wide range of load impedance, and that the useful impedance range is simply related to the defined switch on-time. For constant displacement excitation condition, the optimal power output is more than twice the power extracted by the standard technique as long as the on-time interval is small comparatively with the vibration period. For constant force excitation, an optimal on-time can be defined resulting in an optimally wide load bandwidth. Keywords: piezoelectric; energy harvesting; non-linear harvesting techniques; switching techniques.
Stratification of prostate cancer patients into low‐ and high‐grade groups using multiparametric magnetic resonance radiomics with dynamic contrast‐enhanced image joint histograms

This study aimed to investigate the potential of stratification of prostate cancer patients into low‐ and high‐grade groups (GGs) using multiparametric magnetic resonance (mpMR) radiomics in conjunction with two‐dimensional (2D) joint histograms computed with dynamic contrast‐enhanced (DCE) images.
Classification of Knowledge within the Electrical Contracting Industry: A Case Study

This paper provides electrical contractors with important information related to the future vision for the industry and how knowledge management can play a key role in a firm’s success. The methodology involved conducting nine structured and extensive interviews with experts in the electrical contracting business about trends and related best practices. These experts identified that the electrical contracting industry is becoming more complex, and that contractors must adopt more sophisticated management tools. Electrical contractors must also accelerate their adoption of information technology and actively pursue new market opportunities. A literature review on knowledge management as a best practice tool is provided, followed by a discussion of how this management tool can be used to help electrical contractors meet the challenges they face and enhance a firm’s chance of survival. The results of the interviews have been collated and placed within the proposed knowledge classification system as a case st.
Community-based water governance for adaptation to water reduction and scarcity in Badulla district of Sri Lanka

Sustainable Development Goal number 6 declares safe drinking water for all as a human right and it can be used as an indicator to measure development. While urban and municipal residents benefit from safe drinking water through centralized water supply systems, water supply for rural areas and estates were decentralized due to large construction costs, according to the demand-driven approach introducing community governance mechanism for water sources and water supply in rural areas. Community-based water societies emerged as a consequence of this situation. In Badulla district of Sri Lanka, 47% of community-based water societies depend upon natural water springs benefitting 46% of households in a particular area. Recently, two natural water springs dried up affecting 191 households and 10 community-based water societies who depend on natural water springs are regulating their water supply hours due to a long and extended drought situation.This affected 1,953 households in Badulla. Further it represents 8.4% of households who depend upon natural water springs. Owing to the present water scarcity, 37 community-based water societies started catchment protection initiatives with the support of government and non-governmental agencies. One community-based water society in this district has collapsed due to lack of water with the drying up of their natural water spring and another is functioning with an alternative water source. Other community-based water societies are functioning to a varying extent because of water level reduction in natural water springs. While the climate is changing, there are development initiatives that, in particular, are affecting natural water springs.
Comparison of two techniques for assessing pancreatic islet viability: flow cytometry and fluorescein diacetate/propidium iodide staining

Introduction: The success of islet transplantation for patients with unstable type 1 diabetes mellitus depends, in part, on the number of isolated islets and their quality, which is assessed by functional and viability tests. The test currently employed to evaluate islet viability, used by the Collaborative Islet Transplant Registry to release products for transplantation, is fluorescein diacetate/propidium iodide (FDA/PI) staining. However, the efficacy of this method relies on researcher experience; in this context, a quantitative method may be useful. The aim of this study was to compare islet viability as assessed by flow cytometry and the FDA/PI assay.
ASSESSING MARINEQUEST: A FOLLOW-UP STUDY ON EFFECTS OF A SUMMER RESIDENTIAL MARINE ENVIRONMENTAL EDUCATION PROGRAM ON KNOWLEDGE AND ATTITUDES

The purpose of this study was to investigate the effects of a one-week marine science education program, UNCW’s MarineQuest program, on the participants’ knowledge and attitudes towards the marine environment. This study is the second of a multi-year assessment examining the effectiveness of an informal environmental education program. Subjects were instructed on creating concept maps using techniques developed by Novak and Gowin (1984). Knowledge content and structure scores were obtained from concept maps and multiple choice surveys. Attitude scores were obtained using the Marine Life Attitude Inventory created by Andrews (2003) based on Kellert’s (1985) attitudinal dimensions towards wildlife. Data sets (2003 and 2006) were combined and analyzed using Chi-squared, Kruskal-Wallis, Wilcoxon, and Tukey- Kramer tests. The results of this study show significant differences favoring the Experimental Group I in structural complexity and knowledge content of participants. Differences in Mastery of Learning Objectives and Marine Animal Life Attitude Inventory posttest scores were significant, favoring the experimental group in all cases. These findings further support the MarineQuest program’s significant influence on participants’ knowledge and attitudes towards the marine environment and provide future guidelines for developing curricular and assessment efforts in environmental education.
Predicting Wind Speed for Wind Energy; Progress of the WINDENG Project

The suitability of the computer model MM5 for predicting wind speed, and hence wind energy, is investigated by performing simulations for different geographical regions. The focus is on wind speed in the lowest 200 m of the planetary boundary layer (PBL). The dependency of the simulated wind speed on PBL parameterization and atmospheric stability is studied. The smallest deviation between measured and simulated wind speed, averaged over a three-day period, is 1% and occurs for an off-shore simulation with unstable stratification. The largest deviations of 31% and 20% occur with orographically structured terrain, stable stratification and weak synoptic forcing. The results suggest that unstable conditions are simulated with better accuracy by MM5. Changes of the PBL scheme cause wind speed variations between 9% and 40% of the average wind speed. None of the PBL schemes is clearly the best and their performance can strongly vary for different conditions. Nevertheless, the Mellor-Yamada-Janjic (ETA) and the Blackadar PBL parameterization (BLK) schemes seem to be the most suitable schemes for wind energy applications. Additionally, MM5 was successfully adapted for idealised, stationary simulations in order to calculate a wind-climatology for Sardinia using a statistical-dynamical downscaling approach.
Effect of Washing Condition on the Fracture Strength, and the Degree of Conversion of 3D Printing Resin

This study compared the surface roughness, contact angle, surface energy, residual monomers, degree of conversion, and flexural strength of 3D-printed dental resin under various washing conditions. The specimens were printed with a digital light processing (DLP) printer and were divided into four groups: the group dipped in IPA for 5 s (IPA-D), the group washed in IPA for 1 min (IPA-1), the group washed in IPA for 10 min (IPA-10), and the group washed with TPM for 10 min (TPM-10). Following, the groups were redivided into two groups: a cured group and an uncured group. All experimental data were statistically analyzed using one-way analysis of variance and Tukey’s test. In all groups, the surface roughness showed a value of 1.2–1.8 μm, with no significant difference (p > 0.05). Contact angle showed a significant difference between the three groups using IPA and the TPM group, whereby the TPM-washed specimen showed a low contact angle (p < 0.05). The degree of conversion (DOC) increased in the following order: IPA-D group, IPA-1 group, IPA-10 group, and TPM-10 group, exhibiting a significant difference between all groups (p < 0.05). Flexural strength was measured at 110–130 MPa in all groups, with no significant difference between groups (p > 0.05). The washing time and washing solution type of the 3D printing material had no significant effect on surface roughness and flexural strength.
Optimal Algorithms for Stochastic Contextual Preference Bandits

We consider the problem of preference bandits in the contextual setting. At each round, the learner is presented with a context set of K items, chosen randomly from a potentially inﬁnite set of arms D ⊆ R d . However, unlike classical contextual bandits, our framework only allows the learner to receive feedback in terms of item preferences: At each round, the learner is allowed to play a subset of size q (any q ∈ { 2 , . . . , K } ) upon which only a (noisy) winner of the subset is revealed. Yet, same as the classical setup, the goal is still to compete against the best context arm at each round. The problem is relevant in various online decision-making scenarios, including recommender systems, information retrieval, tournament ranking–typically any application where it’s easier to elicit the items’ relative strength instead of their absolute scores. To the best of our knowledge, this work is the ﬁrst to consider preference-based stochastic contextual bandits for potentially inﬁnite decision spaces. We start with presenting two algorithms for the special case of pairwise preferences ( q = 2) : The ﬁrst algorithm is simple and easy to implement with an ˜ O ( d √ T ) regret guarantee, while the second algorithm is shown to achieve the optimal ˜ O ( √ dT ) regret, as follows from our Ω( √ dT ) matching lower bound analysis. We then proceed to analyze the problem for any general q -subsetwise preferences ( q ≥ 2 ), where surprisingly, our lower bound proves the fundamental performance limit to be Ω( √ dT ) yet again, independent of the subsetsize q . Following this, we propose a matching upper bound algorithm justifying the tightness of our results. This implies having access to subsetwise preferences does not help in faster information aggregation for our feedback model. All the results are corroborated empirically against existing baselines.