Miracle-dz/UniFAR-FTUs huggingface dataset:
Mobile Software Development Kit for Real Time Multivariate Blood Glucose Prediction

In the field of blood glucose prediction, the literature is abounded with algorithms that demonstrate potential in glucose management. However, these propositions face an issue common to many machine learning algorithms: the repeated reuse of datasets (overfitting) and a tendency to develop algorithms in isolation, detached from practical scenarios. Compounding these challenges is that many insulin pump vendors and continuous glucose monitor vendors use closed and proprietary protocols, restricting researchers’ data access and the ability to deploy complex, multivariate optimizers. This study seeks to bridge the gap between theoretical algorithms and their real-world applications by devising a software development kit. This kit collects real-time data from continuous glucose monitors, carbohydrate intake, insulin deliveries from insulin management systems, and metrics like physical activity, stress, and sleep from wearables. Our methodology leverages the open-source insulin management system, Loop, integrated with Apple Health and various wearable devices. Although navigating through diverse communication protocols to link these devices presented challenges, we succeeded in aggregating a comprehensive dataset for blood glucose predictions. To underscore the utility of our software development kit, we executed a technical proof-of-concept on this platform, illustrating real-time, individualized, data-driven multivariate blood glucose predictions. We hope that our platform can contribute to transforming machine learning algorithms from technical developments into actionable tools with real-world benefits in blood glucose management. It provides a foundation for researchers to refine their predictive algorithms and decision support systems within a more dynamic, data-rich environment.
The Energy of Interval-Valued Complex Neutrosophic Graph Structures: Framework, Application and Future Research Directions

Graph structure is a developing field with many real-world applications and advancements, particularly effective frameworks for integrative problem-solving in computer networks and artificial intelligence systems. To define the idea of an Interval-Valued Complex Neutrosophic Graph Structure (IVCNGS), the concept of an Interval-Valued Complex Neutrosophic Set (IVCNS) is applied to the graph structure. Using the adjacency matrix to calculate the degree of vertex, we have defined some findings about the IVCNGS. Further, we compute the energy and Laplacian energy of IVCNGS. Moreover, we derive the lower and upper bounds for the energy and Laplacian energy of IVCNGS, and we have discussed their application in IVCNGS. Finally, we develop an algorithm that clarifies the fundamental processes of the application.
Impacts of PM concentrations on visibility impairment

In the paper, an accurate and sensitive cavity attenuated phase shift spectroscopy (CAPS) sensor was used to monitor the atmospheric visibility. The CAPS system mainly includes a LED light source, a band-pass filter, an optical resonant cavity (composed of two high mirror, reflectivity is greater than 99.99%), a photoelectric detector and a lock-in amplifier. The 2L/min flow rate, the optical sensor rise and fall response time is about 15 s, so as to realize the fast measurement of visibility. An Allan variance analysis was carried out evaluating the optical system stability (and hence the maximum averaging time for the minimum detection limit) of the CAPS system. The minima (~0.1 Mm-1) in the Allan plots show the optimum average time (~100s) for optimum detection performance of the CAPS system. During this period, the extinction coefficient was correlated with PM2.5 mass (0.88), the extinction coefficient was correlated with PM10 mass (0.85). The atmospheric visibility was correlated with PM2.5 mass (0.74). The atmospheric visibility was correlated with PM10 mass (0.66).
Effect of the SBA-15 N-functionalization on the adsorption of organic contaminants

This work aimed to investigate the adsorption of selected organic molecules as models of water contaminants on unmodified and N-functionalized mesoporous silica adsorbents. In particular, ibuprofen and 4-chloro-2-methylphenoxyacetic acid (MCPA) were chosen as organic adsorbates. The surface of the mesoporous ordered silica phase containing free silanol groups was enriched with (3-aminopropyl)triethoxysilane by post-synthesis functionalization. The textural properties of synthesized silica phases were evaluated by low-temperature nitrogen adsorption–desorption iso-therms, X-ray diffraction, scanning and transmission electron microscopy, infrared spectroscopy as well as thermal analysis. The SBA-15 type ordered mesoporous silica functionalized with amino groups (SBA-15_NH 2 ) was used as the highly porous adsorbent for analyzing the carrier-drug interactions and mutual affinity. The adsorption experimental data were analyzed and well-fitted using the Freundlich, Langmuir, and Temkin isotherms. Ibuprofen was better adsorbed on SBA-15 while MCPA showed greater adsorption affinity for SBA-15_NH 2 . The better adsorption of MCPA on the N-functionalized silica was the result of interactions (hydrogen bond formation) between SBA-15_NH 2 and the adsorbate molecule. The mesoporous silica phases were also tested as carbon paste electrode (CPE) modifiers. Electrochemical measurements were conducted using cyclic voltammetry and differential pulse voltammetry. The mechanism of the electrooxidation process was controlled by diffusion. Compared with the bare (graphite) electrode, the silica-modified electrodes greatly increased the oxidation peak current of MCPA and ibuprofen. The peak current was strongly correlated with the adsorptive properties of the silica modifiers. The CPE modified by amino-functionalized SBA-15 type mesoporous silica (SBA-15_NH 2 ) showed a larger peak current and higher sensitivity for MCPA, while the CPE modified by pure silica phase electrode was much more appropriate for the detection of ibuprofen.
Leadership Style and Organizational Justice: Does Gender Matter?

Purpose: This study examines the relationship between leadership style and organizational justice among bankers in commercial banks in Kathmandu Valley. It also investigates the effect of gender on the study variables. Design/Methodology/Approach: It uses a quantitative approach comprising a self-administrated questionnaire to test hypotheses from 151 bankers. Correlation and one-way analysis of variance (ANOVA) are used for data analysis. Findings: The results suggest that a positive relationship between leadership style and organizational justice exists. Moreover, it is found that there exists a significant difference between male and female bankers in transformational leadership but not in transactional leadership. Further, gender has significant differences among bankers in relation to organizational justice and its sub-dimensions. Implications: This research could help understand the importance of leadership in banks to prevail in organizational justice. It reflects the importance of creating a diverse workforce, especially the necessity of female employees to promote fairness in the organization. Keywords: Leadership style, Gender, Transactional leadership, Transformational leadership, Organizational Justice Paper Type: Research Paper
The Impact Of Green Bond Issuance And Esg Performance On Firm Profitability: Evidence From Listed Companies In China, South Korea And Thiland

Concern on the detrimental effects of climate change is one reason for the increased global attention to sustainability issues. Significant investment is required to achieve carbon neutrality by 2050, and financing through green bonds is one alternative to fund green projects. On the other side, ESG criteria are frequently used as a measurement to assess corporations' commitment and actions toward net zero emission targets. However, whether the issuance of green bonds and ESG performance can increase profitability is still a big concern for companies. Using panel data from listed firms in China, South Korea, and Thailand from 2016 to 2022, this study employs the Difference-in-Difference (DID) model to investigate the impact of green bond issuance and ESG performance on firm profitability. Furthermore, panel data regression is used to examine the impact of green bond issuance on ESG performance. According to the findings of this study, the issuance of green bonds had no significant impact on ROA or ROE. However, according to the DID regression result, ESG performance (esg_1t) had a positive and significant effect on ROE (at a 10% significance level). This study also discovered that issuing green bonds (green_bond) had a negative and significant impact on the company's ESG performance.
3-D Object Detection With Balanced Prediction Based on Contrastive Point Loss

Object detection on point clouds is widely used in autonomous driving technology. Recent studies have demonstrated that good feature representation is the key to 3-D object detection, especially for point-based methods. Meanwhile, contrastive learning has shown its effectiveness in learning the general visual representation of images as a pretraining paradigm. Motivated by this, contrastive learning is extended to the task of object detection for better distinguishing different types of objects. In this article, a simple and effective single-stage detector, named 3-D object detection with balanced prediction based on contrastive point loss (BP-CPL), is proposed with a contrastive point loss (CPL) and a rebalanced branch (RBB). Through the CPL, similar representations among points of the same category and discriminative information among points of different categories can be learned. To keep the contrastive points consistent, a point filter is proposed. In addition, compared to the original point-wise feature, the self-supervised learned embedding is more robust to few-sample categories. Therefore, an RBB combined with the origin classification branch in a cumulative learning manner is proposed to rebalance the prediction results during the training phase. Extensive experiments show the effectiveness of the proposed method, especially for few-sample objects. The code will be available at https://github.com/Tongjiaxun/BP-CPL.
Infectious disease phylodynamics with occurrence data

Point 1 Phylodynamic models use pathogen genome sequence data to infer epidemiological dynamics. With the increasing genomic surveillance of pathogens, especially amid the SARS-CoV-2 outbreak, new practical questions about their use are emerging. Point 2 One such question focuses on the inclusion of un-sequenced case occurrence data alongside sequenced data to improve phylodynamic analyses. This approach can be particularly valuable if sequencing efforts vary over time. Point 3 Using simulations, we demonstrate that birth-death phylodynamic models can employ occurrence data to eliminate bias in estimates of the basic reproductive number due to misspecification of the sampling process. In contrast, the coalescent exponential model is robust to such sampling biases, but in the absence of a sampling model it cannot exploit occurrence data. Subsequent analysis of the SARS-CoV-2 epidemic in the northwest USA supports these results. Point 4 We conclude that occurrence data are a valuable source of information in combination with birth-death models. These data should be used to bolster phylodynamic analyses of infectious diseases and other rapidly spreading species in the future.
GENETIC DIVERSITY OF MITOCHONDRIAL DNA HAPLOGROUPS IN THE DON HORSE BREED

The Don breed of horses, which became famous in Russia already in the middle of the 18th century, was obtained by long-term crossing of nomadic horses with cultured oriental breeds. Due to the reduction in the number of Don queens to 200 broodmares, the research of the genetic characteristics of this breed is of particular relevance. The purpose of the research was to study the matrilineal structure of the Don horse breed based on phylogenetic analysis of 530 nucleotide pairs [n.p.] of the hypervariable section of the D-loop of mitochondrial DNA [mtDNA] in 26 mares representing the main female families. Analysis of the mtDNA sequence was performed using the Neighbor-Joining [NJ] method in combination with bootstrap analysis in the MEGA7 software. In the mitochondrial genomes of the tested Don horses, 26 different haplotypes were identified, which are part of 10 mtDNA haplogroups, including A, B, D, G, L, M, N, O, P, and Q, according to the modern classification. Additionally, four new haplogroups were identified, leading the line from Black Sea mares and atypical for most European breeds. The sequenced fragment of the D-loop from 15471 to 16000 n.p. included 115 polymorphic sites, mainly represented by transversions. The mtDNA structure of the Don breed was dominated by haplogroups G (19.2%), B (15.4%), and L (11.5%). All the analyzed uterine families were clearly differentiated at the level of haplogroups and haplotypes with a high bootstrap support rate (58%–100%). This indicates a high genetic diversity of the genealogical matrilineal structure of the Don horse breed.
Concept Study of Micro-Architectural Elements of Street Businesses in Pulau Tuba

The purpose of this paper is to identify the elements of street business microarchitecture (MCR) in rural areas, namely Tuba Island, Langkawi, and its significance in the local economy. The impact of Covid-19 leads to a trend of Malaysian youth who had previously migrated to the city are returning to the countryside. Hence, it encourages a better understanding of urban sustainability through classification, design, and intervention in rural areas of Malaysia using case studies from Tuba Island, Langkawi. This study uses a qualitative research approach and literature review, by recording the presence of active structure of MCR of the street businesses and the scenarios that occur in the specific area and identifies the type of microarchitecture classification based on previous studies. Interviews and observation approaches were implemented to obtain comprehensible information to gather data, which were then used in the analysis. This study finds that MCR units that are available at Pulau Tuba are mainly permanent and semi-permanent status and can be found on main roads and places of commercial activities with many visitors. MCR typoscape T8 are mostly restaurants and grocery stores, while T3, T4 and T5 are suitable for small island use as they are remote, easy to set up and ad-hoc but fixed setting.
Alternative Rupture‐Scaling Relationships for Subduction Interface and Other Offshore Environments

Abstract Alternative fault‐rupture‐scaling relationships are developed for M w 7.1–9.5 subduction interface earthquakes using a new database of consistently derived finite‐fault rupture models from teleseismic inversion. Scaling relationships are derived for rupture area, rupture length, rupture width, maximum slip, and average slip. These relationships apply width saturation for large‐magnitude interface earthquakes (approximately M w >8.6) for which the physical characteristics of subduction zones limit the depth extent of seismogenic rupture, and consequently, the down‐dip limit of strong ground motion generation. On average, the down‐dip rupture width for interface earthquakes saturates near 200 km (196 km on average). Accordingly, the reinterpretation of rupture‐area scaling for subduction interface earthquakes through the use of a bilinear scaling model suggests that rupture asperity area is less well correlated with magnitude for earthquakes M w >8.6. Consequently, the size of great‐magnitude earthquakes appears to be more strongly controlled by the average slip across asperities. The sensitivity of the interface scaling relationships is evaluated against geographic region (or subduction zone) and average dip along the rupture interface to assess the need for correction factors. Although regional perturbations in fault‐rupture scaling could be identified, statistical significance analyses suggest there is little rationale for implementing regional correction factors based on the limited number of interface rupture models available for each region. Fault‐rupture‐scaling relationships are also developed for intraslab (within the subducting slab), extensional outer‐rise and offshore strike‐slip environments. For these environments, the rupture width and area scaling properties yield smaller dimensions than interface ruptures for the corresponding magnitude. However, average and maximum slip metrics yield larger values than interface events. These observations reflect both the narrower fault widths and higher stress drops in these faulting environments. Although expressing significantly different rupture‐scaling properties from earthquakes in subduction environments, the characteristics of offshore strike‐slip earthquake ruptures compare similarly to commonly used rupture‐scaling relationships for onshore strike‐slip earthquakes. Electronic Supplement: Table of rupture parameters.
Neural field theory of adaptive effects on auditory evoked responses and mismatch negativity in multifrequency stimulus sequences

Physiologically based neural field theory (NFT) of the corticothalamic system, including adaptation, is used to calculate the responses evoked by trains of auditory stimuli that differ in frequency. In oddball paradigms, fully distinguishable frequencies lead to different standard (common stimulus) and deviant (rare stimulus) responses; the signal obtained by subtracting the standard response from the deviant is termed the mismatch negativity (MMN). In this analysis, deviant responses are found to correspond to unadapted cortex, whereas the part of auditory cortex that processes the standard stimuli adapts over several stimulus presentations until the final standard response form is achieved. No higher-order memory processes are invoked. In multifrequency experiments, the deviant response approaches the standard one as the deviant frequency approaches that of the standard and analytic criteria for this effect to be obtained. It is shown that these criteria can also be used to understand adaptation in random tone sequences. A method of probing MMNs and adaptation in random tone sequences is suggested to makes more use of such data.
Chemodiversity affects preference for Tanacetum vulgare chemotypes in two aphid 1 species 2

12 Plants of the same species often strongly differ in morphological traits, as well as in the 13 abundance and composition of specialized metabolite profiles. Specialized metabolites can 14 act as mediators of interactions on plants, and partially explain insect presence and 15 abundance in the field. However, how specialized chemistry shapes plant attractiveness to 16 herbivorous insects is not fully understood. Here we used common tansy ( Tanacetum 17 vulgare L., Asteraceae) – a perennial plant that is highly diverse in terpenoid composition 18 and is known to have variable chemotypes – to test whether 1) plants with different 19 chemotype profiles differ in attractiveness to two specialized aphids, Macrosiphoniella 20 tanacetaria and Uroleucon tanaceti , in pairwise choice assays. Furthermore, we tested 21 whether 2) the diversity of the terpenoid blend affects aphid attractiveness. Lastly, we tested 22 how 3) plant chemical traits relate to plant morphological traits, and which best explain aphid 23
Water Quality Sampling Under Preferential Flow Conditions

Shallow wells, porous cup samplers, and wick and gravity pan lysimeters were used to observe the movement of bromide applied to the surface of a grass covered field during a 23 day period. The observed concentrations not only varied spatially over short distances, but more importantly, were significantly affected by the sampling device employed. Wick pan lysimeters are shown to be superior in determining loading to groundwater for the silt loam soil in the zone above the capillary fringe. Porous cup samplers in the capillary fringe also yielded consistent samples of the quality of water entering the aquifer as verified from shallow wells.
Comparative Analysis of Loss Mechanism Localization in a Semi-2D SOEC Single Cell Modell: Non-Equilibrium Thermodynamics versus Monocausal-Based Approach

This study aims to theoretically analyze the local entropy production rate in a SOEC single cell at T = 1123.15 K and p = 1 bar. Local entropy rates signify loss mechanisms, crucial for cell design and optimization. A semi-2D SOEC model based on non-equilibrium thermodynamics is developed, supplemented by monocausal correlations for direct comparison. The model is validated using KeraCell III data and grid independence analysis. Simulations of electric current density, temperature, heat flow, and local entropy production for various SOEC operating modes are presented. Coupled transport mechanisms significance is discussed, highlighting the pronounced impact of the Peltier effect on heat flux and temperature. The importance of the Peltier effect in SOECs compared to SOFCs is emphasised. The effects of the Seebeck effect on the potential distribution are superimposed by the dominant ohmic losses in the electrolyte. The localization of entropy production rates shows for exothermic operation that 66.6% of the total losses are due to the predominantly dominant irreversible ion transport in the electrolyte, while the entanglements in the reaction layers contribute 33% and GDLs less than 1%.
Simplified structural map of Kras; Kras (Slovene), Carso (Italian) = Geographical unit

With this contribution comes a printed copy of the Simplified structural map of Kras, comprising an area on both sides of the state border between Slovenia and Italy, as well as its short description. The map conveys updated information on faults and newly discovered geomorphologically indicated joint-fault zones in the area. Izvle~ek Prispevek prina{a natis Poenostavljene strukturno-geolo{ke karte Krasa, ki zajema ozemlje na slovenski in italijanski strani državne meje ter kratek opis. Karta vsebuje dopolnjene podatke o poteku prelomov in o novoodkritih geomorfolo{ko izraženih razpoklinsko-prelomnih conah.
Enhancing public information quality during the Covid-19 pandemic: A cyber public relations strategy on local government initiatives

The Covid-19 pandemic has induced widespread fear, emphasizing the imperative for high-quality public information dissemination to alleviate societal anxiety. This research examined the Cyber Public Relations (Cyber PR) strategies implemented by the Communication and Informatics Office or Dinas Komunikasi dan Informatika (Diskominfo) of Jepara Regency in disseminating quality public information during the ongoing pandemic. Utilizing a qualitative case study methodology, the study focused on the efforts of Diskominfo Jepara to enhance public information quality, specifically related to Covid-19 data updates, health protocol campaigns, and the Covid-19 vaccination campaign. Data collection involved in-depth interviews, observations, and documentation. The analysis employed the Cyber PR framework, assessing dimensions such as strategic, integrated, targeted, and measurable, alongside indicators like intrinsic, contextual, representational, and accessibility for scrutinizing public information quality. Findings revealed some key elements in Diskominfo Jepara's Cyber PR strategies, including the establishment of a comprehensive digital media center, active engagement with media outlets, collaborations with influencers, and the utilization of Key Opinion Leaders (KOLs). These strategies have been intricately developed based on situational analysis and predefined communication objectives. The research contributes significantly to the academic literature on Cyber PR in local government contexts, providing nuanced insights and enriching the reference landscape.