Miracle-dz/UniFAR-FTUs huggingface dataset:
Risk Assessment of Whale Entanglement and Vessel Strike Injuries From Case Narratives and Classification Trees

Entanglements and vessel strikes impact large whales worldwide. Post-event health status is often unknown because whales are seen once or over short spans that conceal long-term health declines. Well-studied populations with high site fidelity verified by photo-ID offer opportunity to confirm deaths, health declines and recoveries. We used known outcome entanglements and vessel strikes of right whales (Eubalaena glacialis) and humpback whales (Megaptera novaeangliae) to model probabilities of deaths, health declines and recoveries with Random Forest (RF) classification trees. Variables included presence or absence of phrases from case narratives (‘deep laceration’, ‘cyamid’, ‘healing’, ‘superficial’) and a categorical variable for vessel size. Health status post-entanglement was correctly classified in 95.7% of right whale and 93.6% of humpback whale cases (expected by chance=50%). Health status post-vessel strike was correctly classified in 91.4% of right whale and 88.6% of humpback whale cases. Important variables included cyamid presence, emaciation, discolored skin, constricting entanglements, gear-free resightings, superficial or healing lacerations, and vessel size. Cross-validated RF models were applied to unknown outcome cases to estimate the probability of deaths, health declines and recoveries. Total serious injuries (probability of death or health decline > 0.50) assigned by RF were nearly equal to current injury assessment methods applied by biologists for known outcomes. However, RF consistently predicted higher serious injury totals for unknown outcomes, suggesting that current assessment methods may underestimate risk for cases lacking details or long-term observations. Advantages of the RF method include: 1) risk models are based on known outcomes; 2) unknown outcomes are assigned post-event health status probabilities; and 3) identification of important predictor variables improves data collection standards.
Flowers and Leaves Extracts of Stachys palustris L. Exhibit Stronger Anti-Proliferative, Antioxidant, Anti-Diabetic, and Anti-Obesity Potencies than Stems and Roots Due to More Phenolic Compounds as Revealed by UPLC-PDA-ESI-TQD-MS/MS

The present work aims to assess the biological potential of polyphenolic compounds in different parts (flowers, leaves, stems, and roots) of Stachys palustris L. Towards secondary metabolites profile, 89 polyphenolic compounds (PCs) were identified by UPLC-PDA-ESI-TQD-MS/MS, with a total average content of 6089 mg/100 g of dry matter (d.m.). In terms of biological activity, antioxidant activity (radical activity, reducing power), digestive enzyme inhibitory (α-glucosidase, α-amylase, pancreatic lipase) effect, and antiproliferative activity (inhibition of cell viability and induction of apoptosis in different human cancer cell lines) were explored. Leaves, flowers, stems, and roots of S. palustris L. have not been studied in this regard until now. Vescalagin and cocciferin d2, isoverbascoside (verbascoside), luteolin 6-C-glucoside, luteolin 6-C-galactoside, apigenin 6-C-glucoside, (−)-epicatechin, ellagic acid, and malvidin 3-O-diglucoside were detected as main ingredients in the studied parts. Methanolic extract of S. palustris L. leaves and flowers revealed the highest amount of PCs with the strongest antiradical (18.5 and 15.6 mmol Trolox equivalent (TE)/g d.m. , respectively) and reducing power effects (7.3 and 5.6 mmol TE/g d.m.). Leaf extracts exhibited better α-amylase and pancreatic lipase inhibition effects, while flower extracts exhibited better α-glucosidase inhibition effect. Regarding antiproliferative activity, extracts of the leaves and flowers significantly reduced cell viability and induced a high level of apoptosis in human lung, pancreatic, bladder, and colon cancer cell lines, as well as in human acute myeloid leukemia; whereas the extracts from stems and roots revealed the weaker effects. The results of this work showed anti-proliferative and potentially anti-diabetic, anti-obesity properties of S. palustris L. , especially for flowers and leaves, which may have wide potential applications in the functional food, special food, pharmaceutical, cosmetics industries, and/or in medicine.
Design and Preliminary Testing of a Quadleaflet ePTFE Pediatric Prosthetic Heart Valve

In the United States, congenital heart defects affect nearly 40,000 births each year and often will require heart valve replacement [1]. Viable prosthetic heart valve options are limited for pediatric patients that need a valve smaller than 16mm in diameter. When commercially available valve sizes are not available, surgeons often handcraft a valve using expanded polytetrafluoroethylene (ePTFE) to fabricate a valve that is small enough to meet the size constraints of young pediatric patients. There is limited published hemodynamic data for ePTFE valves. A comparison between the two ePTFE handmade valves (trileaflet and quadleaflet) demonstrated hemodynamic differences in regurgitation due to leaflet number. The handmade valves both showed increased regurgitation compared to a Carbomedics valve (commercially available design). Regurgitation had varying effects on pressure gradients and cardiac output. The aim of this paper is to: 1) showcase the design process of a quadleaflet ePTFE valved conduit with a diameter of 16mm or less and 2) offer a hemodynamic performance comparison.
A CNFET-based hybrid multi-threshold 1-bit full adder design for energy efficient low power applications

ABSTRACT In this article, a low-power and energy-efficient hybrid full adder circuit is proposed, which is implemented based on multi-threshold NAND and NOR gates and transmission gate multiplexers. In order to implement this circuit, carbon nano tube field effect transistors are utilised. For evaluating the proposed design, comprehensive simulations are performed with regard to the most important aspects power, delay and power-delay product. The results are presented and displayed the superiority of the proposed cell in different voltage levels, load conditions, temperatures and robustness against process variations.
ACCESS TO JUSTICE OF PLEA BARGAINING IN ADDRESSING THE CHALLENGE OF TAX CRIME IN INDONESIA

It is crucial and urgent to construct the prevailing law of plea bargaining in the x-factor to generate the ideal of plea bargaining in addressing the challenge of tax crime in Indonesia based on access to the justice concept. The purpose of this study is to show that the use of the normative juridical method is adequate in answering the formulation of existing problems and, at the same time, providing constructive suggestions for these legal issues. Several facts, such as the number of tax crimes and the amount of loss in state revenues that arise, indicate the need to consider law enforcement in the field of taxation with a sociological perspective, one of which is by producing a legal concept in plea bargaining in the taxation sector. Of course, the ideal tax enforcement in renewing plea bargaining in taxes is sufficient to use the idea of access to justice. It is necessary to study legal empiricism on direct taxpayers. However, this normative study can enrich the study of legal empiricism in subsequent research. Access to justice is ideal in building plea bargaining to handle the challenges of tax crimes in Indonesia. The building of the access to justice concept includes regulating taxpayers' good faith, granting taxpayer rights in plea bargaining, and updating the rules for criminal sanctions for fines at each stage of authority.
Clinical characteristics and prognostic analysis of multiple primary malignant neoplasms in female patients with breast cancer or genitalia malignancies

Background As public awareness of health has increased and diagnostic and treatment options have improved, the survival of patients with malignant tumors has continued to extend, and the population has been aging, the number of multiple primary malignant neoplasms has gradually increased in recent years. There are few reports concerning female patients with multiple primary malignant neoplasms of breast cancer or genitalia malignancies. In this study, we aimed to analyze the clinical characteristics and prognosis of multiple primary malignant neoplasms in female patients with breast cancer or genitalia malignancies, as well as further explore the factors that affect the survival. Methods We collected clinical data on 80 female patients diagnosed with multiple primary malignant neoplasms of the breast or genitalia, described their clinical features. Furthermore, we calculated the survival and prognostic factors for 52 participants. Results In our study, the prevalence rate of multiple primary malignant neoplasms was 0.66% (367/55404). Corresponding to female patients with multiple primary malignant neoplasms of breast cancer or genitalia malignancies, it was 1.4% (80/5707). the median age of diagnosis for the first tumor was 48 years, and the median age of diagnosis for the second tumor was 52 years. Regarding the interval, 67.57% (50/74) of patients were within five years. Most tumors were located in the breast (44.68%), followed by the uterus (20.21%), the ovary (17.02%), and the cervix (15.96%). The overall 12-, 36-and 60-month survival rates of the patients were 86.4%, 74.3%, and 69.8%. For the female patients, the stage (III–IV) (P = 0.046), non-radical surgery (P = 0.002), and types of the last tumor (breast cancer or genitalia malignancies) (P = 0.019) were associated with the poor prognosis. Conclusions Female patients with breast cancer or genital malignancies should pay attention to screening for the second tumor, especially within 4 years after the first tumor diagnosed. Furthermore, during tumor screening, it may be recommended for these patients to focus on colorectal cancer and lung cancer. Compared with previous studies, in addition to clinical staging and types of surgery, we found whether the last tumor was breast cancer or genitalia malignancies should also be considered a prognostic factor.
Deep Learning Radiomics Nomogram to Predict Lung Metastasis in Soft-Tissue Sarcoma: A Multi-Center Study

Objectives To build and evaluate a deep learning radiomics nomogram (DLRN) for preoperative prediction of lung metastasis (LM) status in patients with soft tissue sarcoma (STS). Methods In total, 242 patients with STS (training set, n=116; external validation set, n=126) who underwent magnetic resonance imaging were retrospectively enrolled in this study. We identified independent predictors for LM-status and evaluated their performance. The minimum redundancy maximum relevance (mRMR) method and least absolute shrinkage and selection operator (LASSO) algorithm were adopted to screen radiomics features. Logistic regression, decision tree, random forest, support vector machine (SVM), and adaptive boosting classifiers were compared for their ability to predict LM. To overcome the imbalanced distribution of the LM data, we retrained each machine-learning classifier using the synthetic minority over-sampling technique (SMOTE). A DLRN combining the independent clinical predictors with the best performing radiomics prediction signature (mRMR+LASSO+SVM+SMOTE) was established. Area under the receiver operating characteristics curve (AUC), calibration curves, and decision curve analysis (DCA) were used to assess the performance and clinical applicability of the models. Result Comparisons of the AUC values applied to the external validation set revealed that the DLRN model (AUC=0.833) showed better prediction performance than the clinical model (AUC=0.664) and radiomics model (AUC=0.799). The calibration curves indicated good calibration efficiency and the DCA showed the DLRN model to have greater clinical applicability than the other two models. Conclusion The DLRN was shown to be an accurate and efficient tool for LM-status prediction in STS.
Fully Integrated Low-Ripple Switched-Capacitor DC–DC Converter with Parallel Low-Dropout Regulator

In this paper, we propose a fully integrated switched-capacitor DC–DC converter with low ripple and fast transient response for portable low-power electronic devices. The proposed converter reduces the output ripple by filtering the control ripple via combining a low-dropout regulator with a main switched-capacitor DC–DC converter with a four-bit digital capacitance modulation control. In addition, the four-phase interleaved technique applied to the main converter reduces the switching ripple. The proposed converter provides an output voltage ranging from 1.2 to 1.5 V from a 3.3 V supply. Its peak efficiency reaches 73% with ripple voltages below 55 mV over the entire output power range. The transient response time for a load current variation from 100 μA to 50 mA is measured to be 800 ns. Importantly, the converter chip, which is fabricated using 0.13 μm complementary metal–oxide–semiconductor (CMOS) technology, has a size of 2.04 mm2. We believe that our approach can contribute to advancements in power sources for applications such as wearable electronics and the Internet of Things.
Entwicklung eines neuartigen leichten Deckenträgers aus Carbonbeton

Carbonbeton ermöglicht dünne Querschnitte und leichte, hochfeste Tragwerke. Dies wird im vorliegenden Beitrag am Beispiel eines leichten, vorgefertigten Deckenträgers demonstriert, der einfach montierbar z. B. als Ersatz von sanierungsbedürftigen Trägern in Bestandsbauten einsetzbar wäre. Hierbei kommt ein neuartiges zementgebundenes Verbundmaterial, bestehend aus Schichten von betongetränkten Nadelvliesstoffen sowie carbonbewehrtem Feinbeton, zur Anwendung, mit feiner Rissbildung und hoher Duktilität. Der Träger ist als dünne zylindrische Schale mit seitlichen Stegen konzipiert. Neben Material, Entwurf und Herstellung beschreibt der Beitrag experimentelle und numerische Untersuchungen zum Spannungs‐Dehnungsverhalten des Verbundmaterials sowie zum Tragverhalten des Deckenträgers. Bei geringem Gewicht wird eine sehr hohe Tragfähigkeit nachgewiesen, welche die Gebrauchslasten um ein Vielfaches überschreitet. Entwurf sowie experimentelle und rechnerische Analysen sind exemplarisch und sollten ein größeres Anwendungsspektrum ermöglichen.
On the Effects of Various Measures of Performance Selections on Simulation Model Calibration Performance

Objective. This paper examines the effects of various measures of performance (MOP) selections on simulation model calibration performance, in terms of reflecting actual traffic conditions and vehicle interactions. Method. Two intersections in Shanghai were selected for simulation model calibration, one for testing and another for validation. Three effective MOPs were utilized, including average travel time (i.e., time passing the intersection), average queue length, and vehicle headway distribution. The counts of three types of traffic conflicts (i.e., crossing, rear-end, and lane change) were used as safety MOPs. Those MOPs, as calibration objectives, were examined and compared. Results. The results of the testing site showed that different effective MOPs had their own advantages: average travel time appeared to be the best in reflecting lane change and rear-end conflicts while headway distribution performed the best consistency between simulated and actual crossing conflicts. Compared to the safety MOPs, average travel time and headway distribution still performed better, in terms of resulting in more similar simulated conflict metrics (e.g., TTC, PET) to actual ones. A multicriteria calibration strategy based on average travel time and headway distribution generally had better performances in reflecting actual traffic conditions and vehicle interactions than using any single effective or safety MOP. Similar results were found for the validation site. Conclusion. To simulate actual traffic conditions and vehicle interactions, multiple effective MOPs could be simultaneously considered for model calibration, instead of using safety MOPs.
Optimizing time delay in cloud using enhanced multi‐hold inherited maximization algorithm to reduce cost and improve bandwidth

Optimizing the time delay in the cloud is one of the essential parameters to be considered for providing an efficient environment for the user to work. Virtual machine (VM) allocation is performed on various heuristic and genetic algorithms (GAs) to schedule the VM to the users in lesser time. However, the scheduling mechanisms do not provide the best serving VM among different data centres. This paper proposes an Enhanced multi‐hold inherited maximization (Enhanced MHIM) algorithm to provide an optimal allocation of VMs across multiple geographically distributed data centres. Based on load information shared between the various data centres, the algorithm computes the best performing machine among the data centres and shares the template for allocating the new device to the user. As a result, the workload is completed quicker by assigning to each user optimally. Heuristic scheduling algorithms, including Min‐Min, Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), and GA, are compared with the proposed algorithm. Experimental results indicate that the proposed algorithm is efficient by maximum reduction of 12.63% of the makespan time, 13.06% of execution time, 3.89% of computational cost, and producing the 3× times best serving VM.
Colloidal Synthesis and Photocatalytic Properties of Cu3NbS4 and Cu3NbSe4 Sulvanite Nanocrystals

Niobium sulvanites Cu3NbX4 (X = S, Se) have been theoretically predicted as promising candidates for solar photovoltaics and photocatalytic water splitting. This report outlines the first synthesis of Cu3NbS4 and Cu3NbSe4 in a nanocrystalline form. The crystal structures were investigated by X-ray diffraction, identity was confirmed by Raman spectroscopy, and the optoelectronic properties and morphology of Cu3NbS4 and Cu3NbSe4 nanocrystals were examined by UV–vis spectroscopy and transmission electron microscopy, respectively. To gain insight into the Cu3NbX4 formation, a mechanistic study was conducted for Cu3NbSe4 monitoring the nanoparticles’ formation as a function of reaction time. Methylene blue photodegradation tests were conducted to evaluate the photoactivity of Cu3NbS4 and Cu3NbSe4. The degradation rates, 2.81 × 10–2 min–1 and 1.22 × 10–2 min–1 proved the photocatalysts’ potential of nanoscale Cu3NbX4.
EFFECT OF LOYALTY PROGRAM ADVANTAGES TOWARDS SATISFACTION AND BRAND LOYALTY: INDONESIAN BUBBLE TEA INDUSTRY

Tujuan dari penelitian ini adalah untuk mengevaluasi hubungan antara berbagai jenis program loyalitas (praktis, hedonis dan simbolik), kepuasan program dan loyalitas e-commerce (loyalitas program dan loyalitas e-commerce) terkait dengan minuman bubble tea Indonesia. Sebanyak 389 kuesioner dikumpulkan di antara anggota pelanggan bubble tea Indonesia menggunakan purposive sampling. Hubungan antara variabel-variabel yang diusulkan diuji dengan menggunakan model Persamaan Struktural Partial Least Square (PLSSEM). Hasil penelitian menunjukkan bahwa di antara ketiga keunggulan (praktis, hedonis, dan simbolik), hanya keunggulan hedonis dan simbolik yang berpengaruh positif signifikan terhadap kepuasan program. Selain itu, kepuasan program telah terbukti memberikan kontribusi yang signifikan dan positif terhadap program dan loyalitas merek. Ditemukan pula bahwa loyalitas program berpengaruh positif terhadap loyalitas merek. The study aims to shed light on the connection between different type of loyalty programs (practical, hedonic and symbolic), towards program satisfaction and customer loyalty (loyalty to the program and loyalty to the brand) related to Indonesian bubble tea beverages. A total of 389 questionnaires were collected amongst members of the Indonesian bubble tea customers using convenience sampling. The degree of significance between variables was tested using a Partial Least Square Structural Equation modeling (PLS-SEM). Acquired data and analysis infer that among the three advantages (practical, hedonic, and symbolic), only hedonic and symbolic advantages have a significant positive impact on program satisfaction. In addition, program satisfaction has been shown to make a significant and positive contribution to program and brand loyalty. Finally, it is found that program loyalty has a positive effect on brand loyalty.
Case Report: The First Report on Moraxella canis Isolation From Corneal Ulcer in a Bulldog

A 5-year-old castrated male bulldog was diagnosed with a corneal ulcer accompanied by edema and conjunctival hyperemia. Ophthalmic examination and microbiological analysis were performed, and the bacteria were found to be gram-negative and globular. The isolated clone was identified as Moraxella canis (MZ579539) via MALDI-TOF MS and 16S rDNA sequencing. Antimicrobial susceptibility testing showed that the bacteria were sensitive to tetracycline and chloramphenicol, but resistant to levofloxacin and ciprofloxacin. After a conjunctival flap was placed, tobramycin ophthalmic solution and 5% sodium hyaluronate were administered. Following surgery, the ulcer was effectively controlled, and after 3 weeks, the cornea healed. This is the first case report of a canine corneal ulcer associated with M. canis, which should be considered when corneal ulceration or keratitis were suspected.
Industrie 4.0 : Competencies for a modern production system

Under the concept of "Industry 4.0", production processes will be pushed to be increasingly interconnected, information based on a real time basis and, necessarily, much more efficient. In this context, capacity optimization goes beyond the traditional aim of capacity maximization, contributing also for organization’s profitability and value. Indeed, lean management and continuous improvement approaches suggest capacity optimization instead of maximization. The study of capacity optimization and costing models is an important research topic that deserves contributions from both the practical and theoretical perspectives. This paper presents and discusses a mathematical model for capacity management based on different costing models (ABC and TDABC). A generic model has been developed and it was used to analyze idle capacity and to design strategies towards the maximization of organization’s value. The trade-off capacity maximization vs operational efficiency is highlighted and it is shown that capacity optimization might hide operational inefficiency. © 2017 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the scientific committee of the Manufacturing Engineering Society International Conference 2017.
Encapsulation of Caffeic Acid in Carob Bean Flour and Whey Protein-Based Nanofibers via Electrospinning

The purpose of this study was to introduce caffeic acid (CA) into electrospun nanofibers made of carob flour, whey protein concentrate (WPC), and polyethylene oxide (PEO). The effects of WPC concentration (1% and 3%) and CA additions (1% and 10%) on the characteristics of solutions and nanofibers were investigated. The viscosity and electrical conductivity of the solutions were examined to determine characteristics of solutions. Scanning electron microscopy (SEM), X-ray diffraction (XRD), thermogravimetric analyzer (TGA), differential scanning calorimetry (DSC), water vapor permeability (WVP), and Fourier transform infrared (FTIR) analysis were used to characterize the nanofibers. According to the SEM results, the inclusion of CA into nanofibers resulted in thinner nanofibers. All nanofibers exhibited uniform morphology. CA was efficiently loaded into nanofibers. When CA concentrations were 1% and 10%, loading efficiencies were 76.4% and 94%, respectively. Nanofibers containing 10% CA demonstrated 92.95% antioxidant activity. The results indicate that encapsulating CA into carob flour–WPC-based nanofibers via electrospinning is a suitable method for active packaging applications.