Miracle-dz/UniFAR-FTUs huggingface dataset:
Extraction of keywords in the abstract of scientifics papers using BERT

Keywords are used to facilitate searches, inaccurate keyword determination, which can result in searches for journals that do not match the intended title. To overcome this, it is necessary to implement a keyword search in the abstract using deep learning methods from a journal to produce the right keywords that will distinguish journals from one another. The purpose of this study is to implement a keyword search system in abstracts using the Bidirectional Encoder Representations from Transformers (BERT) method as an abstract word search system that produces keyword answers that have context according to the desired keyword results. The results of this study get optimal results in the epoch 500, and from these results using a dataset with of 444 training data and 10 test data for testing.
Influence of defects and doping on phonon transport properties of monolayer MoSe2

The doping of monolayer MoSe2 by tungsten (W) can suppress the Se vacancy concentration, but how doping and resulting change in defect concentration can tune its thermal properties is not understood yet. We use first-principles density functional theory (DFT) along with the phonon Boltzmann transport equation (BTE) to study the phonon transport properties of pristine MoSe2 and W doped MoSe2 with and without the presence of Se vacancies. We found that for samples without Se vacancy, the W doping could enhance the thermal transport of monolayer MoSe2 due to reduced three-phonon scattering phase space. For example, we observed that the 16.7% W doping increases the thermal conductivity of the monolayer MoSe2 with 2% Se vacancy by 80% if all vacancies can be suppressed by W-doping. However, the W doping in the defective MoSe2 amplifies the influence of the phonon scattering caused by the Se vacancies, which results in a further decrease in thermal conductivity of monolayer MoSe2 with defects. This is found to be related with higher phonon density of states of Mo0.83W0. 17Se2 and larger mass difference between W and Se atoms compared to Mo and Se atoms. This study deciphers the effect of defects and doping on the thermal conductivity of monolayer MoSe2, which helps us understand the mechanism of defect-induced phonon transport, and provides insights into enhancing the heat dissipation in MoSe2-based electronic devices.
Multi-Label ECG Classification Using Convolutional Neural Networks in a Classifier Chain

Over the last decade, AI has shown its feasibility in classifying heart-related diagnoses from ECGs. Earlier studies have mainly focused on 12 and 2-lead ECGs, but we aim to classify 26 different diagnoses based on 12, 6, 4, 3, and 2-lead ECGs in this study. We trained a supervised model on a dataset containing 88 253 ECGs with 26 different diagnoses used as ground truth. The training and classification steps can be separated into three parts. (1) Pan Tompkins algorithm was used to find peaks and calculate the average heart rate. (2) The average heart rate and the Fourier transformed ECG signal was used to train convolutional neural networks (CNN) system that classified the ECGs with regular or irregular rhythms. 9 out of 26 classes were classified in this step. (3) Finally, CNN models in a classifier chain were trained to classify the remaining 17 diagnoses. The classification results from step 2 and the raw ECG signal were used as input to the classifier chain in step 3. Our team, CardiOUS, achieved a PhysioNet Challenge score of −0.63 for all sets of leads on the hidden test set. Based on the test score, our team placed at 38th out of 39 teams in the official ranking.
Luminescent Nanosensors for Ratiometric Monitoring of Three-Dimensional Oxygen Gradients in Laboratory and Clinical <named-content content-type='genus-species'>Pseudomonas aeruginosa</named-content> Biofilms

Bacterial biofilms can form persistent infections on wounds and implanted medical devices and are associated with many chronic diseases, such as cystic fibrosis. These infections are medically difficult to treat, as biofilms are more resistant to antibiotic attack than their planktonic counterparts. An understanding of the spatial and temporal variation in the metabolism of biofilms is a critical component toward improved biofilm treatments. To this end, we developed oxygen-sensitive luminescent nanosensors to measure three-dimensional (3D) oxygen gradients, an application of which is demonstrated here with Pseudomonas aeruginosa biofilms. The method was applied here and improves on traditional one-dimensional (1D) methods of measuring oxygen profiles by investigating the spatial and temporal variation of oxygen concentration when biofilms are challenged with antibiotic attack. We observed an increased oxygenation of biofilms that was consistent with cell death from comparisons with antibiotic kill curves for PAO1. Due to the spatial and temporal nature of our approach, we also identified spatial and temporal inhomogeneities in the biofilm metabolism that are consistent with previous observations. Clinical strains of P. aeruginosa subjected to similar interrogation showed variations in resistance to colistin and tobramycin, which are two antibiotics commonly used to treat P. aeruginosa infections in cystic fibrosis patients. IMPORTANCE Biofilm infections are more difficult to treat than planktonic infections for a variety of reasons, such as decreased antibiotic penetration. Their complex structure makes biofilms challenging to study without disruption. To address this limitation, we developed and demonstrated oxygen-sensitive luminescent nanosensors that can be incorporated into biofilms for studying oxygen penetration, distribution, and antibiotic efficacy— demonstrated here with our sensors monitoring antibiotic impacts on metabolism in biofilms formed from clinical isolates. The significance of our research is in demonstrating not only a nondisruptive method for imaging and measuring oxygen in biofilms but also that this nanoparticle-based sensing platform can be modified to measure many different ions and small molecule analytes.
Mechanism Development and Position Control of Smart Buoy Robot

There is a gradual increase in the need for energy charging in marine environments because of energy limitations experienced by electric ships and marine robots. Buoys are considered potential energy charging systems, but there are several challenges, which include the need to maintain a fixed position and avoid hazards, dock with ships and robots in order to charge them, be robust to actions by birds, ships, and robots. To solve these problems, this study proposes a smart buoy robot that has multiple thrusters, multiple docking and charging parts, a bird spike, a radar reflector, a light, a camera, and an anchor, and its mechanism is developed. To verify the performance of the smart buoy robot, the position control under disturbance due to wave currents and functional tests such as docking, charging, lighting, and anchoring are performed. Experimental results show that the smart buoy robot can operate under disturbances and is functionally effective. Therefore, the smart buoy robot is suitable as an energy charging system and has potential in realistic applications.
VERBUS: A Formal Model for Business Process Verification

Business process management is a key issue in B2B. Different process modelling languages and workflow management tools and frameworks have appeared to aid the development, deployment and management of e-commerce solutions. Nevertheless, there is not yet a framework to compel with tasks such as guaranteeing: safety outcomes of the run of a composition of processes, the eventual execution of processes under some condition, or the soundness of a design with respect to the specification. This is the mission of formal methods, and they have been successfully applied in the fields of real-time software, hardware verification, and a growing list of application areas as the computation costs decrease. In this article we present VERBUS, a formal system for the modelling and verification of business processes. VERBUS allows a designer to specify properties for verification. The Finite State Machine theory is under the hood of VERBUS, providing the designer with a well-known and understandable approach, which offers a set of existing tools for verification or for compiling to other formats for the application of model–checkers.
The Response of Sobaity Sea Bream Sparidentex
hasta Larvae to the Toxicity of Dispersed
and Undispersed Oil

Accidental oil spillages can release millions of barrels of oil into the marine environment threatening aquatic wildlife like fisheries. As a part of the oil spill response strategy, several chemical dispersants have been recommended that have been successfully used elsewhere. However, the adverse effects of dispersed oil are unknown to fish species in Kuwait. Therefore, this study investigated the toxicity of water-accommodated fraction (WAF) and chemically enhanced water-accommodated fraction (CEWAF) of Kuwait crude oil (KCO) with three dispersants (Corexit® 9500, Corexit® 9527, and Slickgone® NS) against the larvae of the sobaity sea bream Sparidentex hasta which is of an international economic significance. Total petroleum hydrocarbons (TPH) were used for comparison of chemical compounds partitioned in WAF of dispersed and non-dispersed oil. Toxicity test results with fish larvae showed that WAF of non-dispersed oil and Corexit® 9527 treated CEWAF had similar LC50 values (0.12 g oil. l -1) whereas CEWAF’s of Corexit® 9500 and Slickgone® NS CEWAF showed lower toxicity.
Reaction-Diffusion Modelling for the Cross-Linking of Actin Gels

We expand upon the Split Reactive Brownian Dynamics (SRBD) algorithm for reaction-diffusion modelling, whereby particles diffuse, and also react when within a chosen reactive radius. We extend this algorithm to allow for the numerical simulation of dimers. To do so, we employ several temporal integrators to simulate Langevin stochastic differential equations, and assess their convergence properties. We investigate the various competing time scales that are relevant to the simulation of dimers, and develop a new integration scheme for evolving Brownian motion on the unit sphere. We show that this integration scheme minimizes inaccuracies and numerical instability in our model, especially when solving stiff equations.
Distortion Product Otoacoustic Emissions (DPOAE) patterns in individuals with Type 1 and Type 2 Diabetes Mellitus - A comparative study

Diabetes mellitus (DM) is a chronic and potentially life-threatening condition, incidence of which is increasing rapidly in the present era. Various studies showed conflicting relationship between DM and Hearing Loss (HL). The current study was carried out to find the effect of Type 1 and Type 2 DM on hearing. The study group consisted of 90 adults in the age range of 20 to 40 years from various hospitals in and around Calicut, Kerala. These participants were divided into three groups: Group1 (Experimental group 1), included 30 individuals with Type 1 DM; Group 2 (Experimental group 2), included 30 individuals with Type 2 DM and Group 3 (Control group) included 30 age-matched non-diabetic individuals with normal hearing sensitivity. Results of the study revealed that there was significant difference in the DPOAE amplitude between Type 1 and Type 2 DM with control group and there was no significant difference in the DPOAE amplitude between Type 1 and Type 2 DM group. From the results it can be concluded that DPOAE amplitude were reduced in both Type 1 and Type 2 DM when compared to control group. This could be attributed to damage of the cochlear Outer Hair Cells (OHCs). Further, it could be assumed that damage to the OHCs due to DM in both Type 1 and Type 2 groups are relatively equal.
Trampoline variables: a general method for state accumulation in reactive programming

Reactive programming is all about relegating the management of a program’s state changes to the realm of the runtime environment. Nevertheless, sometimes it is still necessary to enrich a reactive program with state variables that are explicitly updated by the programmer. In current reactive languages this is accomplished either by polluting the reactive paradigm with imperative constructs or by relying on built-in operators such as foldp. This paper introduces trampoline variables, a new general mechanism that allows reactive programs to manipulate state explicitly without resorting to imperative programming. We show that our proposal is at least as powerful as existing built-in reactive operators. We also analyse how reactive programs with trampoline variables can be composed and how they can form the basis to replace stateful constituents of a running reactive program — a.k. a. hotswapping — in a coherent way. The latter is an essential building block towards live IDEs for reactive programming languages.
An Intellectual Review of Milliken-Rodriguez

In the legendary, unanimous landmark opinion in Brown v. Board of Education (1954) authored by Mr Chief Justice Earl Warren, he declared that public education must be made available to all on equal terms. Unknowingly, in countermanding Plessy v. Ferguson (1896), Brown removed the mechanism for internalizing the externality of segregation (Reeves 2021), allowing Milliken v. Bradley (1974), establishing de facto segregation in schools, and San Antonio Independent School District v. Rodriguez (1973), decided a year earlier legalizing unequal school funding schemes, to sanction separate but unequal schools and render Brown a lion with no teeth. Under Brown Milliken-Rodrieguezcum, there is no obligation for the Court to bring equality to even a manifest disequilibrium and hopeless state for children under blatant de facto segregation; or is there. If Steve Jobs had been hampered from acquiring his technological skills, Apple would be worth only a fraction of its USD 2.25 trillion market capitalization (Szmigiera 2021), the global economy would be a scale replica, and the global Society would be unrecognizable. Cognizing human capital and the intellectual property that it produces are both forms of property, we aver that State enactments that for whatever reason restrict an individual from freely accumulating and upgrading her human capital stock in the market are violative of the Due Process Clauses of the Fifth and Fourteenth Amendments. Additionally, enactments that restrict population segments non-uniformly could potentially violate the Equal Protection Clause of the Fourteenth Amendment. Furthermore, because human capital and intellectual property are instrumentalities of commerce, such enactments would be repugnant to the Commerce Clause. As the Court has observed, it is highly improbable that any schooling program operating with even de facto, separate but unequal schools would survive a single let alone run a gauntlet of Constitutional challenges. Finally, even if State de facto separate but unequal schooling systems can withstand the Constitutional challenges, we proffer that the Federal government, while it does not need one, has a compelling state interest to intervene in the distribution and allocation of human capital to ensure that the aggregate stock of human capital is sufficient to meet the military, national security, and strategic macroeconomic needs of the nation. The Constitutional challenges together with the Federal government’s compelling state interest lay the groundwork to finally ensure education is made available to all on equal terms.
An Unsuccessful Reform on the Local Public Contracts Law in Korea

In Korea, local governments and local agencies had to apply a version of the first price auction augmented by an ex-post screening process when they procure construction contracts. However, this first price auction had been criticized because it was felt that too much price competition could lead to poor ex-post performance in construction. In response, the existing auction method was recently replaced by a version of the average price auction with a similar screening process. This paper empirically examines the effectiveness of this reform and finds that the replacement only increases the fiscal burden of local governmental bodies without making any improvement in the ex-post performance.
The Role of Demand Information for Price-Setting Newsvendors: A Monotone Comparative Statics Approach

In this paper, we examine the role of demand forecast information for price-setting newsvendors. In our model, the newsvendor faces stochastic demand that is price-sensitive, has the discretion of setting the retail price, and receives some informative signal that helps the quantity decision. Focusing on a specific family of signal structure which satisfies the scale-location property, we find that when the newsvendor's demand forecast gets improved, the optimal retail price can either increase, decrease, or stay the same, and we provide concrete sufficient conditions on primitives under which each sort of monotonicity prevails. The analysis utilizes the monotone comparative statics approach, which does not require the solution uniqueness and largely weakens the regularity conditions commonly adopted in the literature. We offer a comprehensive investigation of a full spectrum of information structures, whereas the extant literature focuses exclusively on the comparison between the full-information and null-information cases. We also provide several commonly adopted distribution functions as applications of this approach.
Algorithmic Bosses Can’t Lie! How to Foster Transparency and Limit Abuses of the New Algorithmic Managers

Technology is changing the way entrepreneurs manage their human resources. Many employers have already started to dismiss the completely human exercise of their managerial prerogatives, totally or partially delegating them to more or less smart machines. Data collected through people or workforce analytics practices are the fuel to fill the tank of algorithmic management tools, which are capable of taking automated decisions affecting the workforce. Notwithstanding the advantages in terms of increased labour productivity, recurring to technology is not always risk-free. It has already happened, also in the HR management context, that algorithms have revealed themselves as biased decision-makers. This problem has often been exacerbated by the lack of transparency characterising most part of automated decision-making processes. Moreover, this issue is worse in the employment context because it increases the already existent information asymmetries between entrepreneurs and workers. These are the main reasons why it has been underlined how workforce analytics and algorithmic management practices may implicate an augmentation of managerial prerogatives unheard in the past. It has also been stressed that this should entail an update – or even a rethinking – of employment laws that, as they are today, may be inadequate to address the issues posed by the technological revolution. This paper tries thus to understand, mainly looking at the Italian and other EU civil-law based legal systems, whether there are rules that may foster transparency and prevent abuses of employers’ managerial prerogatives potentially arising from the increasing recourse to algorithmic management practices. More specifically, this article points to three types of regulatory techniques that may alleviate the abovementioned issues. These three regulatory techniques are: a) information and access rights, to be exercised before a claim has been brought with a view to gather evidence to be used within a trial; b) rules that, within a trial, totally or partially switch the burden of proof to the employer; and c) rules that, within a trial, grant employment judges with broad powers to gather evidence. All these regulatory techniques strongly incentivise employers to recur to only those algorithmic tools with a decision-making process that can potentially be made transparent to their employees and, in case of a trial, to employment judges. Therefore, the employment legal system already knows how to foster transparency in the workplace and consequently uncover the violation of rules that already limit abuses of managerial prerogatives by employers. In light of the pervasive use of new technological tools to manage human resources, a more massive recourse to these regulatory antibodies can constitute an effective policy recommendation to better face the challenges posed by the algorithmic revolution.
Tail Risk Connectedness in the Refined Petroleum Market: A First Look at the Impact of the COVID Pandemic

We use the conditional autoregressive value at risk (CAViaR) model in combination with the time-varying parameter vector autoregressive (TVP-VAR) based connectedness approach to study the systematic tail risk transmission considering two types of crude oil (Brent and WTI) and also four refined petroleum products prices (gasoline, heating oil, jet fuel and propane) from January, 17, 1997 to December 11, 2020. For robustness purposes, we utilise three commonly used VaR probability cut-off points; that is, 10%, 5% and 2.5%. The selected sample period covers the first stage of the recent COVID-19 pandemic crisis. Results show that, both heating oil and kerosene are persistent net transmitters of uncertainty episodes in the network, signifying the importance of liquidity in the relevant markets. In addition, the role of the two measures of crude oil appears to shift around 2009 following developments in the energy market. Overall, findings suggest that, connectedness rises with major crisis episodes and that the recent COVID-19 pandemic appears to have the potential to propel tail risk and exposure to losses to levels akin to those of the Global Financial Crisis of 2007.
Room temperature ammonia sensing properties of nanostructured polyaniline salt and polyaniline base thin films

ABSTRACT Polyaniline salt and polyaniline base thin films were grown by chemical polymerization technique. Films of salt and base were characterized by optical absorbance spectroscopy which reveals the formation of polyaniline. The resistivity of both samples was investigated by I-V source meter which shows ohmic nature. Surface morphology of both samples was investigated by Field Emission Scanning Electron Microscopy, which represents the nanostructured and granular morphology. Ammonia sensing properties of both samples were by I-V source meter in presence of 25 ppm of ammonia. Observed values of sensitivity (S) is 82% and 56% for polyaniline salt and polyaniline base.
Importance of Optimized Guideline-Based Therapy for Preventing Rehospitalization of Chronic Heart Failure Patients　― From the KUNIUMI Acute Cohort ―

Background: Because the effectiveness of strengthening guideline-based therapy (GBT) to prevent heart failure (HF) rehospitalization of chronic HF patients remains unclear, this study investigated the characteristics of HF patients in the Kobe University Heart Failure Registry in Awaji Medical Center (KUNIUMI) acute cohort. Methods and Results: We studied 254 rehospitalized HF patients from the KUNIUMI Registry. Optimized GBT was defined as a Class I or IIa recommendation for chronic HF based on the guidelines of the Japanese Circulation Society. The primary endpoint was all-cause death or first HF rehospitalization after discharge. Outcomes tended to be more favorable for patients who had rather than had not received optimized GBT (hazard ratio [HR] 0.82; 95% confidence interval [CI] 0.57–1.19; P=0.27). Similarly, among New York Heart Association (NYHA) Class IV patients, outcomes tended to be more favorable for those who had rather than had not undergone optimized GBT (HR 0.73; 95% CI 0.47–1.12; P=0.15). Importantly, outcomes were significantly more favorable among NYHA Class IV patients aged <79 years who had rather than had not undergone optimized GBT (HR 0.33; 95% CI 0.14–0.82; P=0.02). Multivariate Cox regression analysis showed that optimized GBT was the only independent factor for the prediction of the primary endpoint. Conclusions: Optimized GBT can be expected to play an important role as the next move for chronic HF patients.