Miracle-dz/UniFAR-FTUs huggingface dataset:
The Probability to Reach an Agreement as a Foundation for Axiomatic Bargaining

We revisit the Nash bargaining model and axiomatize a procedural solution that maximizes the probability of successful bargaining. Our characterization spans several known solution concepts, including the special cases of the Nash, egalitarian, and utilitarian solutions. Using a probability‐based language, we offer a natural interpretation for the product operator underlying the Nash solution: when the bargainers' individual acceptance probabilities are independent, their product recovers the joint acceptance probability.
Utilization of the Mobile Library Application via Smartphone

Background of the study: The use of technology in an all-digital world has made the Lubuklinggau City Library and Archives Service innovate to create a mobile library named Ilubuklinggau. Purpose: This study examines the use of the Ilubuklinggau mobile library application through a smartphone. This study aims to determine the use of existing collections in Ilubuklinggau by users, to find out the fulfillment of digital collection needs in the Ilubuklinggau application, and to know the skills of the community in accessing information through the Ilubuklinggau mobile library. Method: The research method used is a qualitative approach. The research subjects were 6 people consisting of 3 users of the Ilubuklinggau application and 3 library staff, informants as data sources were taken with certain considerations. Findings: Utilization is explained using the Unified Theory of Acceptance and Use of Technology (UTAUT) model parameters. Based on this research, it is concluded that the results of 4 aspects include: 1) aspects of performance expectations 2) business expectations 3) social influences 4) facilitation conditions. These four aspects must be possessed in order to make optimal use of the Ilubuklinggau mobile library application through smartphones. Conclusion: The Ilubuklinggau application helps performance and makes it easier in terms of use, as well as increasing the competence and existence of the library, but this application has several obstacles that affect utilization such as incomplete collections due to budget conditions and face-to-face socialization that has not been held so that application enthusiasts are still lacking.
Artificial Intelligence (AI) Chatbots in Medicine: A Supplement, Not a Substitute

This editorial discusses the role of artificial intelligence (AI) chatbots in the healthcare sector, emphasizing their potential as supplements rather than substitutes for medical professionals. While AI chatbots have demonstrated significant potential in managing routine tasks, processing vast amounts of data, and aiding in patient education, they still lack the empathy, intuition, and experience intrinsic to human healthcare providers. Furthermore, the deployment of AI in medicine brings forth ethical and legal considerations that require robust regulatory measures. As we move towards the future, the editorial underscores the importance of a collaborative model, wherein AI chatbots and medical professionals work together to optimize patient outcomes. Despite the potential for AI advancements, the likelihood of chatbots completely replacing medical professionals remains low, as the complexity of healthcare necessitates human involvement. The ultimate aim should be to use technology like AI chatbots to enhance patient care and outcomes, not to replace the irreplaceable human elements of healthcare.
Peran Moderasi Financial Access Pada Pengaruh Human Capital Dan Social Capital Terhadap Kinerja UMKM

Human capital, social capital dan financial access telah diidentifikasi sebagai sumber daya utama yang mempengaruhi kinerja usaha mikro, kecil, dan menengah (UMKM), variabel-variabel ini jarang dipelajari. Makalah ini, oleh karena itu, menguji hubungan antara modal manusia, modal sosial pada kinerja perusahaan dengan akses ke keuangan sebagai moderating variable. 378 UMKM penghasil Batik Jonegoroan digunakan sebagai sampel penelitian. Pemodelan Persamaan Struktural menggunakan Partial Least Square (PLS) digunakan untuk menganalisis data yang dikumpulkan menggunakan sampling area. Hasil penelitian menunjukkan bahwa modal manusia, modal sosial, dan akses keuangan berpengaruh langsung terhadap kinerja perusahaan.Akses keuangan terbukti menguatkan pengaruh dari social capital terhadap kinerja UMKM. Sementara Akses keuangan tidak memiliki peran moderasi pada pengaruh dari human capital terhadap kinerja UMKM. Disarankan agar pengusaha didorong untuk membangun lebih banyak hubungan dalam jaringan mereka. Serta berupaya untuk mendapatkan akses permodalan baik dari perbankan ataupun lembaga keuangan lain karena akses fianancial terbukti memberi dampak positif terhadap kinerja UMKM. Selain itu, lembaga pemerintah dan lembaga keuangan harus menyusun strategi yang akan mengurangi tingkat bunga sehingga UMKM dapat mengakses sumber keuangan.
Indirect Adaptive Fuzzy Control Scheme Based on Lyapunov Approach for a Class of SISO Nonlinear Systems

In this paper we are interested in an indirect fuzzy adaptive control of SISO nonlinear systems in the presence of parametric uncertainties. The plant model structure is represented by a fuzzy system. The essential idea of the on-line parametric estimation of the plant model is based on a comparison of the measured state with the estimate one. The design of adaptive law is based on a Lyapunov approach. The control action comprises two terms: a classical indirect adaptive fuzzy controller and a supervisory controller. The plant state tracks asymptotically any bounded reference input signal. Two examples are used to check performance of the proposed controller.
Current Account Imbalances in Asia’s Countries: The Contributing Elements

The current account has emerged as one of the primary indicators of external imbalances in the global economy, and it may be used to assess the strength of a nation's economy. Since the 1990s, it has been a prevalent trend for Asia region to always demonstrate a current account surplus condition and continue to reinforce in the early 2000s. Although it experiences a huge drop of current account balance in 2009 during the mortgage crisis period, the region persists in its current account surplus. Hence, the aim of this study is to assess the determinants of current account imbalances in Asia region. This study is a panel regression model that covered a total of 48 Asia countries from 1990 to 2021 annually. The dependent variable is current account balance and the independent variables are fiscal balance, public debt, age dependency ratio for old, age dependency ratio for young, ICT, and real GDP. The empirical methods that employed are including of panel unit root tests, panel cointegration tests, and pooled mean group (PMG) estimation. The major finding demonstrates that the determinants of current account imbalances are fiscal balance, public debt, age dependency ratio for old, age dependency ratio for young, and real GDP.
Multilevel method to compute the lambda modes of the neutron diffusion equation

Abstract Determination of the reactor kinetic characteristics is very important for the design and development of a new reactor system. In this sense, the computation of lambda modes associated to a nuclear power reactor has interest since these modes can be used to analyze the reactor criticality and to develop modal methods to analyze transient situations in the reactor. In this paper, the lambda problem has been discretized using a high order finite element method to obtain a generalized algebraic eigenvalue problem. A multilevel method is proposed to solve this generalized eigenvalue problem combining a hierarchy of meshes with a Modified Block Newton method. The Krylov-Schur method is used to compare the efficiency of the multilevel method solving several benchmark problems.
Autonomous Agents: An Advanced Course on AI Integration and Deployment

A majority of the courses on autonomous systems focus on robotics, despite the growing use of autonomous agents in a wide spectrum of applications, from smart homes to intelligent traffic control. Our goal in designing a new senior-level undergraduate course is to teach the integration of a variety of AI techniques in uncertain environments, without the dependence on topics such as robotic control and localization. We chose the application of an autonomous greenhouse to frame our discussions and our student projects because of the greenhouse's self-contained nature and objective metrics for successfully growing plants. We detail our curriculum design, including lecture topics and assignments, and our iterative process for updating the course over the last four years. Finally, we present some student feedback about the course and opportunities for future improvement.
Comparison of a Telehealth-Based Intensive Treatment Program with a Rewarding App vs. On-Site Care for Youth with Obesity: A Historical Cohort Study

The recommended treatment for children with obesity includes numerous consultations by a multidisciplinary team, which is very cumbersome. Telehealth can assist in administering frequent care to children with obesity, yet the exact approaches and modes of delivery are still explored. During the COVID-19 pandemic, we developed an intensive telehealth-based treatment program that included a rewarding app for children with obesity. The aim of this study was to compare 6-month changes in body mass index (BMI) and body fat percent between participants in the program (n = 70) vs. children that underwent historic on-site care (n = 87). After 6 months, more participants in the telehealth group continued treatment compared to the on-site group (79% vs. 60%, p < 0.001). A significant reduction in the median BMI z-score (zBMI) was seen after 6 months in both groups (p < 0.01), with a similar proportion of zBMI reductions (71% in the telehealth group, 75% in the comparison group, p = 0.76). No statistically significant differences were found between the study groups in 6-month changes in BMI, zBMI, body fat percent or fat z-scores. We conclude that our telehealth program, which was executed during the COVID-19 pandemic, resulted in a high proportion of children with zBMI reduction that was comparable with the more personal on-site care.
Size Uncertainty in Individual Nanoparticles Measured by Single Particle Inductively Coupled Plasma Mass Spectrometry

Single particle inductively coupled plasma mass spectrometry has been used for size measurements of individual nanoparticles (NPs). Here, uncertainties in size analysis based upon two calibration approaches were evaluated: (i) the use of particle size standard and (ii) the use of ion standard solution. For particle size standard approach, the source of uncertainty to determine the target NP diameter was related to the variation in the signal intensities of both target NPs and particle size standard, and the size distribution of the particle size standard. The relative uncertainties of the 50 nm silver NP as the target were 15.0%, 9.9%, and 10.8% when particle size standards of 30 nm, 60 nm, and 100 nm silver NPs were used, respectively. As for the ion standard solution approach, the sources of uncertainty were the concentration of working standard solution, sample flow rate, transport efficiency, slope of calibration curve, and variation in the signal intensity of the ion standard solution and of the target NPs. The relative uncertainties for the 50 nm silver NP were 18.5% for 1 ng/g, 7.6% for 10 ng/g, and 4.7% for 100 ng/g solutions. The lower uncertainty obtained with a high concentration working standard solution is recommended to improve precision on particle size determinations by spICP-MS.
MRI-Conditional Breast Tissue Expander: First In-Human Multi-Case Assessment of MRI-Related Complications and Image Quality

This study aims to assess potential complications and effects on the magnetic resonance imaging (MRI) image quality of a new MRI-conditional breast tissue expander (Motiva Flora®) in its first in-human multi-case application. Twenty-four patients with 36 expanders underwent non-contrast breast MRI with T1-weighted, T2-weighted, and diffusion-weighted imaging (DWI) sequences on a 3 T unit before breast tissue expander exchange surgery, being monitored during and after MRI for potential complications. Three board-certified breast radiologists blindly and independently reviewed image quality using a four-level scale (“poor”, “sufficient”, “good”, and “excellent”), with inter-reader reliability being assessed with Kendall’s τb. The maximum diameters of RFID-related artifacts on T1-weighted and DWI sequences were compared with the Wilcoxon signed-rank test. All 24 examinations were completed without patient-related or device-related complications. The T1-weighted and T2-weighted sequences of all the examinations had “excellent” image quality and a median 11 mm (IQR 9–12 mm) RFID artifact maximum diameter, significantly lower (p < 0.001) than on the DWI images (median 32.5 mm, IQR 28.5–34.5 mm). DWI quality was rated at least “good” in 63% of the examinations, with strong inter-reader reliability (Kendall’s τb 0.837, 95% CI 0.687–0.952). This first in-human study confirms the MRI-conditional profile of this new expander, which does not affect the image quality of T1-weighted and T2-weighted sequences and moderately affects DWI quality.
Co-evolution of social networks and continuous actor attributes

Social networks and the attributes of the actors in these networks are not static; they may develop interdependently over time. The stochastic actor-oriented model allows for statistical inference on the mechanisms driving this co-evolution process. In earlier versions of this model, dynamic actor attributes are assumed to be measured on an ordinal categorical scale. We present an extension of the stochastic actor-oriented model that does away with this restriction, using a stochastic dierential equation to model the evolution of continuous actor attributes. We estimate the parameters by a procedure based on the method of moments. The proposed method is applied to study the dynamics of a friendship network among the students at an Australian high school. In particular, we model the relationship between friendship and obesity, focusing on body mass index as a continuous co-evolving attribute.
Improvement in negative bias illumination stress stability of In–Ga–Zn–O thin film transistors using HfO2 gate insulators by controlling atomic-layer-deposition conditions

The effects of atomic layer deposition (ALD) conditions for the HfO2 gate insulators (GI) on the device characteristics of the InGaZnO (IGZO) thin film transistors (TFTs) were investigated when the ALD temperature and Hf precursor purge time were varied to 200, 225, and 250 °C, and 15 and 30 s, respectively. The HfO2 thin films showed low leakage current density of 10−8 A cm−2, high dielectric constant of over 20, and smooth surface roughness at all ALD conditions. The IGZO TFTs using the HfO2 GIs showed good device characteristics such as a saturation mobility as high as 11 cm2 V−1 s−1, a subthreshold swing as low as 0.10 V/dec, and all the devices could be operated at a gate voltage as low as ±3 V. While there were no marked differences in transfer characteristics and PBS stabilities among the fabricated devices, the NBIS instabilities could be improved by increasing the ALD temperature for the formation of HfO2 GIs by reducing the oxygen vacancies within the IGZO channel.
Data Mining Techniques for Predicting Cassava Yields in Lower Northern Thailand

This paper investigates the factors influencing the cassava yields and develops the predictive models to predict the cassava yields in lower northern Thailand. The main objective is to compare the prediction accuracy between data mining technique namely Artificial neural network model and the conventional model namely Stepwise regression model. The root mean square error and mean absolute error values are used to validate the prediction accuracy. The results show that the significant factors are plantation area, cassava variety, cultivation period, and quantity of fertilizer. Further Artificial neural network performs better than stepwise regression model in terms of prediction accuracy. The results obtained from this study will assist farmers to improve their practices in order to increase the cassava yields.
Physiological and Genetic Modifications Induced by Plant-Growth-Promoting Rhizobacteria (PGPR) in Tomato Plants under Moderate Water Stress

Simple Summary The availability of water is an essential factor in food production and, therefore, for food security, since even with moderate water deficits, plants reduce their production significantly. In a context of climate change, in which water scarcity is becoming increasingly evident, food security can be seriously compromised. In this work, the use of plant-growth-promoting rhizobacteria (PGPR) strains is proposed as a biotechnological tool to improve the physiological conditions of tomato plants under conditions of moderate water stress with the aim of trying not to lose productive capacity under these conditions. To validate it, the effect of PGPR on photosynthesis, oxidative state, and innate defensive response were determined in plants growing under moderate water stress. The results obtained show that PGPR can alter the physiology of plants in different ways, improving their resistance under moderate water stress conditions, maintaining their productive capacity. The use of this technology in agricultural production could reduce water consumption without reducing food production, which would have a strong social impact at all levels. Abstract Physiological, metabolic, and genetic changes produced by two plant growth promoting rhizobacteria (PGPR) Pseudomonas sp. (internal code of the laboratory: N 5.12 and N 21.24) inoculated in tomato plants subjected to moderate water stress (10% polyethylene glycol-6000; PEG) were studied. Photosynthesis efficiency, photosynthetic pigments, compatible osmolytes, reactive oxygen species (ROS) scavenging enzymes activities, oxidative stress level and expression of genes related to abscisic acid synthesis (ABA; 9-cis-epoxycarotenoid dioxygenase NCDE1 gene), proline synthesis (Pyrroline-5-carboxylate synthase P5CS gene), and plasma membrane ATPase (PM ATPase gene) were measured. Photosynthetic efficiency was compromised by PEG, but bacterial-inoculated plants reversed the effects: while N5.12 increased carbon fixation (37.5%) maintaining transpiration, N21.24 increased both (14.2% and 31%), negatively affecting stomatal closure, despite the enhanced expression of NCDE1 and plasma membrane ATPase genes, evidencing the activation of different adaptive mechanisms. Among all parameters evaluated, photosynthetic pigments and antioxidant enzymes guaiacol peroxidase (GPX) and ascorbate peroxidase (APX) responded differently to both strains. N 5.12 increased photosynthetic pigments (70% chlorophyll a, 69% chlorophyll b, and 65% carotenoids), proline (33%), glycine betaine (4.3%), and phenolic compounds (21.5%) to a greater extent, thereby decreasing oxidative stress (12.5% in Malondialdehyde, MDA). Both bacteria have highly beneficial effects on tomato plants subjected to moderate water stress, improving their physiological state. The use of these bacteria in agricultural production systems could reduce the amount of water for agricultural irrigation without having a negative impact on food production.
Lower-Limb Exoskeleton With Compliant Actuators: Human Cooperative Control

Active exoskeletons for the lower extremities are increasingly being used in rehabilitation therapy. One of the key areas of research in developing these assistive devices is ensuring safe human-machine interaction, which requires both a safe mechanical system and an effective assistive control framework. Therefore, we present a novel human cooperative control framework for exoskeletons with variable stiffness actuators to assist users during both the swing and stance phases of walking and other motion sequences such as sit-to-stand. The control framework estimates the user’s joint torques during the swing and stance phases using an Unscented Kalman Filter (UKF) and inverse kinematics, respectively. Using the Lower-Limb Exoskeleton with Serial Elastic Actuators (L2Exo-SE) as an example, the control approach was validated for its applicability to exoskeletons with compliant actuators. The validation results reveal a reduction of the average user’s joint torque during gait by 63.6%-78.4% for the hip and 40.8%-50.2% for the knee compared to non-assisted walking. Furthermore, we introduce an automatic stiffness selection for the serial elasticity of the variable stiffness actuator (VSA) based on the gait phases and the active human joint torque. The stiffness variation increases the physical human-robot interaction during the swing phase while maintaining a high control bandwidth during the stance phase.
Infection with tuberculosis in children under six who come into touch with smear-positive individuals

Introduction: Annually, tens of millions of children are being exposed to tuberculosis infection. Note that children are in higher risk of getting infection and sever types of the disease, detecting the factors associated with transmission of the tuberculosis infection and disease to the exposed children is necessary for disease prevention within the community. Methods: In this retrospective cohort study, 50 children under 6 who were in close contact with 25 smear-positive pulmonary tuberculosis cases in Pondicherry, India, were investigated. Demographic, behavioral and clinical characteristics of children and index cases were collected and tuberculosis infection and disease were assessed using the WHO guidelines. Results: Of 50 children exposed to the active cases, 12 (24%) were infected to tuberculosis but none of them had active disease. We also found significant associations of the history of diabetes mellitus in the index cases (p = 0.043) and large family size (p = 0.026) with the increased risk of infection among the exposed children. Conclusion: Children under six which are in close contact with diabetic tuberculosis cases in large families are in higher risk of getting infection.
Similarity Solution of Forced Convection Flow of Powell-Eyring & Prandtl-Eyring Fluids by Group-Theoretic Method

Generalized one parameter group theoretical method is applied to study Powell-Eyring and Prandtl-Eyring fluid models for heat transfer in forced convection boundary layer flow. The velocity and the temperature variations for two dimensional steady incompressible, laminar forced convection flow of both fluid modelspast a flat plate is considered. Velocity and temperature variation for different values offluid index and physical parameter A,B,α,β and Pr are presented graphically. Also, comparison for both fluid models is done graphically.