Miracle-dz/UniFAR-FTUs huggingface dataset:
Coalition Formation and Cost Allocation for Joint Replenishment Systems

T his paper focuses on the issues of coalition formation and cost allocation in a joint replenishment system involving a set of independent and freely interacting retailers purchasing an item from one supplier to meet a deterministic demand. The papers dealing with this problem are mainly focused on supperadditive games, where the cost savings associated with a coalition increase with the number of players in the coalition. The most relevant question addressed then is how to allocate the savings to the players. In this paper, we propose to go further by dealing with a non-supperadditive game, where a set of independent retailers have the common understanding to share the cost savings according to the cost-based proportional rule. In this setting, the global cost optimization is no longer a relevant approach to identify appealing coalitions for any retailer. Here, we provide an iterative procedure to form the so-called efficient coalition structure and we show that this coalition structure has the nice properties of being (i) weakly stable in the sense of the coalition structure core and (ii) strongly stable under a given assumption. An exact fractional programming based solution is also given to generate such efficient coalitions.
Early Discharge and Patient-Initiated Follow-Up in Hand Surgery: A New Norm Following Simple Hand Surgery?

Aims: The demand for elective hand surgery has increased substantially over the last 10 years. With COVID-19 providing an added challenge of restrictions on face-to-face consultations, already overflowing follow-up clinics will be stressed further. Our aim is to assess the viability, effectiveness, and safety of an early discharge directly from the operating theatre following common hand surgery procedures with the safety net of open-access follow-up. Methods: All eligible patients undergoing open-hand surgery under local anaesthesia between February 2019 and December 2020 were offered early discharge. Informed consent was obtained in the clinic, and they were counselled on rehabilitation immediately prior to surgery. Patients were given a custom-made "open-access business card" with clear post-operative instructions and hand exercises, along with information on how to get in touch to request clinic follow-up. A review was completed at a minimum of two months following surgery. Administrative support staff were briefed beforehand to minimise any delays in follow-up requests and either book patients who requested follow-up into a routine elective clinic or utilise ring-fenced emergency elective clinic slots depending on the patient's individual requirements. Results: A total of 105 patients were included in this study, with an average age of 60 years. The average interval between surgery and review was 20 weeks. Eighty-nine patients had a successful early discharge, with 16 patients requesting clinic follow-up. The average time to follow up in the clinic was 35 weeks (range: four to 84 weeks). There were no complications that we were made aware of, and the most common reason for returning to the clinic was a new complaint, unrelated to the surgery. Conclusions: Although virtual follow-up is now well established in both the fracture and elective clinic settings, early discharge is largely uncharted water. Our pilot demonstrates that early discharge and patient-initiated follow-up for common elective hand surgical procedures under local anaesthesia are efficient, safe, and viable.
Identifying Smartphone Users Based on Activities in Daily Living Using Deep Neural Networks

Smartphones have become ubiquitous, allowing people to perform various tasks anytime and anywhere. As technology continues to advance, smartphones can now sense and connect to networks, providing context-awareness for different applications. Many individuals store sensitive data on their devices like financial credentials and personal information due to the convenience and accessibility. However, losing control of this data poses risks if the phone gets lost or stolen. While passwords, PINs, and pattern locks are common security methods, they can still be compromised through exploits like smudging residue from touching the screen. This research explored leveraging smartphone sensors to authenticate users based on behavioral patterns when operating the device. The proposed technique uses a deep learning model called DeepResNeXt, a type of deep residual network, to accurately identify smartphone owners through sensor data efficiently. Publicly available smartphone datasets were used to train the suggested model and other state-of-the-art networks to conduct user recognition. Multiple experiments validated the effectiveness of this framework, surpassing previous benchmark models in this area with a top F1-score of 98.96%.
Efficacy and Safety of Pharmacist-Managed NSAIDs Deprescribing: A Jordanian Outpatient Study

Background. Nonsteroidal anti-inflammatory drugs (NSAIDs) are commonly used to manage pain, including chronic pain conditions. However, their prolonged use is associated with significant risks, particularly gastrointestinal (GI) adverse events. This study aimed to evaluate the effectiveness and safety of a pharmacist-managed deprescribing program for NSAIDs in a Jordanian outpatient population. Methods. A convenience sample of 100 participants who had been using NSAIDs for pain management was recruited. Participants underwent a structured deprescribing intervention in collaboration with physicians. Various effectiveness and safety outcomes were assessed before and after deprescribing. Descriptive statistics and chi-square test were used for data analysis. Results. The majority of participants reported chronic pain conditions, with rheumatoid arthritis (24%) and osteoarthritis (22%) being the most prevalent. Ibuprofen (28%) and diclofenac (22%) were the most commonly used NSAIDs. The deprescribing program was associated with a significant reduction in heartburn, stomach ulcer, kidney problems and fluctuation in blood pressure readings (p<0.05), and pain exacerbation. Notably, the reduction in pain exacerbation was evident (p=0.003) in the 4-month follow-up. Conclusion. A pharmacist-managed NSAIDs deprescribing program demonstrated effectiveness in reducing the risk of GI adverse events and fluctuation in blood pressure readings without causing harm during a short-term follow-up. These findings support the feasibility of implementing such programs in outpatient settings. Further long-term investigations are necessary to confirm these results.
STOCK MARKET CAPITALIZATION: HOW TO MANAGE ITS DETERMINANTS?

: The paper investigates the determinants of stock market capitalization in emerging market and developing economies, including China, Indonesia, India, Sri Lanka, Malaysia, the Philippines, Thailand and Vietnam from 2008-2020. Although this is not a new research topic for developed economies, it is less popular for emerging markets and developing economies, which is this paper’s novelty. Moreover, most current studies have focused solely on exploring the determinants of stock market capitalization, with only a few examining how the stock market capitalization responds to a country's corruption control efforts. This study aims to address this gap by thoroughly analyzing how efforts to control corruption by countries impact stock market capitalization and its determinants. By applying the Generalized Method of Moments (GMM), the author has defined inflation as a negative economic determinant of stock market capitalization. However, it positively correlates to the corruption control index and other economic factors, namely GDP per capita, domestic credit and trade. These confirm that the improvements in macro environments and corruption control play a vital role in the emerging market and developing economies in fostering their stock markets.
A new discovery of The Early Cretaceous Supercritical Hyperpycnal Flow Deposits on Lingshan Island, East China

Understanding the dynamics of sediment gravity flows is of great importance to correctly interpret their related deposits. The discovery of supercritical sediment gravity flows provides some new viewpoints for the explanation of controversial sediment gravity flow deposits. However, the dynamics, formation, evolution processes of supercritical sediment gravity flows and their recognition criteria from their associated deposits are still worldwide controversial. The supercritical hyperpycnal flow deposits recognized in the upper part of Early Cretaceous Lingshandao Formation provide a rare opportunity to understand their sedimentary characteristics. This work is aimed at documenting the typical sedimentary structures associated with the supercritical hyperpycnal flow, and discussing the vertical stacking and its relationship with flow evolution.
Hippocampal ΔFosB expression is associated with cognitive impairment in a subgroup of patients with childhood epilepsies

Epilepsy is a chronic neurological disorder characterized by recurrent seizures, and is often comorbid with other neurological and neurodegenerative diseases, such as Alzheimer's disease (AD). Patients with recurrent seizures often present with cognitive impairment. However, it is unclear how seizures, even when infrequent, produce long-lasting deficits in cognition. One mechanism may be seizure-induced expression of ΔFosB, a long-lived transcription factor that persistently regulates expression of plasticity-related genes and drives cognitive dysfunction. We previously found that, compared with cognitively-intact subjects, the activity-dependent expression of ΔFosB in the hippocampal dentate gyrus (DG) was increased in individuals with mild cognitive impairment (MCI) and in individuals with AD. In MCI patients, higher ΔFosB expression corresponded to lower Mini-Mental State Examination scores. Surgically resected DG tissue from patients with temporal lobe epilepsy also showed robust ΔFosB expression; however, it is unclear whether ΔFosB expression also corresponds to cognitive dysfunction in non-AD-related epilepsy. To test whether DG ΔFosB expression is indicative of cognitive impairment in epilepsies with different etiologies, we assessed ΔFosB expression in surgically-resected hippocampal tissue from 33 patients with childhood epilepsies who had undergone Wechsler Intelligence Scale for Children (WISC) testing prior to surgery. We found that ΔFosB expression is inversely correlated with Full-Scale Intelligence Quotient (FSIQ) in patients with mild to severe intellectual disability (FSIQ < 85). Our data indicate that ΔFosB expression corresponds to cognitive impairment in epilepsies with different etiologies, supporting the hypothesis that ΔFosB may epigenetically regulate gene expression and impair cognition across a wide range of epilepsy syndromes.
Valuing Indigenous Knowledge in the Highlands of Papua New Guinea: A Model for Agricultural and Environmental Education

Abstract Current methods of agricultural and environmental education for indigenous farmers in Papua New Guinea (PNG) fail to provide high level engagement. Indigenous knowledge (IK) forms the basis of natural resource management, agriculture and health of farmers in PNG, yet its value to agricultural and environmental education in PNG is rarely recognised. The argument made in this article is that valuing indigenous knowledge will enhance agricultural and environmental education. The purpose of this empirical study was to assess the application of a knowledge management model in understanding indigenous knowledge to enhance agricultural and environmental education. This article focuses on agricultural and environmental indigenous knowledge and culture in two villages in the Western Highlands of PNG. Participant observation, semi-structured interviews, and apprentice observations were methods to collect data from small-scale indigenous farmers. The study found that as farmers shift to cash crops, IK is devalued against Western knowledge. The study also found that trust, culture, and social barriers limit sharing of knowledge. The article concludes with recommendations for future agricultural and environmental education in the PNG highlands.
Analysis of metabolite and strain effects on cardiac cross-bridge dynamics using model linearisation techniques

Multi-scale models of cardiac energetics are becoming crucial in better understanding the prevalent chronic diseases operating at the intersection of metabolic and cardiovascular dysfunction. Computationally efficient models of cardiac cross-bridge kinetics that are sensitive to changes in metabolite concentrations are necessary to simulate the effects of disease-induced changes in cellular metabolic state on cardiac mechanics across disparate spatial scales. While these models do currently exist, deeper analysis of how the modelling of metabolite effects and the assignment of strain dependence within the cross-bridge cycle affect the properties of the model is required. In this study, model linearisation techniques were used to simulate and interrogate the complex modulus of an ODE-based model of cross-bridge kinetics. Active complex moduli were measured from permeabilised rat cardiac trabeculae under five different metabolite conditions with varying ATP and Pi concentrations. Sensitivity to metabolites was incorporated into an existing three-state cross-bridge model using either a direct dependence or a rapid equilibrium approach. Combining the two metabolite binding methods with all possible locations of strain dependence within the cross-bridge cycle produced 64 permutations of the cross-bridge model. Using linear model analysis, these models were systematically explored to determine the effects of metabolite binding and their interaction with strain dependence on the frequency response of cardiac muscle. The results showed that the experimentally observed effects of ATP and Pi concentrations on the cardiac complex modulus could be attributed to their regulation of cross-bridge detachment rates. Analysis of the cross-bridge models revealed a mechanistic basis for the biochemical schemes which place Pi release following cross-bridge formation and ATP binding prior to cross-bridge detachment. In addition, placing strain dependence on the reverse rate of the cross-bridge power stroke produced the model which most closely matched the experimental data. From these analyses, a well-justified metabolite-sensitive model of rat cardiac cross-bridge kinetics is presented which is suitable for parameterisation with other data sets and integration with multi-scale cardiac models.
Synthesizing Magnesium Oxide through a 3D Experience

This lesson is from the Types of Reactions unit in a High School Chemistry class and focuses on the synthesis of magnesium oxide. The purpose of this lesson is for students to conduct a lab experiment, and understand, at an atomic level, how the reaction occurs. In collaboration between a Chemistry teacher and Educational Technology faculty member, one three-dimensional (3D) experience was created to support the visualization of the reaction and minimize the students’ misconceptions.
Ground Penetrating Radar Investigations of Landslides: A Case Study in a Landslide in Radziszów

Abstract The article presents the results of research of the activated landslide in Radziszów in 2010. The study focused on the evaluation of engineering geology conditions, preceded by geophysical surveys. It mainly focused on the GPR method using the IDS georadar equipped with antennas in the frequency range of 100 MHz. Antenna selection was based on archival research which showed that the depth of occurrence of clays, where the roof can be a potential slip surface, ranges between 3-10 m below the surface. GPR method applied allowed the course of the potential slip surface to be determined and the results obtained significantly correlated with the results of engineering geology tests carried out.
Establishment of feijoa (Acca sellowiana) callus and cell suspension cultures and identification of arctigenin - a high value bioactive compound

Feijoa (Acca sellowiana (O. Berg.) Burret), also known as pineapple guava, is a member of the Myrtaceae family and is well known for its fruit. Chemical profiling of the different tissues of the feijoa plant has shown that they generate an array of useful bioactive compounds which have health benefits such as significant antioxidant activities. In this study, an in vitro culture system has been developed, which could be explored to extract high-value bioactive compounds from feijoa. Feijoa tissue culture was initiated by the induction of callus from floral buds. Sections of floral buds were plated on MS medium supplemented with 2,4-D and BAP at 2.0mg/L and 0.2mg/L concentrations, respectively. Cell suspension cultures of feijoa were established using a liquid MS medium with different concentrations of 2,4-D and BAP and cultured on a rotary shaker. The growth of the cell suspension was evaluated with different parameters such as different carbohydrate sources, concentration of MS media, and inoculum density. When the cell suspensions were treated with different concentrations of MeJA at different time points, phytochemicals UPLC - QTOF MS analysis identified extractables of interest. The main compounds identified were secondary metabolites (flavonoids and flavonoid-glucosides) and plant hormones. These compounds are of interest for their potential use in therapeutics or skin and personal care products. This report investigates essential methodology parameters for establishing cell suspension cultures from feijoa floral buds, which could be used to generate in vitro biomass to produce high-value bioactive compounds. This is the first study reporting the identification of arctigenin from feijoa, a high-value compound whose pharmaceutical properties, including anti-tumour, anti-inflammatory and anti-colitis effects, have been widely reported. The ability of feijoa cell cultures to produce such high-value bioactive compounds is extremely promising for its use in pharmaceuticals, cosmeceuticals and nutraceuticals applications.
Reinforcement Learning-Based Adaptive Control of a Piezo-Driven Nanopositioning System

This article proposes a new reinforcement learning (RL)-based adaptive control design for precision motion control of a two-degree-of-freedom piezoelectric XY nanopositioning system. In this design, an actor-critic structure is developed to eliminate the effects of uncertain nonlinearities and cross-coupling motion between the two working axes. Then, an adaptive parameter adjustment mechanism is designed to optimize the control performance without a priori knowledge of the unknown perturbations. The effectiveness and superiority of the proposed method are verified by performing simulation and experimental studies. The results show that the proposed RL-based adaptive control method provides a better robust performance and smaller tracking error for the nanopositioning system.
Hybrid Renewable Energy System Analysis For Off Grid Great Lakes Residential Housing

Renewable energy has become an important area of research and development for both environmental as well as economic reasons. At the academic level, it is possible to introduce students to issues related to renewable energy. This paper discusses the effort two students put in, as part of a thesis, and an independent study, to develop an economically feasible, self-sufficient, renewable energy system for a residential home in the Great Lakes region. The design of the system sought to use both wind and solar energy to supply energy to the home. The students were able to consider effects such as the design and capability of the wind turbine and solar panels to determine whether the design would be viable economically. After deciding that the initial system design would be too expensive, the students then considered other options to reduce the cost of the renewable energy system while still providing the necessary electrical systems that are used in a modern home. This included the development of a survey that was distributed to faculty and staff. The survey was used to determine the critical electrical loads that families in the Great Lakes region would require throughout the year. From this data, the average daily, weekly, and annual power requirements for a 2,000 square foot home was determined. Hybrid energy systems (using wind and solar power only) were then researched and priced to determine feasibility in the Great Lakes region. Alternative and supplementary sources of home and water heating were also explored in an attempt to reduce energy consumption in order to meet the specified cost requirements of the renewable energy project. Successes and challenges of developing a completely self-sufficient (off of the commercial electrical grid) home in the Great Lakes region of North America using renewable energy will be discussed.
The global warming hiatus: Slowdown or redistribution?

Global mean surface temperatures (GMST) exhibited a smaller rate of warming during 1998–2013, compared to the warming in the latter half of the 20th Century. Although, not a “true” hiatus in the strict definition of the word, this has been termed the “global warming hiatus” by IPCC (2013). There have been other periods that have also been defined as the “hiatus” depending on the analysis. There are a number of uncertainties and knowledge gaps regarding the “hiatus. ” This report reviews these issues and also posits insights from a collective set of diverse information that helps us understand what we do and do not know. One salient insight is that the GMST phenomenon is a surface characteristic that does not represent a slowdown in warming of the climate system but rather is an energy redistribution within the oceans. Improved understanding of the ocean distribution and redistribution of heat will help better monitor Earth's energy budget and its consequences. A review of recent scientific publications on the “hiatus” shows the difficulty and complexities in pinpointing the oceanic sink of the “missing heat” from the atmosphere and the upper layer of the oceans, which defines the “hiatus. ” Advances in “hiatus” research and outlooks (recommendations) are given in this report.
Examining the Hydrological Variations in an Aquaplanet World Using Wave Activity Transformation

AbstractBuilding on the recent advent of the concept of finite-amplitude wave activity, a contour-following diagnostics for column water vapor (CWV) is developed and applied to a pair of aquaplanet model simulations to understand and quantify the higher moments in the global hydrological cycle. The Lagrangian nature of the diagnostics leads to a more tractable formalism for the transient, zonally asymmetric component of the hydrological cycle, with a strong linear relation emerging between the wave activity and the wave component of precipitation minus evaporation (). The dry-versus-wet disparity in the transient hydrological cycle is measured by , and it is found to increase at a super-Clausius–Clapeyron rate at the poleward side of the mean storm track in response to a uniform sea surface temperature (SST) warming and the meridional structure of the increase can be largely attributed to the change of the meridional stirring scale of the midlatitude Rossby waves. Further scaling for indicates that the ra.