Miracle-dz/UniFAR-FTUs huggingface dataset:
Experimental and Therapeutic Opportunities for Stem Cells in Multiple Sclerosis

Multiple Sclerosis (MS) is an inflammatory demyelinating neurodegenerative disorder of the brain and spinal cord that causes significant disability in young adults. Although the precise aetiopathogenesis of MS remains unresolved, its pathological hallmarks include inflammation, demyelination, axonal injury (acute and chronic), astrogliosis and variable remyelination. Despite major recent advances in therapeutics for the early stage of the disease there are currently no disease modifying treatments for the progressive stage of disease, whose pathological substrate is axonal degeneration. This represents the great and unmet clinical need in MS. Against this background, human stem cells offer promise both to improve understanding of disease mechanism(s) through in-vitro modeling as well as potentially direct use to supplement and promote remyelination, an endogenous reparative process where entire myelin sheaths are restored to demyelinated axons. Conceptually, stem cells can act directly to myelinate axons or indirectly through different mechanisms to promote endogenous repair; importantly these two mechanisms of action are not mutually exclusive. We propose that discovery of novel methods to invoke or enhance remyelination in MS may be the most effective therapeutic strategy to limit axonal damage and instigate restoration of structure and function in this debilitating condition. Human stem cell derived neurons and glia, including patient specific cells derived through reprogramming, provide an unprecedented experimental system to model MS “in a dish” as well as enable high-throughput drug discovery. Finally, we speculate upon the potential role for stem cell based therapies in MS.
effectiveness of weekly cognitive stimulation therapy for people with dementia and the additional impact of enhancing cognitive stimulation therapy with a carer training program

Purpose of the study: Cognitive stimulation therapy (CST) is a widely used, evidence-based intervention for people with dementia (PwD). Although designed as a 14 session, twice weekly intervention, many services in the UK deliver CST once a week for 14 weeks. However, this method of delivery has yet to be evaluated. In addition, CST does not include any formal carer training. This study aimed to evaluate the effectiveness of once weekly CST and determine any additional impact when enhanced with a carer training program. Design and methods: A single blind, randomized controlled trial was conducted. Sixty eight PwD and their carers were recruited through three community Memory Assessment Services. PwD and their carers were randomized to one of three conditions: CST plus carer training, CST only, or a wait list control. PwD were administered standardized measures of cognition, quality of life, and quality of relationship with carer at baseline and the 15 week follow-up. Results: There were no baseline differences across the three groups. At follow-up, there were no significant differences between PwD in the three groups on any outcomes. Implications: Weekly CST with or without carer training may not be an effective form of delivery. Several possible explanations for the outcomes are proposed. Weekly CST may not offer the necessary “dose” required to combat decline, and equally the carer training may have been too brief to have made a difference. Services currently offering weekly CST should collect routine outcome data to support its use and provide practice-based evidence.
Edinburgh Research Explorer Constraint-Based Sentence Compression: An Integer Programming Approach

The ability to compress sentences while preserving their grammaticality and most of their meaning has recently received much attention. Our work views sentence compression as an optimisation problem. We develop an integer programming formulation and infer globally optimal compressions in the face of linguistically motivated constraints. We show that such a formulation allows for relatively simple and knowledge-lean compression models that do not require parallel corpora or large-scale resources. The proposed approach yields results comparable and in some cases superior to state-of-the-art.
GEOSTATISTICS AND DIGITAL IMAGE ANALYSIS FOR OPTIMIZING RICE PRODUCTION

Rice, as the staple food for a significant majority of the Indonesian population, plays a crucial role in food security and socio-economic stability. To address the strategic challenges associated with rice production, this study focuses on utilizing geostatistics and digital image analysis techniques to optimize rice production and enhance agricultural practices. The key factors influencing rice production, including land area, fertilization, seed varieties, human resources, and agricultural technology, are examined in relation to food security concerns. Fertilizers, high-yielding varieties, and water availability emerge as vital elements for increasing national rice production. However, the efficiency and effectiveness of fertilization practices are heavily influenced by localized conditions, and current approaches often lack rationality and balance. To achieve efficient production and rationalize fertilization practices, this research proposes the application of geostatistics and digital image analysis techniques. Geostatistical models, specifically the Kriging Method, are employed to predict the spatial distribution of key nutrients and fertilizers, such as Sodium, Phosphorus, and Potassium (NPK), required by rice plants in paddy fields. Additionally, digital image processing and computer vision technologies are utilized to automate the assessment of nutrient adequacy based on leaf color analysis. This advancement replaces the previous manual comparison method, providing a more accurate and efficient approach. The integration of geostatistics and digital image analysis offers a promising solution to optimize nutrient management, precision fertilization, and overall rice production. By harnessing advanced technologies and data-driven approaches, this study aims to contribute to the development of sustainable agricultural practices, ensuring improved food security and socio-economic well-being for the Indonesian population.
THE EFFECT OF AUDITOR EXPERIENCE, BIG DATA AND FORENSIC AUDIT AS MEDIATING VARIABLES ON FRAUD DETECTION

The many cases of fraud in Indonesia caused losses to the state. It has driven stakeholders, including the Government, to determine effective and efficient methods to detect fraudulent issues. Therefore, this study aimed to examine the influence of auditor experience, Big Data, and forensic auditing as mediating variables on fraud detection. It used a quantitative approach with a survey method by distributing questionnaires through a google form. Respondents comprised 128 internal, external, and government auditors. Furthermore, the data were analyzed using structural equation modeling (SEM) with the help of SmartPLS tools. The results showed that the auditor's experience, forensic audit, and Big Data positively and significantly affect fraud detection. Auditor experience and Big Data variables positively and significantly affect Forensic Audits. Additionally, a forensic audit mediates the auditor's experience with fraud detection but does not mediate Big Data against fraud detection.
Two-Stepping into the Icehouse: East Antarctic Weathering During Two-Stepping into the Icehouse: East Antarctic Weathering During Progressive Ice-Sheet Expansion at the Eocene–Oligocene Progressive Ice-Sheet Expansion at the Eocene–Oligocene Transition Transition

In conjunction with increasing benthic foraminiferal δ 18 O values at the Eocene–Oligocene transition (EOT; ca. 34 Ma), coarse-grained ice-rafted debris (IRD; >425 µm) appears abruptly alongside fossil ﬁ sh teeth with continentally derived neodymium (Nd) isotope ratios ( ε Nd ) in Kerguelen Plateau (Southern Ocean) sediments. Increased Antarctic weathering ﬂ ux, as inferred from two steps to less radiogenic ε Nd values, coincides with two steps in benthic foraminiferal δ 18 O values. These results indicate that two distinct surges of weathering were generated by East Antarctic ice growth during the EOT. Weathering by ice sheets during a precursor glaciation at 33.9 Ma did not produce signiﬁ cant IRD accumulation during the ﬁ rst ε Nd shift. Glacial weathering was sustained during a terrace interval between the two steps, probably by small high-elevation ice sheets. A large increase in weathering signals the rapid coalescence of small ice sheets into an
National Institutes of Health social and behavioral research in response to the SARS-CoV2 Pandemic

Abstract The COVID-19 pandemic has been mitigated primarily using social and behavioral intervention strategies, and these strategies have social and economic impacts, as well as potential downstream health impacts that require further study. Digital and community-based interventions are being increasingly relied upon to address these health impacts and bridge the gap in health care access despite insufficient research of these interventions as a replacement for, not an adjunct to, in-person clinical care. As SARS-CoV-2 testing expands, research on encouraging uptake and appropriate interpretation of these test results is needed. All of these issues are disproportionately impacting underserved, vulnerable, and health disparities populations. This commentary describes the various initiatives of the National Institutes of Health to address these social, behavioral, economic, and health disparities impacts of the pandemic, the findings from which can improve our response to the current pandemic and prepare us better for future infectious disease outbreaks.
Edinburgh Research Explorer The trypanosome Pumilio-domain protein PUF7 associates with a nuclear cyclophilin and is involved in ribosomal RNA maturation

Proteins with Pumilio RNA binding domains (Puf proteins) are ubiquitous in eukaryotes. Some Puf proteins bind to the 3 0 -untranslated regions of mRNAs, acting to repress translation and promote degradation; others are involved in ribosomal RNA maturation. The genome of Trypanosoma brucei encodes eleven Puf proteins whose function cannot be predicted by sequence analysis. We show here that epitope-tagged Tb PUF7 is located in the nucleolus, and associated with a nuclear cyclophi-lin-like protein, Tb NCP1. RNAi targeting PUF7 reduced trypanosome growth and inhibited two steps in ribosomal RNA processing. (cid:2) 2010 Federation of European Biochemical
Validation of a musculoskeletal model for simulating muscle mechanics and energetics during diverse human hopping tasks

Computational musculoskeletal modelling has emerged as an alternative, less-constrained technique to indirect calorimetry for estimating energy expenditure. However, predictions from modelling tools depend on many assumptions around muscle architecture and function and motor control. Therefore, these tools need to continue to be validated if we are to eventually develop subject-specific simulations that can accurately and reliably model rates of energy consumption for any given task. In this study, we used OpenSim software and experimental motion capture data to simulate muscle activations, muscle fascicle dynamics and whole-body metabolic power across mechanically and energetically disparate hopping tasks, and then evaluated these outputs at a group- and individual-level against experimental electromyography, ultrasound and indirect calorimetry data. Comparing simulated and experimental outcomes, we found weak to strong correlations for peak muscle activations, moderate to strong correlations for absolute fascicle shortening and mean shortening velocity, and strong correlations for gross metabolic power. These correlations tended to be stronger on a group-level rather than individual-level. We encourage the community to use our publicly available dataset from SimTK.org to experiment with different musculoskeletal models, muscle models, metabolic cost models, optimal control policies, modelling tools and algorithms, data filtering etc. with subject-specific simulations being a focal goal.
On the incorporation of moire´ shape measurements in ﬁnite-element models of the cat eardrum

The mechanical behavior of the eardrum has previously been shown to depend critically on its shape, but accurate shape measurements have been difﬁcult to make. Phase-shift moire´ topography provides a valuable technique for measuring such shapes, and measurement in the presence of large static pressures facilitates the determination of the boundaries of the pars tensa, pars ﬂaccida, and manubrium. New measurements of the shape of the cat eardrum are presented. The presence of hysteresis in the pressure-displacement response is demonstrated. The shapes are incorporated in individualized ﬁnite-element models for four different ears, and the variability between and within animals is examined. Fixed-manubrium low-frequency displacements are simulated and compared for the different models. © 1996 Acoustical Society of America.
DEVELOPMENT OF EXPERT UNSTRUCTURED DECISION-MAKING SUPPORT SYSTEM

With the advent of data warehouses and OLAP-technology, and subsequently many other systems that output information for decision-making, all such systems began to be referred to as decision support system (DSS). Thus, the original purpose of DSS has been forgotten: the selection of an effective solution from the set of possible alternatives for poorly structured or unstructured management decision-making tasks based on mathematical methods and information technology. Therefore, it would be more correct to call systems of this class Unstructured decision-making support systems (UDMSS), and other support systems, DSS. Currently, new terms are appearing, the purpose of which is to combine DSS into certain classes; for example, System DSS, Business DSS and Intelligent DSS. Research objective is the following: to develop a new UDMSS that combines elements of expert systems, data warehouses, group DMSS, author's UDMSS, and can be called Expert UDMSS (EUDMSS). The following main results are presented in the article: features of an expert unstructured decision making support system; system architecture; decision-making method selection module (expert system shell); decision-making module, including 50 mathematical methods (decision-making methods using the majority principle, Pareto and Bayes principle, in partial and full uncertainty, in dynamic formulation, vector optimization, methods combining various principles of matching evaluations of alternatives and other methods); system functionality.
Composting textile sludge using PGPRs grown sugarcane bagasse in a solid state bioreactor-a next step towards zero discharge of waste from textile industry

Generation of solid dye waste during wastewater puri�cation especially in coagulation/precipitation steps and its detoxi�cation is a major issue since it again leachate in the ground water from the land�lls because of rains. The semisolid textile waste (sludge) showed 99 and 97% decolourization at �ask and reactor scale within 72 h, respectively when treated with consortium ARBR (Azotobacter vinelandii MTCC 1241, Rhodobacter erythropholis MTCC 4688, B. megaterium NCIM 2054 and Rhizobium meliloti NCIM 2757). The decolourization rate of textile sludge majorly affects by the pH, temperature and moisture content of the sludge. At the optimum conditions of pH (6), temperature (30 o C) and moisture content (90%) the consortium showed maximum decolourization of 81, 84 and 97, respectively. A signi�cant increase in the activities of oxidoreductase enzymes such as lignin peroxidase (5 fold), laccase (2.6 fold), veratryl alcohol oxidase (4.7 fold) and tyrosinase (2.9 fold) was observed; while azo reductase (-1.3 fold) showed a decrease in the activity during sludge treatment. In addition, a noteworthy reduction in the concentration of macromolecules N (45%), P (70%), K (50%) and C (63%), and microelements B (59%), Cu (50%), Fe (59%) and Mn (75%) were also observed after treatment with sludge bed reactor. Bio-transformed sludge showed less toxic effects on plants. The outcome from the sludge bed bioreactor (solid state bioreactor) was found to be more effective and can be used using sugar industry waste like sugarcane bagasse (SCB) for composting.
HOW REMOTE WORKING CAN AFFECT EMPLOYEE PERFORMANCE USING SCRUM IN SOFTWARE DEVELOPMENT COMPANIES

Context . Lately, the rise of remote work has increasingly become an alternative to being present in the office, especially for IT employees in software development companies. However, remote working is not easy. It requires personal skills and a supporting workspace, one of which is the internet connection. Objective . This paper seeks to understand the impact of remote working in Scrum software development. Method . The questionnaire survey was made mainly from existing and validated scales. The questionnaire received 316 responses from scrum practitioners. The data were analyzed using SmartPLS version 3.0 and applying PLS-SEM analysis, including inner and outer model testing. Results . The structural model achieved a good fit (SRMR = 0.073, NFI = 0.714). The research findings show that team influence has a more significant effect than individual influence on employee performance with the most significant effect is communication and teamwork in scrum teams. By knowing the factors that affect employee performance, company stakeholders can help facilitate employee and provide a platform for scrum activities to improve the project's development. We cover this topic, along with the limitations of future research and work.
SECURE INITIALIZATION MODEL IMPROVEMENT FOR NFC-HCE SECURITY IN MOBILE PAYMENT SYSTEM

Near Field Communication (NFC) has two payment ecosystems based on its secure element location: NFC-SIM-SE (Subscriber Identity Module Secure Element) and NFC-HCE (Host Card Emulation). Secure elements in the NFC-HCE ecosystem are currently in the cloud, so they have security weaknesses. One of these security weaknesses is a vulnerability in the delivery process because data is manipulated and used for fake transactions. This security issue of credential data arises because of the bulk amount of data transmission in the cloud. When the information is stored in the smartphone, there is no data transmission over the global network. This credential data stored in a smartphone will later be used for a faster transaction process. We propose a model that puts the secure element to the smartphone and performs multilevel verification to fix its security issues. The proposed model consists of two stages: the account and the card registration stage. The model was tested to determine the security level using random data with the 50.34%avalanche effect,3.99542 entropy, and 0.42048 P-value tests. The test also calculates the processing time for each step, and the result is 0.0025 seconds. The test results show that the encryption process can increase the NFC-HCE ecosystem's security; only verified data could be stored on APL-SE as credential data.
Lightweight Joint Loss 2D Pose Estimation Network Based onCM-RTMPose

Human pose estimation tasks often need to be deployed on edge devices. While existing human pose estimation networks can achieve good accuracy, their complex network structure leads to slow inference speed, which is not suitable for real-time tasks. At the same time, the large model structure is not conducive to model deployment. To address this issue, increasingly lightweight networks have been proposed in recent years, but existing lightweight networks have a certain gap in model accuracy compared to traditional pose estimation networks. We enhance the feature extraction and keypoint reﬁnement capabilities of the model by adding spatial attention mechanism and using the transformer module Meta3D, which is more suitable for pose estimation tasks. We trained a lightweight network CM-RTMpose on the COCO dataset, which achieved an AP value of 69.8 % , surpassing most existing lightweight pose estimation networks. To demonstrate the eﬀectiveness of our method, we conducted corresponding ablation experiments on the COCO and OCHuman datasets. The experiments showed that our method achieved an AP value of 66.1 % on the OCHuman dataset, surpassing the baseline network.
Identi�cation of a Cinnamoyl-CoA Reductase Involved in Cinnamaldehyde Biosynthesis from Cinnamomum cassia

A signi�cant accumulation of cinnamaldehyde has been found in the barks of Cinnamomum cassia, which are used in traditional Chinese medicine. Cinnamaldehyde exhibits various pharmacological properties such as anti-inammatory, analgesic, and stomachic effects. However, further con�rmation of the biosynthetic pathway for cinnamaldehyde is needed. In this study, we analyzed 15 transcriptomes from �ve different tissues to understand the accumulation of active components and identify the genes responsible for cinnamaldehyde biosynthesis. Our transcriptome database contained nearly all genes associated with the cinnamaldehyde pathway, with the majority of them demonstrating high abundance in branch barks and barks. We successfully cloned C. cassia cinnamoyl-CoA reductase (CcCCR1), a key gene in the biosynthesis of cinnamaldehyde, and found that its expression pattern mirrored the cinnamaldehyde content level. The recombinant CcCCR1 protein e�ciently converted cinnamoyl-CoA into cinnamaldehyde. Compared to Arabidopsis thaliana cinnamoyl-CoA reductase 1 (AtCCR1), CcCCR1 exhibited approximately 17-fold higher catalytic e�ciency (kcat/Km). Molecular docking studies also indicated superior catalytic activity of CcCCR1 compared to AtCCR1, which can be utilized for engineering higher cinnamaldehyde production as previously reported. These �ndings provide valuable insights for the functional characterization of enzyme-coding genes and hold potential for future engineering of cinnamaldehyde biosynthetic pathways.
Computers and Fluids

In this article we develop a high order accurate method to solve the incompressible boundary layer equations in a provably stable manner. We first derive continuous energy estimates, and then proceed to the discrete setting. We formulate the discrete approximation using high-order finite difference methods on summation-by-parts form and implement the boundary conditions weakly using the simultaneous approximation term method. By applying the discrete energy method and imitating the continuous analysis, the discrete estimate that resembles the continuous counterpart is obtained proving stability. We also show that these newly derived boundary conditions removes the singularities associated with the null-space of the nonlinear discrete spatial operator. Numerical experiments that verifies the high-order accuracy of the scheme and coincides with the theoretical results are presented. The numerical results are compared with the well-known Blasius similarity solution as well as that resulting from the solution of the incompressible Navier–Stokes equations.
MIT Open Access Articles Dynamic Pricing Under Debt: Spiraling Distortions and Efficiency Losses

Firms often ﬁnance their inventory through debt and subsequently sell it to generate proﬁts and service the debt. Pricing of products is consequently driven by both inventory and debt servicing considerations. We show that limited liability under debt induces sellers to charge higher prices and to discount products at a lower pace. We ﬁnd that these distortions result in revenue losses that compound over time, leading to some form of performance spiral down. We quantify the extent to which these ine ﬃ ciencies can be mitigated by practical debt contract terms that emerge as natural remedies from our analysis, and ﬁnd debt amortization or ﬁnancial covenants to be the most e ﬀ ective, followed by debt relief and early repayment options