Miracle-dz/UniFAR-FTUs huggingface dataset:
Behavioural and neurophysiological responses to written naming treatment and high definition tDCS: a case study in advanced primary progressive aphasia

ABSTRACT Background Primary progressive aphasia (PPA) is associated with progressive loss of language functions in the context of irreversible neurodegeneration, for which there is no cure. Speech-language therapy can help preserve language abilities, and most promisingly, interventions like transcranial direct current stimulation (tDCS) have been shown to augment the effectiveness of therapy. However, the underlying mechanism for this enhancement is unknown. Objectives We evaluated the behavioural and physiological (using resting-state magnetoencephalography [rsMEG]) effects of contemporary naming treatment provided with tDCS in a patient with an advanced case of nonfluent variant PPA (P01; 67 year old male). P01 was mute but had preserved written abilities, which we aimed to enhance with written naming therapy and excitatory or anodal-tDCS. We hypothesized greater improvement in written performance, particularly immediate gains, maintenance, and generalization, after anodal- than sham-tDCS. Additionally, reductions in oscillatory abnormal activity, as indicated by rsMEG, were expected after repeated sessions of anodal-tDCS with the naming treatment. Methods A written picture naming therapy was paired with five sessions of anodal and five sessions of sham high-definition tDCS over two weeks. Anatomical and neurophysiological abnormalities were mapped with structural-MRI and rsMEG, respectively. TDCS was targeted towards an anatomically intact left supramarginal gyrus. The therapy-induced changes in written performance were evaluated on both trained and untrained pictures using Levenshtein Distances (LD). The neurophysiological changes were evaluated by comparing spectral relative power estimates in frequency bands ranging from delta to low-gamma (1–50 Hz), before and after therapy. All evaluations were completed immediately after therapy with sham- and anodal-tDCS, and at a 3-month follow-up. Results Compared to sham-tDCS, anodal-tDCS augmented the immediate therapy-induced gains on trained items, as indicated by reductions in LD scores, reflecting improvement in written performance, particularly for more difficult target words. Neural activity at the stimulation spot and in surrounding and remote regions exhibited reduced oscillatory slowing, both immediately after one session (short-term) and after completion of five sessions (long-term) of anodal-tDCS compared to sham-tDCS. This is manifested as decreased theta (1–4 Hz) and increased beta and low-gamma (15–50 Hz) power. No additional gains with anodal-tDCS were found on untrained items (generalization) or at 3-month follow-up (maintenance). Conclusions Our findings suggest that five sessions of anodal-tDCS can improve written performance by partially reversing abnormal neural activity and thus boosting the functional capacity of the structurally intact cortex. Longer duration of treatment may be needed for additional gains in maintenance and generalization with anodal-tDCS.
The relative and interactive impact of multiple risk factors in schizophrenia spectrum disorders: a combined register-based and clinical twin study

Abstract Background Research has yielded evidence for genetic and environmental factors influencing the risk of schizophrenia. Numerous environmental factors have been identified; however, the individual effects are small. The additive and interactive effects of multiple risk factors are not well elucidated. Twin pairs discordant for schizophrenia offer a unique opportunity to identify factors that differ between patients and unaffected co-twins, who are perfectly matched for age, sex and genetic background. Methods Register data were combined with clinical data for 216 twins including monozygotic (MZ) and dizygotic (DZ) proband pairs (one or both twins having a schizophrenia spectrum diagnosis) and MZ/DZ healthy control (HC) pairs. Logistic regression models were applied to predict (1) illness vulnerability (being a proband v. HC pair) and (2) illness status (being the patient v. unaffected co-twin). Risk factors included: A polygenic risk score (PRS) for schizophrenia, birth complications, birth weight, Apgar scores, paternal age, maternal smoking, season of birth, parental socioeconomic status, urbanicity, childhood trauma, estimated premorbid intelligence and cannabis. Results The PRS [odds ratio (OR) 1.6 (1.1–2.3)], childhood trauma [OR 4.5 (2.3–8.8)], and regular cannabis use [OR 8.3 (2.1–32.7)] independently predicted illness vulnerability as did an interaction between childhood trauma and cannabis use [OR 0.17 (0.03–0.9)]. Only regular cannabis use predicted having a schizophrenia spectrum diagnosis between patients and unaffected co-twins [OR 3.3 (1.1–10.4)]. Conclusion The findings suggest that several risk factors contribute to increasing schizophrenia spectrum vulnerability. Moreover, cannabis, a potentially completely avoidable environmental risk factor, seems to play a substantial role in schizophrenia pathology.
Roasting Coffee Sales Prediction for Demand Satisfaction

The purpose of this study is to predict sales of coffee roasting at the Café (Coffee and Roastery) Philosophy in 2021. This research was conducted using sales data from 2018 – 2020. The primary data for roasted coffee is sales data. This type of research is quantitative, using excel software tools. This study indicates that the forecasting of coffee roasting sales in the Café philosophy (Coffee and Roastery) suggests an increase in sales, although not too much because of limited production capacity. Keywords—forecasting, moving average, single moving average
Traducción y análisis de validez de contenido del instrumento Opening Minds Scale for Healthcare Practitioners (OMS-HC) para la evaluación del estigma hacia la enfermedad mental en profesionales de la salud en Chile.

REV. CHIL NEURO-PSIQUIAT 2021; 59 (2); 91-101 www.sonepsyn. cl 91 Traducción y análisis de validez de contenido del instrumento Opening Minds Scale for Healthcare Practitioners (OMS-HC) para la evaluación del estigma hacia la enfermedad mental en profesionales de la salud en Chile. Translation and content analysis of the Opening Minds Scale for Healthcare Practitioners (OMS-HC) for the assessment of stigma towards mental illness in health care professionals in Chile
Predicting the potential of capacitive deionization for the separation of pH‐dependent organic molecules

One of the main steps in the biotechnological production of chemical building blocks, such as, e.g. bio‐based succinic acid which is used for lubricants, cosmetics, food, and pharmaceuticals, is the isolation and purification of the target molecule. A new approach to isolate charged, bio‐based chemicals is by electrosorption onto carbon surfaces. In contrast to ion exchange, electrosorption does not require additional chemicals for elution and regeneration. However, while the electrosorption of inorganic salts is well understood and in commercial use, the knowledge about electrosorption of weak organic acids including the strong implications of the pH‐dependent dissociation and their affinity towards physical adsorption must be expanded. Here, we show a detailed discussion of the main pH‐dependent effects determining the achievable charge efficiencies and capacities. An explicit set of equations allows the fast prediction of the named key figures for constant voltage and constant current operation. The calculated and experimental results obtained for the electrosorption of maleic acid show that the potential‐free adsorption of differently protonated forms of the organic acid play a dominating role in the process. At pH 8 and a voltage threshold of 1.3 V, charge efficiencies of 25% and capacities around 40 mmol/kg could be reached for a constant current experiment. While this capacity is clearly below that of ion exchange resins, the required carbon materials are inexpensive and energy costs are only about 0.013 €/mol. Therefore, we anticipate that electrosorption has the potential to become an interesting alternative to conventional unit operations for the isolation of charged target molecules.
Frontiers in Dentistry

Article type: Original Article Objectives: One of the main problems with polymethyl methacrylate (PMMA) used for the fabrication of oral removable appliances is plaque accumulation due to surface porosities. Incorporation of antimicrobial agents in this material might help tackle this problem. The aim of this study was to evaluate the antimicrobial activity of PMMA acrylic resin incorporated with propolis nanoparticles (PNPs). Materials and Methods: Antimicrobial properties of acrylic resin incorporated with PNPs were assessed against Streptococcus mutans (S. mutans), Streptococcus sanguinis (S. sanguinis), Lactobacillus acidophilus (L. acidophilus) and Candida albicans (C. albicans). Acrylic discs were fabricated in four groups: A control group without PNPs and three experimental groups containing 0.5%, 1% and 2% concentrations of PNPs. Disc agar diffusion (DAD) test was performed to determine the antimicrobial effects of PNPs by measuring the microbial growth inhibition zones on Muller-Hinton agar plates. The eluted components test evaluated the viable counts of microorganisms in liquid medium after 24 and 72h. Finally, biofilm inhibition test assessed the efficacy of PNPs for inhibition of biofilm formation. P<0.05 was considered significant. Results: The acrylic discs failed to produce microbial inhibition zones in the DAD test. Discs containing 1% and 2% nanoparticles showed anti-biofilm effects on all four microbial species. The colony counts of all microorganisms significantly decreased following exposure to liquids containing nanoparticles after 24 and 72h in eluted component test. Conclusion: PMMA acrylic discs incorporated with PNPs presented some antimicrobial properties against S. mutans, S. sanguinis, L. acidophilus, and C. albicans.
A New Quantum-computing-based Algorithm for Robotic Arms and Rigid Bodies’ Orientation

Quantum computing model of robotic arm orientation is presented. Spherical and vector coordinates, a homogenous rotation matrix, Pauli gates and quantum rotation operators are used to formulate the orientation model and establish a new algorithm. The quantum algorithm uses a single qubit to compute orientation and has the advantage of operation reversibility. This was validated for a SCARA robot and a five-joints articulated robotic arm. The obtained results show the effectiveness of the proposed methodology.
Can the Internet narrow regional economic disparities?

ABSTRACT Using city-level data from China for the period 2003–15, this paper studies how the Internet affects economic disparities between cities through its heterogeneous impact on the economic growth of cities with different penetration rates and population sizes. The results show that the Internet widens the economic disparities between cities with low Internet penetration rates and cities with high Internet penetration rates, and even if the penetration gap between cities is bridged in the future, the Internet will still widen the economic gap between large and small cities due to the reinforcing effect of city size.
Adaptive User-Managed Service Placement for Mobile Edge Computing via Contextual Multi-Armed Bandit Learning

Mobile Edge Computing (MEC), envisioned as a cloud extension, pushes cloud resource from the network core to the network edge, thereby meeting the stringent service requirements of many emerging computation-intensive mobile applications. Many existing works have focused on studying the system-wide MEC service placement issues, personalized service performance optimization yet receives much less attention. As motivated, in this paper we propose a novel adaptive user-managed service placement mechanism, which jointly optimizes a user's perceived-latency and service migration cost, weighted by user-specific preferences. We first formulate the user-managed dynamic service placement process with limited system information as a contextual multi-armed bandit learning problem. In particular, we investigate both cases without and with neighboring edge feedbacks, where the later considers edge information sharing for more informed decision making. For both cases, we design lightweight Thompson-sampling based online learning algorithms, which can efficiently assist the user to make adaptive service placement decisions. We further conduct a novel information-directed theoretical analysis on the regret bound of the proposed online learning algorithms and reveal the structural impact of edge information sharing. Extensive evaluations demonstrate the superior performance gain of the proposed adaptive user-managed service placement mechanism over existing learning schemes.
Distributed real-time temperature and energy control of energy efficient buildings via geothermal heat pumps

Geothermal Heat Pumps (GHPs) are a type of Heating Ventilation and Air Conditioning (HVAC) systems that use low-temperature resources from soil and groundwater for heating/cooling. In recent years, there is an increasing interest in GHP systems due to their high energy efficiency and abundant geothermal resources. Thus, the optimization and control design of the GHP system has become a hot topic. On the other hand, as the GHP system is an ideal responsive load, the mechanism design for the GHP system to realize demand response (DR) in a Virtual Power Plant (VPP) without affecting user comfort is particularly essential. In this paper, we propose a distributed real-time temperature and energy management method via the GHP systems for multi-buildings, where both floor and radiator heating/cooling distribution subsystems in multiple thermal zones are considered. We design an energy demand response mechanism for a single GHP to track the given energy consumption command for participating in the VPP aggregation/disaggregation. Besides, a coordination mechanism for multiple GHPs is designed for the community-level operator in joining the VPP aggregation/disaggregation. Both designed schemes are scalable and do not need to measure or predict any exogenous disturbances such as the outdoor temperature and the heating disturbances from external sources, e.g., user activity and device operation. Finally, four numerical examples for the simulation of two different scenarios demonstrate the effectiveness of the proposed methods.
Exploring the Galaxyfly Family to Build Flexible-Scale Interconnection Networks

Interconnection networks play an essential role in the architecture of high-performance computing (HPC) systems. In this article, we explore the Galaxyfly family to build flexible-scale interconnection networks. Galaxyfly is guaranteed to retain a small constant diameter while achieving a flexible tradeoff between network scale and bisection bandwidth. Galaxyfly not only supports small-scale interconnection networks with smaller diameter but also lowers the demands for high-radix routers and is able to utilize routers with moderate radix to build exascale interconnection networks. We analyze the constructible configuration of Galaxyfly and evaluate the properties of Galaxyfly. We conduct extensive simulations and analysis to evaluate the performance, cost, and power consumption of Galaxyfly on physical layout against state-of-the-art topologies. The results show that our design achieves better performance than most existing topologies under typical HPC workloads, and is cost-effective to deploy for exascale HPC systems.
Image retrieval of wool fabric. Part III: based on aggregated convolutional descriptors and approximate nearest neighbors search

For sample reproduction, texture and color are both significant when the consumer has no specific or individual demands or cannot describe the requirements clearly. In this paper, an effective method based on aggregated convolutional descriptors and approximate nearest neighbors search was proposed to combine the texture and color feature for wool fabric retrieval. Aggregated convolutional descriptors from different layers were combined to characterize the wool fabric image. The approximate nearest neighbors search method Annoy was adopted for similarity measurement to balance the trade-off between the search performance and the elapsed time. A wool fabric image database containing 82,073 images was built to demonstrate the efficacy of the proposed method. Different feature extraction and similarity measurement methods were compared with the proposed method. Experimental results indicate that the proposed method can combine the texture and color feature, being effective and superior for image retrieval of wool fabric. The proposed scheme can provide references for the worker in the factory, saving a great deal of labor and material resources.
Understanding curriculum design in the perceptions and practices of classroom music teachers in the lower secondary school in England

Abstract Curriculum design is a domain that infrequently forms a discrete element of initial teacher training, or continuing professional development for music teachers in English secondary schools. Classroom music teachers, teaching Key Stage 3 (KS3) learners (11–14-year olds), are, however, required to design their own curriculum. Teachers are accountable to school leaders for curricula they implement, and the outcomes from their selected approaches. This article discusses classroom music curriculum practices and their significance in music education. The research project was conducted with music teachers from schools in the East and West Midlands of England, utilising questionnaires and semi-structured interviews. Research findings are conceptualised in a model of music curriculum activity. The research thereby facilitates discussion of unacknowledged complexities and tacit teacher planning practices in music curriculum design.
Systematic Review of Occupational Therapy Interventions to Enhance Cognitive Development in Children 0–5 Years: Part 2, At-Risk Due to Environmental Factors and Promoting Cognitive Development

ABSTRACT Aim: This article is the second part of a systematic review updates and broadens a previous systematic review (Frolek Clark & Schlabach, 2010) to examine the evidence for of interventions within the scope of occupational therapy practice to enhance cognitive and pre-academic development in young children with or without at-risk factors. This article is Part 2 of the review and will focus on interventions for children at-risk from environmental factors and interventions that promoting cognitive development in children ages birth to 5 years. Part 1 is published separately and focuses on children with specific diagnoses. Methods: A systematic search of studies published from 2010 to 2020 using MEDLINE, PsycINFO, CINAHL, ERIC, OTseeker, and Cochrane was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Results: Twenty-seven studies met the inclusion criteria and were critically appraised: 19 Level I, 6 Level II, and 2 Level III evidence (Part 2). Two themes are discussed within this paper (Part 2): Children At-Risk of Cognitive Delays due to Environmental Factors, and Promoting Cognitive Development. Strong strength of evidence exists for cognitive and executive functioning training programs, literacy programs, and parent interactions focused on child’s needs. Strong strength of evidence indicates explicit Tier II interventions assist preschool children in learning early literacy skills (e.g., print knowledge, letter names, letter sounds). Moderate strength of evidence supports using movement or play to enhance cognitive and executive functions in preschoolers. Conclusions: Occupational therapy practitioners working in home and preschool programs can use these evidence-based interventions to enhance cognitive development, executive functions, and pre-academic functions performance for young children with or without risk factors. Part 1 of the review also appears in this issue.
Comparison between Continuous Regular Insulin Infusion and Single Dose Subcutaneous Long Acting Insulin Injection in Intensive Care Unit

Background: Stress-induced hyperglycemia is a common metabolic disorder in Intensive Care Unit (ICU) cases (30-60%) in diabetic and non-diabetic patients. It is related to increased rates of mortality and morbidity. Objective: The aim of the current work was to compare between glycemic control in single dose long-acting subcutaneous insulin glargine injection and standard continuous regular insulin infusion in the same critical case. Patients and methods: This prospective clinical study period was 72 hours for every patient and conducted on 111 patients aged 20-70 years with targeted blood glucose (BG) level ranging from 100 to 200 mg/dl using a different calculated dose of standard insulin infusion according to conventional sliding scale for the 1st 24hr of the study before conversion into insulin glargine single dose injection with 1-hour washout transition period. Results: APACHE II score was significantly higher in “Uncontrolled hyperglycemia” group in comparison to “Uncontrolled hypoglycemia” group (P=0.030) but insignificantly different between “Controlled” group and “Uncontrolled hyperglycemia” group and between “Controlled” group and “Uncontrolled hypoglycemia” group. Daily units of insulin and mean BG level at 1st day were significantly lower in “Uncontrolled hypoglycemia” group in comparison to “Controlled” group (P=0.002 and 0.002 respectively) and “Uncontrolled hyperglycemia” group (P=0.004 and 0.006 respectively) but insignificantly different between “Controlled” group and “Uncontrolled hyperglycemia” group. While mean BG level was insignificantly different among the three groups at 2nd day, it was insignificantly different between “Controlled” group and “Uncontrolled hyperglycemia” group at 3rd day. Conclusion: It could be concluded that the use of 100% conversion single dose of long-acting insulin glargine for control of hyperglycemia in critical ICU patients can be considered as an accepted good alternative to the classic use of continuous regular insulin infusion.
Limited evidence of coupling between above and belowground functional traits in tropical dry forest seedlings

Introduction: Water availability is one of the main factors determining the distribution of woody species in the tropics. Although the functional mechanisms that determine the species tolerance to water deficit have been extensively studied in adult individuals, the responses of early ontogenetic stages have been less explored. Objective: To identify functional strategies and trait correlations between different seedlings' dimensions (leaf, stem, and root). We expect limited coordination between above and below-ground functional traits due to a single conservation-acquisition trade-off cannot capture the variability of functions and environmental pressures to which the root system is subjected. Methods: We measured 12 functional traits belonging to 38 seedling species in a tropical dry forest in Colombia. We explored the relationships between pairs of traits using Pearson correlations, and to obtain an integrated view of the functional traits, a principal component analysis (PCA) was performed. Results: The results showed limited evidence of linkage between above- and below-ground traits, but we did find significant correlations between traits for the continuum of conservative and acquisitive strategies. Root traits related to water and nutrient take capacity formed an orthogonal axis to the acquisitive-conservative continuum. Conclusions: Our results showed that dry forest seedlings have different functional strategies to cope with water deficit. The incorporation of root traits helps to explain new functional strategies not reported for leaf and stem traits. This study contributes to understanding the mechanisms that explain species coexistence and is particularly relevant for predicting future forest trajectories.