Miracle-dz/UniFAR-FTUs huggingface dataset:
Elements and Materials Improve the FDM Products: A Review

This work aims to provide a review of available published literature that explores the opportunities to improve the quality of fused deposit modelling (FDM) products, particularly in medical applications. The paper presents details concerning the basis of the technology, process parameter settings and their responses, and reviews the properties of common FDM engineering/bio-materials and the available methods applied for improving their performance. Based on the researches which have been reviewed, FDM technology works within a complex environment from process parameters. Thus, it can achieve good results only with the proper settings for these parameters according to the properties of the material used. Improving the polymers is essentially based on the correct selection of additive materials, which can particularly enhance the key property/properties in the matrix material. This review provides a brief insight into FDM technology, provides an idea of the process parameter settings, the available materials and ways of modifying their properties to consequently improve the quality of FDM products.
Graphene Composites

This chapter reviews recent development of graphene-based polymer composites. The formation of graphene oxide and graphene are a vital two dimensional (2D) material has received a lot of research interest in commercialization aspect due to its excellent electrical, thermal as well as mechanical properties at very low filler content. In this manner, utilization of graphene-based polymer composites with different polymer matrixes have been attracted increasing attention in recent years for both fundamental studies and applied research into industrial applications in many fields. Herein, novel properties of polymer (epoxy, polystyrene, and PANI) / graphene composites will be reviewed along with detailed examples drawn from the scientific literature. Keywords: Graphene-based polymer composites, thermo-mechanical properties, two dimensional (2D) materials
The Effect of Doping of Lead with Lithium and Zinc with Strontium on the Kinetics and Phase Formation in a Number of Low-Melting Eutectic Systens User in Electronics and Heat-Transfer Agents

The effect of Li and Sr impurities on the kinetics and structure formation of alloys in the Sn - Pb, In - Zn, Sn - Zn systems used in the soldering of instrument nodes in electronics has been investigated. The XPS method showed that under the given experimental conditions and the indicated concentrations of lithium impurities in lead and strontium in zinc, there are no prerequisites for the formation of chemical compounds, which is explained by an insignificant impurity content, although a significant amount of chemical compounds is formed according to state diagrams. It was also established that impurities affect the kinetics of phase growth in the junction zone.
The Application of Postactivation Potentiation Methods to Improve Sprint Speed

THIS ARTICLE EXAMINES THE APPLICATION OF A VARIETY OF MODALITIES TO ELICIT A POST-ACTIVATION POTENTIATION (PAP) RESPONSE IN SPRINTING. WE PRESENT THE EXISTING LITERA-TURE ON THE ACUTE EFFECTS OF BACK SQUATS, POWER CLEANS, PLYOMETRICS, AND SLED PULL-ING ON SPRINT DISTANCES RANGING FROM 5 TO 50 M. WE ALSO DISCUSS AND PROVIDE AN EXAMPLE OF HOW COACHES CAN ASSESS THE INDIVIDUAL EFFECTS OF PAP PROTOCOLS ON THEIR ATHLETES TO IDENTIFY WHETHER A PROTOCOL ELICITS AN ACUTE IMPROVEMENT OR IMPAIRMENT IN PERFORMANCE. FINALLY, WE PROVIDE PRACTICAL RECOM-MENDATIONS ON HOW COACHES CAN INCORPORATE THESE METHODS INTO A SPRINT TRAIN-ING SESSION.
The Internet of Things for Crowd Panic Detection

Crowd behavior detection is important for the smart cities applications such as people gathering for different events. However, it is a challenging problem due to the internal states of the crowd itself and the surrounding environment. This paper proposes a novel crowd behavior detection framework based on a number of parameters. We first exploit a computer vision approach based on scale invariant feature transform (SIFT) to classify the crowd behavior either into panic or normalness. We then consider a number of other parameters from the surroundings namely crowd coherency, social interaction, motion information, randomness in crowd speed, internal chaos level, crowd condition, crowd temporal history, and crowd vibration status along with time stamp. Subsequently, these parameters are fed to deep learning model during training stage and the behavior of the crowd is detected during the testing stage. The experimental results show that proposed method renders significant performance in terms of crowd behavior detection.
Figurative Reasoning and Informatics: Metaphors in the Healthcare Room

This tutorial highlights opportunities for clinical informatics to introduce new perceptual-cognitive models involving figurative-metaphorical reasoning that will more faithfully reflect the flow of clinical practitioners’ reasoning and actions. It is designed for professionals who focus on clinical informatics systems and their foundations in biomedical and health informatics and cognitive science. The level will be introductory. We raise critical questions arising from recent findings in cognitive science and neuroscience that present serious challenges to current paradigms of knowledge representation and understanding in Artificial Intelligence (AI) and statistical thinking, both relying on categorical and classification/generalization assumptions from traditional analytic philosophy, upon which they build. We describe challenging issues of clinical healthcare informatics which incorporate novel scientific approaches on language interpretation and its relationship with human perception, cognition and interaction. These are essential for developing new approaches to clinical and biomedical informatics problems incorporating the “bodies-as-mechanisms” metaphors used in almost all clinical reasoning with the practical heuristics of clinical care in populations. We describe how imaginative computational modeling, including natural language interpretation that introduces models for metaphors, together with figurative language, sketches, and images, are essential to convey concepts and actions in clinical practice. How we build “continents” of biomedical and health knowledge from “oceans” of data will benefit from advances in such figurative reasoning informatics.
Fragment-Driven Natural Language Interaction with Databases

Retrieving data from a relational database is a challenge for nontechnical users. While SQL is a formidable swiss army knife for database tasks, even its core functionality, such as the ability to join tables, remains opaque for many users. This challenge is exacerbated by the fact that many production databases have complex schemas. Consequently, several lines of research [3, 8, 9, 11] have focused on helping less-technical users access databases via a natural language interface to database (NLIDB). Several NLIDBs [3, 8, 10] follow a common interaction model: N1. The user issues a free-form natural language query (NLQ) describing their request. N2. The system generates candidate SQL queries from the NLQ. N3. The user selects one of the SQL queries (or an intermediate representation of the SQL [3]), or returns to N1 if none of the SQL queries match the request. N4. The system executes the SQL query and returns an answer. One pitfall of this interaction model is in N3, where the user is expected to select the correct SQL query from a list of candidates. Given that one of our goals in developing an NLIDB is to assist non-technical users without knowledge of SQL, it is contradictory to expect the user to understand standalone SQL queries without any additional annotation during the interaction. In addition, several previous systems lack transparency in the translation process, whether by producing SQL queries with little indication as to how they were produced [8, 10, 11] or requiring users to understand complex intermediate representations [3]. We propose an alternative fragment-driven interaction model, where the system provides an explanation as to how the natural language produced the resulting SQL: I1. The user issues a free-form NLQ describing their request. I2. The system decomposes and rephrases the NLQ into natural language fragments (NLF) which each map to a portion of a generated SQL query. I3. The user views the system interpretation and modifies their NLQ by removing NLFs or adding suggested ones, which also modifies the resulting SQL. I4. The system executes the final SQL query and returns an answer. This interaction model enables the user to interact with the system purely in natural language and to make incremental modifications to their resulting database query without having to learn any SQL. In addition, for users unfamiliar with SQL, transparently displaying the mappings from NLF to SQL can provide confidence in the resulting query.
Speech to text and text to speech recognition systems-Areview

: In present industry, communication is the key element to progress. Passing on information, to the right person, and in the right manner is very important, not just on a corporate level, but also on a personal level. The world is moving towards digitization, so are the means of communication. Phone calls, emails, text messages etc. have become an integral part of message conveyance in this tech-savvy world. In order to serve the purpose of effective communication between two parties without hindrances, many applications have come to picture, which acts as a mediator and help in effectively carrying messages in form of text, or speech signals over miles of networks. Most of these applications find the use of functions such as articulatory and acoustic-based speech recognition, conversion from speech signals to text, and from text to synthetic speech signals, language translation amongst various others. In this review paper, we’ll be observing different techniques and algorithms that are applied to achieve the mentioned functionalities.
Functional Properties, Nutritional and Sensory Qualities of Wheat Biscuit Fortified with Defatted Dioclea reflexa Seed Flours

Dioclea reflexa was processed into flour and used to supplement wheat flour in the percentages of 0, 2.5, 5, 7.5, 10, 12.5 and 15 for biscuit production. Flour blends were evaluated for functional and pasting characteristics, while biscuits were analysed for proximate composition and sensory qualities. Proximate analysis results showed significant (p≤0.05) increase in protein (9.83 – 13.85%), fat (3.86 – 4.72%), fiber (2.03 3.84%), while moisture (10.43 -9.83%) and carbohydrate (70.49-60.95) content decreased with inclusion of Dioclea reflexa. No significant differences (p≥0.05) occurred in the sensory qualities of products from 100% wheat and 92.5: 7.5 flour blend. Hence acceptable biscuit from 92.5: 7.5 (wheat: Dioclea reflexa) blend have been formulated, which could enhance the nutritional wellness of the target consumers.
A New Approach to the Fraenkel Conjecture for Low n Values

We present a new approach to deal with Fraenkel’s conjecture, which describes how the integers can be partitioned into sets of rational Beatty sequences, in the case where the numerators of the moduli are equal. We use this approach to give a new proof of the known n = 4 case when the numerators are equal.
Pixels: Multiversion Wide Table Store for Data Lakes

Data lake can be considered as the place where massive data is continuously ingested, stored, evolved and consumed. As a storage, it is decoupled from computation and shared by various analytic applications. In practice, a data lake can be built upon massively scalable distributed ﬁle system (e.g. HDFS) or cloud storage (e.g. Amazon S3). In data lakes, wide tables with hundreds or even thousands of columns are often seen. They can be naturally wide [2, 3, 4] or denormalized from non-wide tables [6]. Wide table is inevitable for: (1) it eliminates distributed joins, which are the major bottleneck of performance and scalability in distributed environment. (2) it is ﬂexible to structure the raw data. However, there are still some critical problems to be addressed: (1) a storage model should adapt eﬃciently to the rapid evolution of application needs in data lakes. (2) wide table may change access pattern in current column stores from sequential dominated to random dominated [4], so that dedicated layout optimization is needed. Focusing on these problems, we present the idea of building a multiversion store for data lakes which is optimized for wide tables. It can provide more than one order of magnitude improving query performance on wide tables compared to state-of-the-art column stores. Also, it supports eﬃcient evolution of both metadata and user data according to the changing application needs. Although optimized for wide tables, it is also suitable for normal non-wide tables.
Effect of hormone therapy on muscle strength in postmenopausal women: a systematic review and meta-analysis of randomized controlled trials.

OBJECTIVE This study aimed to evaluate the overall effects of hormone therapy (HT) on muscle strength in postmenopausal women through a systematic review and meta-analysis. METHODS PubMed, Web of Science, Embase, and the Cochrane Central Register of Controlled Trials were systematically searched from the inception dates to August 2019. Randomized controlled trials (RCTs) that compared the effects of HT with either no therapy or placebo on muscle strength in postmenopausal women were eligible. The quality of studies was assessed using the Cochrane risk of bias tool. Measurements of changes in muscle strength compared to baseline were extracted for pooled analysis. The effect size was calculated as standardized mean differences using a random effects model. RESULTS We identified nine studies with a combined population of 2,476 postmenopausal women. The studies included were assessed to be of good quality overall. The results showed that HT was not associated with muscle strength gain in postmenopausal women (standardized mean difference = 0.352; 95% confidence interval, -0.098 to 0.803; P = 0.125; I = 95.3%). The changes in muscle strength in women receiving HT were not significant. The results were unchanged when stratified by treatment type, muscle group, and treatment duration. CONCLUSIONS The use of HT was not associated with the improvement of muscle strength in postmenopausal women. This finding suggested that HT might not improve muscle strength or that the effect size was too small to identify significant therapeutic efficacy.
Exploring Social Subtypes in Autism Spectrum Disorder: A Preliminary Study

Impairments in social functioning are considered a hallmark diagnostic feature of autism spectrum disorder (ASD). Yet, individuals diagnosed with ASD vary widely with respect to specific presentation, severity, and course across different dimensions of this complex symptom domain. The aim of this investigation was to utilize the Stanford Social Dimensions Scale (SSDS), a newly developed quantitative measure providing parental perspective on their child's social abilities, in order to explore the existence of homogeneous subgroups of ASD individuals who share unique profiles across specific dimensions of the social domain. Parents of 164 individuals with ASD (35 females, 129 males; meanage = 7.54 years, SD = 3.85) completed the SSDS, the Social Responsiveness Scale (SRS‐2) and the Child Behavior Checklist (CBCL). Data on children's verbal and nonverbal intellectual functioning (FSIQ) were also collected. The Latent Profile Analysis was used to classify participants according to the pattern of SSDS subscale scores (Social Motivation, Social Affiliation, Expressive Social Communication, Social Recognition, and Unusual Approach). Five profiles were identified. Profiles did not differ in terms of chronological age nor gender distribution but showed distinct patterns of strengths and weaknesses across different social components rather than simply reflecting a severity gradient. Profiles were further differentiated in terms of cognitive ability, as well as ASD and internalizing symptom severity. The implications of current findings and the necessary further steps toward identifying subgroups of individuals with ASD who share particular constellation of strengths and weaknesses across key social domains as a way of informing personalized interventions are discussed. Autism Res 2020. © 2020 International Society for Autism Research, Wiley Periodicals, Inc.
PharmGKB summary: lamotrigine pathway, pharmacokinetics and pharmacodynamics

1744-6872 Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved. DOI: 10.1097/FPC.0000000000000397 R.B.A. is a stockholder in Personalis Inc. and 23andMe, and a paid advisor for Youscript. There are no conflicts of interest for the remaining authors. PharmGKB summary: lamotrigine pathway, pharmacokinetics and pharmacodynamics Taraswi Mitra-Ghosh*, Samuel P. Callisto*, Jatinder K. Lamba, Rory P. Remmel, Angela K. Birnbaum, Julia M. Barbarino, Teri E. Klein and Russ B. Altman
Extracellular vesicle miRNA-21 is a potential biomarker for predicting chronic lung disease in premature infants.

Premature infants are often exposed to positive pressure ventilation and supplemental oxygen which leads to the development of CLD. There are currently no standard serum biomarkers used for prediction or early detection of patients who go on to develop CLD. MicroRNAs (miRNAs) are a novel class of naturally-occurring, short non-coding substances that regulate gene expression at the post-transcriptional level, and cause translational inhibition and/or mRNA degradation and present in body fluids packaged in extracellular vesicles (EVs), rendering them remarkably stable. Our aim was to evaluate miRNAs identified in serum EVs of premature infants as potential biomarkers for CLD. Serum EVs were extracted from premature infants at birth and 28th day of life (DOL), Using a human miRNA array we identified 62 miRNAs that were universally expressed in CLD patients and non-CLD patients. Of the 62 miRNAs, 59 miRNAs and 44 miRNAs were differentially expressed on DOL0 and DOL28 in CLD and non-CLD patients respectively. Of these miRNAs, serum EVs miR-21 was upregulated in CLD patients on DOL28 compared with levels at birth, and downregulated in non-CLD patients on DOL28 compared with levels at birth. In neonatal mice exposed to hyperoxia for 7days, as a model of CLD, 5 miRNAs (miR-34a, miR-21, miR-712, miR-682, miR-221) were upregulated, and 7 miRNAs (miR-542-5p, miR-449a, miR-322, miR-190b, miR-153, miR-335-3p, miR-377) were downregulated. MiR-21 was detected as a common miRNA that changed in CLD patients and in the hyperoxia exposed mice. We conclude that EV miR-21 may be a biomarker of CLD.
Direct oral anticoagulants for the treatment of left ventricular thrombus - a new indication? A meta-summary of case reports DOACs in left ventricular thrombosis.

Left ventricular thrombus (LVT) can be a consequence of cardiac diseases such as reduced ejection fraction heart failure (HFrEF) and acute myocardial infarction (MI). Currently the guidelines recommend the use of warfarin for the treatment of this condition. However, there are increasing reports of patients with LVTs being treated with direct oral anticoagulants (DOACs), for several reasons. We set out to review the available literature to assess the safety and the efficacy of this approach. We analyzed 52 cases, extrapolated by 34 papers contained in literature, focusing on the characteristics of patients, treatment, outcome and follow-up. Rivaroxaban was the most commonly used DOAC, followed by apixaban. The diagnosis of LVT and the follow-up were mainly performed by transthoracic echocardiography. The thrombus resolved in 45 patients (92%) out of 49 (there are no data available regarding the outcome of 3 patients) and failed to resolve in 4 patients treated with DOACs. The resolution occurred in a median of 32 days. DOACs shown to be a reasonable and valid option for the treatment of LVT. Our study provides a rationale for a prospective randomized controlled trial.
Dual Targeting of the p38 MAPK-HO-1 Axis and cIAP1/XIAP by Demethoxycurcumin Triggers Caspase-Mediated Apoptotic Cell Death in Oral Squamous Cell Carcinoma Cells

Demethoxycurcumin (DMC) is a curcumin analogue with better stability and higher aqueous solubility than curcumin after oral ingestion and has the potential to treat diverse cancers, including oral squamous cell carcinoma (OSCC). The aim of this study was to investigate the anticancer effects and underlying mechanisms of DMC against OSCC. We found that DMC suppressed cell proliferation via simultaneously inducing G2/M-phase arrest and cell apoptosis. Mechanistic investigations found that the downregulation of cellular IAP 1 (cIAP1)/X-chromosome-linked IAP (XIAP) and upregulation of heme oxygenase-1 (HO-1) were critical for DMC-induced caspase-8/-9/-3 activation and apoptotic cell death. Moreover, p38 mitogen-activated protein kinase (MAPK) and c-Jun N-terminal kinase (JNK)1/2 were activated by DMC treatment in OSCC cells, and only the inhibition of p38 MAPK significantly abolished DMC-induced HO-1 expression and caspase-8/-9/-3 activation. The analyses of clinical datasets revealed that patients with head and neck cancers expressing high HO-1 and low cIAP1 had the most favorable prognoses. Furthermore, a combinatorial treatment of DMC with epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor, gefitinib, significantly enhanced the inhibitory effect of gefitinib on the proliferation of OSCC cells. Overall, the current study supported a role for DCM as part of a therapeutic approach for OSCC through suppressing IAPs and activating the p38-HO-1 axis.
Experimental study of 99mTc-aluminum oxide use for sentinel lymph nodes detection

The purpose of the study was a comparative research in the possibility of using the radiopharmaceuticals 99mTc-Al2O3 and 99mTc-Nanocis for visualizing sentinel lymph nodes. The measurement of the sizes of 99mTc-Al2O3 and 99mTc-Nanocis colloidal particles was performed in seven series of radiopharmaceuticals. The pharmacokinetics of 99mTc-Al2O3 and 99mTc-Nanocis was researched on 50 white male rats. The possibility of the use of 99mTc-Al2O3 and 99mTc-Nanocis for lymphoscintigraphy was studied in the experiments on 12 white male rats. The average dynamic diameter of the sol particle was 52–77 nm for 99mTc-Al2O3 and 16.7–24.5 nm for 99mTc-Nanocis. Radiopharmaceuticals accumulated in the inguinal lymph node in 1 hour after administration; the average uptake of 99mTc-Al2O3 was 8.6% in it, and the accumulation of 99mTc-Nanocis was significantly lower—1.8% (p < 0.05). In all study points the average uptake of 99mTc-Al2O3 in the lymph node was significantly higher than 99mTc-Nanocis accumulation. The results of d.
Can’t Buy Me Love (or Friendship): Social Consequences of Financially Contingent Self-Worth

Although people may think that money improves one’s relationships, research suggests otherwise. Focusing on money is associated with spending less time maintaining relationships and less desire to rely on others for help. But why does focusing on money relate to worse social outcomes? We propose that when people base their self-esteem on financial success—that is, have financially contingent self-worth—they are likely to feel pressured to pursue success in this domain, which may come at the expense of spending time with close others. Consistent with this idea, results of four cross-sectional studies (N = 2,439) and a daily diary study (N = 246) revealed that basing one’s self-worth on financial success is associated with greater feelings of loneliness and social disconnection, and this may be related to experiencing less autonomy and spending less time with family and friends.
ISC Costs of Scarcity 042512a

2 CONTENTS. 2 CLAIM. 3 SCARCITY -­ ABUNDANCE FRAMEWORK. 4 THREE BUILDING BLOCKS . 4 THREE LEVELS OF PERCEIVED REALITY . 5 COSTS OF SCARCITY.6 QUALITATIVE ASSESSMENT.10 FIRMS OF ENDEARMENT. 10 PETCO. 11 GLOBAL PROFESSIONAL SERVICES ORGANIZATION . 12 QUANTITATIVE ASSESSMENT . 14 COMING FULL CIRCLE.18 RESEARCH METHODOLOGY . 19 ACKNOWLEDGEMENTS.19 REFERENCES.19