Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation Practice in a Test-free Semester

This research explored changes in the classroom evaluation practice of a summative test-free semester. In order to do this, eight schools’ plans for a so called ‘free semester’ were analyzed and focus group interviews were implemented with teachers, students, and parents respectively. A total of 33 teachers, 33 students, and 25 parents from 8 middle schools participated in focus group interviews. Each interview group consisted of 2~6 people. Interview questions were about changes in behavior and thoughts in an environment which is summative and paper-pencil test free. As a result, ten characteristics of the evaluation were found: Attempts to devise various evaluation tools, detailed formative evaluations, increased attention to individual students, more frequent and more variable evaluations, process oriented evaluations, goal based evaluations, increased burden on teachers, confused evaluation guidelines, students’ deep understanding and increased ability to express oneself.
Specifying, Verifying and Implementing a MAS : A Case study

This paper deals with the design of multi-agent systems. We demonstrate the goal-oriented agent model called Goal Decomposition Tree on an already studied multi-agent example, that of robots which must clean pieces of garbage on Mars. As we show, the model allows to prove that the agents’ behaviour indeed achieves their goal. We then compare our approach to other ones.
Self-Perceived Benefits of Cognitive Training in Healthy Older Adults

The idea that individualized, computer-based cognitive training improves cognitive functioning in non-trained domains is highly contested. An understudied area is whether cognitive training improves one’s own perception of cognitive and day-to-day functioning. Furthermore, no studies have compared working memory training to programs that train higher-level processes themselves, namely logic and planning, in improving perception of cognitive abilities. We investigated self-reported changes in: (a) cognitive errors relevant to daily life; (b) expectations regarding training; and (c) impact of training on daily life, in healthy older adults who completed working memory training or logic and planning training. Ninety-seven healthy older adults completed 8-weeks of computerized cognitive training that targeted either working memory or logic and planning. Findings were compared to a no-training control group. Participants reported fewer cognitive failures relevant to daily life after training compared to the no-training control group, with a greater reduction in errors reported by the logic and planning training group compared to the working memory training group. Trainees’ perception of training efficacy decreased over time. Nonetheless, approximately half of the participants in both training groups endorsed “some improvement” or more in self-perceived day-to-day functioning at post-testing. These results support the conclusion that individualized computerized cognitive training may enhance subjective perceptions of change and that higher level cognitive training may confer additional benefits. Findings suggest that cognitive training can enhance cognitive self-efficacy in healthy seniors.
Preferential killing of cancer cells and activated human T cells using ZnO nanoparticles

Nanoparticles are increasingly being recognized for their potential utility in biological applications including nanomedicine. Here we examine the response of normal human cells to ZnO nanoparticles under different signaling environments and compare it to the response of cancerous cells. ZnO nanoparticles exhibit a strong preferential ability to kill cancerous T cells (∼28–35 ×) compared to normal cells. Interestingly, the activation state of the cell contributes toward nanoparticle toxicity, as resting T cells display a relative resistance while cells stimulated through the T cell receptor and CD28 costimulatory pathway show greater toxicity in direct relation to the level of activation. Mechanisms of toxicity appear to involve the generation of reactive oxygen species, with cancerous T cells producing higher inducible levels than normal T cells. In addition, nanoparticles were found to induce apoptosis and the inhibition of reactive oxygen species was found to be protective against nanoparticle induced cell death. The novel findings of cell selective toxicity, towards potential disease causing cells, indicate a potential utility of ZnO nanoparticles in the treatment of cancer and/or autoimmunity.
Frequency detection from multiplexed compressed sensing of noisy signals

Signal acquisition under a compressed sensing scheme offers the possibility of acquisition and reconstruction of signals sparse on some basis incoherent with measurement kernel with sub-Nyquist number of measurements. In particular when the sole objective of the acquisition is the detection of the frequency of a signal rather than exact reconstruction, then an undersampling framework like CS is able to perform the task. In this paper we explore the possibility of acquisition and detection of frequency of multiple analog signals, heavily corrupted with additive white Gaussian noise. We improvise upon the MOSAICS architecture proposed by us in our previous work to include a wider class of signals having non-integral frequency components. This makes it possible to perform multiplexed compressed sensing for general frequency sparse signals.
Choosing and adapting design notations in the principled development of complex systems simulations for research

The use of complex system simulation as a research tool is facilitated by principled development; software quality assurance, an important part of fitness for purpose, can be assisted by use of model driven engineering (MDE) techniques. The paper addresses two key aspects of MDE for simulation development: the choice of appropriate modelling languages, and language adaptation, illustrated from a cell division and differentiation simulation development, for use in research on prostate conditions. The resulting language has potential for general modelling of reactive and transitional systems.
THOR: Text-enabled Analytics for Humanitarian Operations

In this demonstration, we present the Text-enabled Humanitarian Operations in Real-time (THOR) framework, which is being prototyped to provide visual and analytical situational awareness to humanitarian and disaster relief (HADR) planners. THOR is a collaborative effort between industrial and university research laboratories, designed with an intent to support both military and civilian HADR operations. At its core, THOR is powered by a domain-specific knowledge graph, which is derived from natural language outputs and is amenable to real-time analytics. THOR is designed to operate in low-resource linguistic environments, process heterogeneous data, including news and social media, reason about arbitrary disasters not knowable in advance, and provide advanced graphical interaction capabilities. We will demo the latest prototype of THOR using an interactive case study situation.
Analysis of insulin growth factor (IGF-1) gene in some selected monogastrics: An Insilico approach

The use of molecular marker-assisted selection has proven to be efficient and lead to the improvement in production performance in animals.1 The ability of meat production is closely associated with muscle growth. Recent researches on polypeptides growth factors have identified several growth factors such as insulin growth factors (IGFs), epidermal growth factor, transforming growth factor and platelet-derived growth factor as modulators of muscle.2,3 Insulin-like Growth Factor 1 (IGF-1) gene has been described in several researches as a candidate gene for growth.4 It regulates differentiation including the maintenance of differentiated function in numerous tissues and in specific cell types.5 IGF-1 also stimulates the anabolic and mitogenic activity of growth hormone in various tissues.6 The primary source of circulatory IGF-1 is the liver however; it is also produced locally in a tissue specific manner.7 Recent advances in high-throughput technologies have generated massive amounts of genome sequence and genotype data for a number of species. The method to identify functional synonymous polymorphism sequence (SNPs) from a pool, containing both functional and neutral SNPs is challenging by experimental protocols.8 Therefore, computational predictions have become indispensable for evaluating the disease-related impact of non-synonymous single-nucleotide variants discovered in exome sequencing.9 A number of computational methods have been developed to predict the functional effect of a non-synonymous singlenucleotide polymorphism (nsSNP) and a single-nucleotide change in a protein-coding region of a gene that causes an amino acid substitution (AAS) in the resulting protein.10 Many such methods have their roots in molecular evolution, as they use information derived from multiple sequence alignments. Most computational prediction tools for amino acid variants rely on the assumption that protein sequences observed among living organisms have survived natural selection. Therefore, evolutionarily conserved amino acid positions across multiple species are likely to be functionally important, and amino acid substitutions observed at conserved positions will potentially lead to deleterious effects on gene functions.11 Therefore, this study was design to look at non-synonymous single nucleotide polymorphism, species diversity and evolutionary relationship of igf-1 gene in some selected monogastrics animals.12
"Don't Just Stand There, Do Something!" How Effective Procedural Training Can Help Physicians Find the Right Balance Between Doing No Harm and Doing Good.

“I’m really worried about this guy,” she said. “I think he’s about to obstruct. ” As I glanced over at the man, who was sitting up and leaning forward with drool coming from his mouth, I was also worried. “He’s so swollen,” she continued. “I don’t know if I’m going to be able to intubate him. He can barely open his mouth. I think we need to prepare for a cricothyrotomy and I’ve never done one. ” As her attending on the case, I knew it might fall to me to perform this rare but lifesaving procedure of cutting through the neck to insert a tube into the trachea. Anne had performed the procedure only in the simulation lab. I had done it only five times in my career, most recently more than five years ago. I sent for the on-call surgical resident and surgical attending for help, but they were in the operating room and would not be available for half an hour. Before I could make any other calls, the man in the red jacket collapsed, fell back on the stretcher unconscious, and stopped breathing. A nurse began to do CPR while Anne looked into the man’s throat with her laryngoscope to see if she could intubate him.
Loss of Fgfr1 in chondrocytes inhibits osteoarthritis by promoting autophagic activity in temporomandibular joint

Temporomandibular joint osteoarthritis (TMJ OA) is a common degenerative disease with few effective disease-modifying treatments in the clinic. Fibroblast growth factor (FGF) signaling is implicated in articular cartilage homeostasis, but the functional roles of FGFR1 in TMJ OA remain largely unknown. In this study, we report that deletion of Fgfr1 in TMJ chondrocytes delayed TMJ OA progression in the age-associated spontaneous OA model and the abnormal dental occlusion OA model. Immunohistochemical staining revealed that Fgfr1 deficiency decreased the expressions of MMP13 (matrix metalloproteinase-13), ADAMTS5 (a disintegrin and metalloproteinase with thrombospondin motifs 5), and COL10A1 but increased aggrecan expression level in two TMJ OA models. Furthermore, our data show that inactivation of FGFR1 signaling may promote autophagic activity in TMJ. FGFR1 inhibitor decreased the expressions of Mmp13, Adamts5, and Runx2 in IL-1β–stimulated condylar chondrocytes, whereas autophagy inhibitors abrogated the protective effects of the FGFR1 inhibitor. Thus, our study indicates inactivated FGFR1 signaling ameliorates TMJ OA progression partially by promoting autophagic activity. Manipulation of this signaling may be a potential therapeutic approach to modify TMJ OA.
Research on Chinese Tourists Uncivilized Behavior Classification and Attribution

On the basis of Chinese tourists uncivilized behavior full investigation, there has carried on the classification research on Chinese tourists uncivilized behavior and classified the national tourist uncivilized behavior as six categories. The survey found the kinds of behavior major prone population, by analyzing the social relationship between citizens' tourist uncivilized behavior major prone population and tourist uncivilized behavior and carried on the attribution of tourist uncivilized behavior, puts forward measures to tackle the problem of Chinese tourists uncivilized behavior.
Optimal Recognition Method of Human Activities Using Artificial Neural Networks

Abstract The aim of this research is an exhaustive analysis of the various factors that may influence the recognition rate of the human activity using wearable sensors data. We made a total of 1674 simulations on a publically released human activity database by a group of researcher from the University of California at Berkeley. In a previous research, we analyzed the influence of the number of sensors and their placement. In the present research we have examined the influence of the number of sensor nodes, the type of sensor node, preprocessing algorithms, type of classifier and its parameters. The final purpose is to find the optimal setup for best recognition rates with lowest hardware and software costs.
Inequality and Growth Re-Examined

This paper examines the relationship between income inequality and subsequent economic growth. It builds on the model suggested by Alesina and Rodrik (1994) in which inequality works through greater demands for redistribution to slow down growth, and the idea by Ray (1998) that inequality negatively affects savings, work capacity, economic incentives, and access to and efficiency of credit and financial markets. Using an updated dataset and seven model variants, both OLS and 2SLS regressions find a strong negative effect of income inequality on future growth. The effect is considerably stronger for developing countries, but the existence or absence of democracy has no effect on either the relationship between inequality and growth or on the rate of growth itself. There is also no support for Barro’s (2008) claim that inequality impacts growth positively in developed countries.
Clinicopathological Risk Factors for an Invasive Breast Cancer Recurrence after Ductal Carcinoma In Situ—A Nested Case–Control Study

Purpose: Ductal carcinoma in situ (DCIS) is treated to prevent progression to invasive breast cancer. Yet, most lesions will never progress, implying that overtreatment exists. Therefore, we aimed to identify factors distinguishing harmless from potentially hazardous DCIS using a nested case–control study. Experimental Design: We conducted a case–control study nested in a population-based cohort of patients with DCIS treated with breast-conserving surgery (BCS) alone (N = 2,658) between 1989 and 2005. We compared clinical, pathologic, and IHC DCIS characteristics of 200 women who subsequently developed ipsilateral invasive breast cancer (iIBC; cases) and 474 women who did not (controls), in a matched setting. Median follow-up time was 12.0 years (interquartile range, 9.0–15.3). Conditional logistic regression models were used to assess associations of various factors with subsequent iIBC risk after primary DCIS. Results: High COX-2 protein expression showed the strongest association with subsequent iIBC [OR = 2.97; 95% confidence interval (95% CI), 1.72–5.10]. In addition, HER2 overexpression (OR = 1.56; 95% CI, 1.05–2.31) and presence of periductal fibrosis (OR = 1.44; 95% CI, 1.01–2.06) were associated with subsequent iIBC risk. Patients with HER2+/COX-2high DCIS had a 4-fold higher risk of subsequent iIBC (vs. HER2−/COX-2low DCIS), and an estimated 22.8% cumulative risk of developing subsequent iIBC at 15 years. Conclusions: With this unbiased study design and representative group of patients with DCIS treated by BCS alone, COX-2, HER2, and periductal fibrosis were revealed as promising markers predicting progression of DCIS into iIBC. Validation will be done in independent datasets. Ultimately, this will aid individual risk stratification of women with primary DCIS. Clin Cancer Res; 24(15); 3593–601. ©2018 AACR.
A Study of Fingerprint-based Methods for Training Phase in Wi-Fi Indoor Positioning Systems

The use of Indoor Positioning Systems (IPSs) is growing in the last years on different scopes, from faculties to airports, hospitals and big malls amongothers. There is a group contained in these kind of systems to be highlighted, those based on the most common technologies like Wi-Fi because the deployment effort is already done. As there is a new trending study topicon using Fingerprinting collection techniques for positioning,this document exposes a survey of Wi-Fi Indoor Positioning Systems in an offline phase, specifically those that use the Fingerprint collection technique, focusing on the cost of that process in terms of the sampling mode and the interaction required with the user.
Analysis of the Draft Genome of the Red Seaweed Gracilariopsis chorda Provides Insights into Genome Size Evolution in Rhodophyta

Red algae (Rhodophyta) underwent two phases of large-scale genome reduction during their early evolution. The red seaweeds did not attain genome sizes or gene inventories typical of other multicellular eukaryotes. We generated a high-quality 92.1 Mb draft genome assembly from the red seaweed Gracilariopsis chorda, including methylation and small (s)RNA data. We analyzed these and other Archaeplastida genomes to address three questions: 1) What is the role of repeats and transposable elements (TEs) in explaining Rhodophyta genome size variation, 2) what is the history of genome duplication and gene family expansion/reduction in these taxa, and 3) is there evidence for TE suppression in red algae? We find that the number of predicted genes in red algae is relatively small (4,803-13,125 genes), particularly when compared with land plants, with no evidence of polyploidization. Genome size variation is primarily explained by TE expansion with the red seaweeds having the largest genomes. Long terminal repeat elements and DNA repeats are the major contributors to genome size growth. About 8.3% of the G. chorda genome undergoes cytosine methylation among gene bodies, promoters, and TEs, and 71.5% of TEs contain methylated-DNA with 57% of these regions associated with sRNAs. These latter results suggest a role for TE-associated sRNAs in RNA-dependent DNA methylation to facilitate silencing. We postulate that the evolution of genome size in red algae is the result of the combined action of TE spread and the concomitant emergence of its epigenetic suppression, together with other important factors such as changes in population size.
Long-term exposure to NO2 and PM10 and all-cause and cause-specific mortality in a prospective cohort of women

We assessed whether long-term exposure to air pollution is associated with all-cause and cause-specific mortality during a period of declining particulate matter concentrations. Approximately 4800 women aged 55 years from North Rhine-Westphalia, Germany, were followed for up to 18 years. Exposure to air pollution was assessed in two ways: (1) using the distance between the residential address and the nearest major road, as calculated from Geographic Information System data and (2) calculating 1-year average particulate matter concentrations below 10 µm (PM10) and nitrogen dioxide (NO2) levels using data from the nearest air-monitoring station data to the subjects’ residences. Ninety-two per cent of all subjects lived in the same community during the entire follow-up period. Associations between mortality and exposure were assessed using Cox's proportional hazards models, including confounder adjustment. Sixteen per cent of women passed away during the follow-up period. An increase of 7 μg/m3 PM10 (IQR) was associated with an increased HR for all-cause (HR 1.15, 95% CI (1.04 to 1.27)), cardiopulmonary (HR 1.39, 95% CI (1.17 to 1.64)), and lung cancer mortality (HR 1.84, 95% CI (1.23 to 2.74)). An increase of 16 μg/m3 (IQR) NO2 exposure was associated with all-cause (HR 1.18, 95% CI (1.07 to 1.30)) and cardiopulmonary mortality (HR 1.55, 95% CI (1.30 to 1.84)). The association between cardiopulmonary mortality and PM10 was reduced for the extended follow-up period, during which PM10 concentrations (but not NO2 concentrations) were lower. Living close to a major road was associated with an increased relative risk for all-cause, cardiopulmonary and respiratory mortality. These associations were temporally stable. Long-term exposure to ambient PM10 and NO2 was associated with increased mortality rates.
Monitoring the Opinion of the Crowd: Psychological Mechanisms Underlying Public Opinion Perceptions on Social Media

Social media technologies offer several features that allow users to monitor other people’s opinions on public issues. Initial research showed that user-generated content can shape recipients’ perceptions of the majority opinion on societal problems. Still, it remains largely unexplored under which circumstances people gauge other users’ opinions through social media and whether perceived opinion climates affect people’s opinions and communication behavior in these environments. Results of a two-session experiment revealed that people’s fear of isolation sharpens their attention toward user-generated comments on Facebook which, in turn, affect recipients’ public opinion perceptions. The latter influenced subjects’ opinions and their willingness to participate in social media discussions. These findings are discussed in light of the spiral of silence theory and the social projection hypothesis.
Automatic for the people: the automation of communicative labor

ABSTRACT Artificial intelligence is rapidly giving rise to new automated technologies. Among the most important of these innovations is the development of artificially intelligent machines that produce increasingly sophisticated forms of oral and written discourse. As more of our communicative encounters are with artificial agents, our notions of communicative labor, surveillance, and digital rhetoric will have to contend with these extensive shifts. As a step in this direction, the present article evaluates several trends in the automation of oral and written discourse, examining their social and economic impact.