Miracle-dz/UniFAR-FTUs huggingface dataset:
1 Concept Learning Through Parametric Design ; A Learning Situation Design for Parametric Design in Architectural

Over the past few decades, architectural practice and, consequently, the design studio have been increasingly challenged. Indeed, the development of digital tools and parametric design, in particular, has given rise to a new type of architectural knowledge. Among the IJAC publications over the past three years, we highlight the current diversity of vocabulary used to discuss this knowledge and develop why we focus our study on conceptual knowledge. We then report a learning situation through studio design education. This paper finally presents the steps developed to measure this knowledge and hypothesizes on the future work needed in order to have relevant quantitative results. The purpose of this paper is to observe the evolution of students’ understanding when shifting from a traditional teacher‐student relationship to an engaging learning environment, considering the specificities of parametric, and not to suggest a strict method to follow when learning parametric. This could guide teachers to adapt to their own situations.
SAMGEP: A Novel Method for Prediction of Phenotype Event Times Using the Electronic Health Record

Objective: While there exist numerous methods to predict binary phenotypes using electronic health record (EHR) data, few exist for prediction of phenotype event times, or equivalently phenotype state progression. Estimating such quantities could enable more powerful use of EHR data for temporal analyses such as survival and disease progression. We propose Semi-supervised Adaptive Markov Gaussian Embedding Process (SAMGEP), a semi-supervised machine learning algorithm to predict phenotype event times using EHR data. Methods: SAMGEP broadly consists of four steps: (i) assemble time-evolving EHR features predictive of the target phenotype event, (ii) optimize weights for combining raw features and feature embeddings into dense patient-timepoint embeddings, (iii) fit supervised and semi-supervised Markov Gaussian Process models to this embedding progression to predict marginal phenotype probabilities at each timepoint, and (iv) take a weighted average of these supervised and semi-supervised predictions. SAMGEP models latent phenotype states as a binary Markov process, conditional on which patient- timepoint embeddings are assumed to follow a Gaussian Process. Results: SAMGEP achieves significantly improved AUCs and F1 scores relative to common machine learning approaches in both simulations and a real-world task using EHR data to predict multiple sclerosis relapse. It is particularly adept at predicting a patient's longitudinal phenotype course, which can be used to estimate population-level cumulative probability and count process estimators. Reassuringly, it is robust to a variety of generative model parameters. Discussion: SAMGEP's event time predictions can be used to estimate accurate phenotype progression curves for use in downstream temporal analyses, such as a survival study for comparative effectiveness research.
Uterine fluid transcriptome as potential non-invasive biomarker for predicting endometrial receptivity

Background: The synchrony between the embryo and the receptive endometrium is essential for successful implantation. Therefore, a reliable non-invasive ER prediction method is highly demanded. We aimed to establish a method that could be used to predict endometrium receptivity non-invasively and to evaluate its clinical application potential in patients undergoing IVF. Methods: The non-invasive RNA-seq based endometrial receptivity test (nirsERT) was established by sequencing and analyzing the RNA of uterine fluid from 48 IVF patients with normal ER. Subsequently, 22 IVF patients were recruited and analyzed the correlation between the predicted results of nirsERT and pregnancy outcomes. Results: 87 marker genes and 3 hub genes were selected to establish the nirsERT. 10-fold cross-validation resulted in a mean accuracy of 93.0%. A small cohort retrospective observation showed that 77.8% (14/18) of IVF patients predicted with normal WOI had successful intrauterine pregnancies, while none of the 3 patients with displaced WOI had successful pregnancy. Conclusions: nirsERT is potential for a non-invasive, accurate and same cycle testing for ER in reproductive clinic.
Periods of automorphic forms: the case of (GLn+1 × GLn,GLn)

Following Jacquet, Lapid and Rogawski, we define a regularized period of an automorphic form on GLn+1 × GLn along the diagonal subgroup GLn and express it in terms of the Rankin–Selberg integral of Jacquet, Piatetski-Shapiro and Shalika. This extends the theory of Rankin–Selberg integrals to all automorphic forms on GLn+1 ×GLn.
Packaging Information as Fact Versus Opinion: Consequences of the (Information-)Structural Position of Subjective Adjectives

ABSTRACT How do we distinguish fact from opinion? We tested whether people’s ability to detect opinion-based content—as indicated by the use of subjective adjectives (e.g., amazing, frustrating)—depends on the linguistic position of the adjective. Our results show that simply changing the linguistic structure of a sentence influences our perception of the sentence’s subjectivity: The same basic information, packaged differently in linguistic terms, yields significantly different subjectivity ratings. Specifically, our results show that texts with subjective adjectives in syntactic positions associated with new information and “main news” are rated as more opinion-based than texts conveying the same core information with the same adjective presented in a position that presents the information as already-known information or as secondary information. We also show that this information-packaging effect is independent of whether the sentence provides grounds/evidence for the opinion. More generally, our results suggest that linguistic-packaging choices can be used to blur the distinction between fact and opinion or, at least, our ability to perceive opinion-based information as such.
EUROPEAN ACADEMIC RESEARCH, VOL

The concentrations of Copper (Cu) in fish from the Vardar river have been investigated in order to assess safety for consumers and the level of contamination. The selected tissues muscle, liver and skin of two fish species: European Chub (Squalius cephalus) and Common barbel (Barbus barbus) from Vardar river stream, Republic of North Macedonia. Samples are collected in nine different points (Hot Spots) in total distance of 301km and approximate 33 km distance between sampling sites. During the experiment it was investigated the effect of environmental conditions and urban discharges on Copper accumulation in muscles, liver and skin. The metal analyses were performed using Inductively coupled plasma mass spectrometry (ICPMS). The average of metal concentrations (microgram per gram wet weight) in nine hot spots (HS) occurred in the following ranges: HS-1: muscles 1.35-liver 7.13-skin 0.74, HS-2: muscles 1.00-liver 3.31-skin 0.56,HS-3: muscles 0.60-liver 3.47-skin 0.27, HS-4: muscles 0.75-liver 3.92-skin 0.65, HS-5: muscles 0.83-liver 3.57-skin 0.68, HS-6: muscles, 0.57-liver 6.41-skin 1.03, HS-7: muscles 1.10-liver 3.42-skin 1.93, HS8: muscles 1.67-liver 6.96-skin 2.19 and HS-9: muscles 2.05-liver 6.901 Corresponding author: lulzimsh@yahoo.com Lulzim Shaqiri, Jani Mavromati– Results on Copper (Cu) Concentration in Wild Fish Squalius Cephalus & Barbus Barbus Tissues in Vardar River, North Macedonia EUROPEAN ACADEMIC RESEARCH Vol. VII, Issue 6 / September 2019 3294 skin 4.05. The lowest levels of the lead were detected in the skin. The muscles and skin were found to accumulate the highest amounts of Cu. In case of organs, the highest levels were identified as follows: liver > skin > muscles. Further investigation of heavy metals is recommended, including a survey of fish consumption frequency among the local inhabitants.
Integration of Neural Networks, Fuzzy Logic, and Genetic Algorithms

Integration of Neural Networks, Fuzzy Logic, and Genetic Algorithms Chapter 101 Neural networks, fuzzy logic, and genetic algorithms are soft computing methods which have been inspired by biological computational processes and nature's problem sólving strategies. Neural networks (NNs) are highly simplified models of the human nervous system which mimic our ability to adapt to circumstances and learn from past experience. Part I of the book discusses three NN systems each representing the three major classes of NN architectures, namely single layer feedforward, multilayer feedforward, and recurrent network architectures. The NN systems presented are the backpropagation network, associative memories, and adaptive resonance theory. Backpropagation network is a multilayer feedforward network architecture with gradient descent learning. Associative memories are single layer feedforward or recurrent network architectures adopting Hebbian learning. ART networks are recurrent network architectures with a kind of competitive learning termed adaptive resonance theory. Fuzzy logic systems address the imprecision or vagueness in input output descriptions of systems using fuzzy sets. Fuzzy sets have no crisp boundaries and provide a gradual transition between membership and non-membership of elements in a set. Part I of the book discusses the fundamental concepts of fuzzy logic and its applications. Genetic algorithms (GAs) inspired by the process of biological evolution, are adaptive search and optimization algorithms. Part Il of the book discusses the basic concepts, namely the genetic inheritance operators and applications of GA. Each of the technologies, in their own right and merit, have provided efficient solutions to a wide range of problems belonging to different domains. At the same time, as mentioned in Chapter 1, various attempts have been successfully made to synergize the three different technologies in whole or in part, to solve problems for which these technologies could not find solutions individually. The objective of the synergy or hybridization has been to overcome the weaknesses in one technology during its application, with the strengths of the other by appropriately integrating them. More often, the complexity surrounding a problem has called for a Judicious combination of the technologies, when a technology individually applied has failed to obtain an efficient solution. However, bybridization of technologies can have its pitfalls and therefore needs to be done with care. If a technology can solve a problem then a hybrid technology ought to be used only if its application results in a better solution or provides a beter method to arrive at the solution or at worst, finds an alternative method to arrive at the solution. Hybridization should only be pertormed for the purpose of investigating better methods of problem solving.
Time‐resolved Fluorescence Measurements of Aquatic Natural Organic Matter (NOM)

The fluorescence decay of aquatic natural organic matter (NOM) samples was investigated using the time-correlated single photon counting technique (TCSPC). Two different approaches for the data analysis are presented: the discrete component approach (DCA) and the exponential series method (ESM). The parameter set obtained in the DCA is discussed in terms of characterization for NOM of different origins. However, the obtained parameter set can only be interpreted as operationally defined. Using the ESM for a fluorescence decay time distribution analysis no a priori assumption about the number of fluorescing components was introduced into the data analysis. The interpretation of fluorescence decay time data for samples before and after ozonation is in good agreement with results of other analytical methods.
Clara Alfonso‐Carrillo 1, Cristina Benavides‐Reyes 2, Jon de los Mozos 1, Nazaret Dominguez‐Gasca 2, Estefanía Sanchez‐Rodríguez 2, Ana Isabel Garcia‐Ruiz 1,* and Alejandro B. Rodriguez‐Navarro 2,*

(1) Background: Nowadays the industry aims to improve lay persistency for extended cycles (100 weeks or longer) to make egg production more sustainable. However, intensive egg pro‐ duction challenges hen health, inducing severe osteoporosis and the incidence of bone fractures. In this study, the relationship between bone quality and egg production, and/or eggshell quality, was evaluated at the end of an extended laying cycle of 100 weeks, comparing groups of hens with dif‐ ferent production and eggshell quality parameters; (2) Methods: Quality parameters of egg (as weight, egg white height), eggshell (as thickness, weight, breaking strength, elasticity and micro‐ structure) and tibiae bone (weight, diameter, cortical thickness, ash weight, breaking strength, me‐ dullary bone) were determined; (3) Results: Hens from groups with a high egg production and good eggshell quality have poorer bone quality (lower ash weight and lesser amount of medullary bone). However, Pearson’s correlation analysis shows no clear relationship between bone and egg/eggshell parameters. (4) Conclusions: Bone and egg production/eggshell quality are independent and can be improved separately. Medullary bone has an important contribution to bone mechanical properties, being important to accumulate enough bone medullary bone early in life to maintain skeletal integ‐ rity and eggshell quality in old hens.
Construction of a Risk Prediction Model for Subsequent Bloodstream Infection in Intestinal Carriers of Carbapenem-Resistant Enterobacteriaceae: A Retrospective Study in Hematology Department and Intensive Care Unit

Background To establish a risk prediction model for carbapenem-resistant Enterobacteriaceae (CRE) bloodstream infection (BSI) in intestinal carriers. Methods CRE screenings were performed every two weeks in hematology department and intensive care unit (ICU). Patients with positive CRE rectal swab screening were identified using electronic medical records from 15 May 2018 to 31 December 2019. Intestinal carriers who developed CRE BSI were compared with those who did not develop CRE infection. A 1:1 matched case-control study was conducted. The control group was selected by stratified random sampling based on the department to ensure that all the departments were represented. Univariate logistic analysis, multivariate logistic analysis and stepwise regression analysis were carried on a variety of patient factors and microbial factors. Results A total of 42 cases were included. Multivariate analysis showed that gastrointestinal injury (OR 86.819, 95% CI 2.584–2916.592, P=0.013), tigecycline exposure (OR 14.991, 95% CI 1.816–123.737, P=0.012) and carbapenem resistance score (OR 11.236, 95% CI 1.811–69.700, P=0.009) were independent risk factors for CRE BSI in intestinal carriers (P<0.050). They were included in the Logistic regression model to predict BSI. According to receiver operating characteristic (ROC) curve analysis, the cut-off value of the model was 0.722, and the sensitivity, specificity and area under the curve (AUC) were 90.5%, 85.7% and 0.921, respectively. Conclusion The risk prediction model based on gastrointestinal injury, tigecycline exposure and carbapenem resistance score of colonizing strain can effectively predict CRE BSI in patients with CRE colonization. Early CRE screening and detection for inpatients in key departments may promote early warning and reduce the risk of nosocomial infection of CRE.
Hepatic Knockdown of Endothelin Type A Receptor (ETAR) Ameliorates Hepatic Insulin Resistance and Hyperglycemia Through Suppressing p66Shc-Mediated Mitochondrial Fragmentation in High-Fat Diet-Fed Mice

Background Emerging evidence from animal studies and clinical trials indicates that systemic inhibition of endothelin1 (ET1) signaling by endothelin receptor antagonists improves pathological features of diabetes and its complications. It is indicated that endothelin type A receptor (ETAR) plays a major role in ET1-mediated pathophysiological actions including diabetic pathology. However, the effects as well as the mechanistic targets of hepatic ET1/ETAR signaling inhibition on the pathology of metabolic diseases remain unclear. This study aimed to investigate the beneficial effects as well as the underlying mechanisms of hepatic ETAR knockdown on metabolism abnormalities in high-fat diet (HFD)-fed mice. Methods Mice were fed a HFD to induce insulin resistance and metabolism abnormalities. L02 cells were treated with ET1 to assess the action of ET1/ETAR signaling in vitro. Liver-selective knockdown of ETAR was achieved by tail vein injection of adeno-associated virus 8 (AAV8). Systemic and peripheral metabolism abnormalities were determined in vivo and in vitro. Mitochondrial fragmentation was observed by transmission electron microscope (TEM) and mitoTracker red staining. Results Here we provided in vivo and in vitro evidence to demonstrate that liver-selective knockdown of ETAR effectively ameliorated hepatic insulin resistance and hyperglycemia in HFD-fed mice. Mechanistically, hepatic ETAR knockdown alleviated mitochondrial fragmentation and dysfunction via inactivating 66-kDa Src homology 2 domain-containing protein (p66Shc) to recover mitochondrial dynamics, which was mediated by inhibiting protein kinase Cδ (PKCδ), in the livers of HFD-fed mice. Ultimately, hepatic ETAR knockdown attenuated mitochondria-derived oxidative stress and related liver injuries in HFD-fed mice. These ETAR knockdown-mediated actions were confirmed in ET1-treated L02 cells. Conclusion This study defined an ameliorative role of hepatic ETAR knockdown in HFD-induced metabolism abnormalities by alleviating p66Shc-mediated mitochondrial fragmentation and consequent oxidative stress-related disorders and indicated that hepatic ETAR knockdown may be a promising therapeutic strategy for metabolic diseases.
Evaluation of Beneficial and Adverse Effects of a Diet Supplemented with Schisandrae Fructus Seed Ethanol Extract on Lipid and Glucose Metabolism in Normal and Hypercholesterolemic/Hyperglycemic Mice

Schisandrae Fructus (SF), the fruit of Schisandra chinensis (Turcz.) Baillon, has been used for the treatment of liver injury and metabolism-related disorders in China. The objective of this study was to investigate the effects of supplementation with ethanol extract of SF seed (EtSF-S) on serum/hepatic lipid and glucose levels as well as fecal total cholesterol (TC) contents in mice fed a normal diet (ND) or high-fat/fructose diet (HFFD) containing 15% lard oil and 15% fructose. Female ICR mice (18–20 g in body weight) were fed with ND or HFFD for 3 months, and then EtSF-S was added to both chow diets at increasing concentrations of 1, 5, and 10% (w/w). Thirty days later, serum and hepatic lipids, including TC, triglyceride (TG), high-density lipoprotein (HDL), low-density lipoprotein (LDL), and glucose, were measured. Dietary supplementation with EtSF-S reduced hepatic TC (36 and 18%) and TG levels (38 and 28%) and increased serum HDL/LDL ratio (16 and 26%) in both ND- and HFFD-fed mice, respectively. Moreover, supplementation with EtSF-S elevated serum HDL (31%) in HFFD-fed mice and reduced serum LDL (27%) in ND-fed mice. EtSF-S treatment reduced fat mass (40%) in ND-fed mice and increased fecal TC contents (33%) in HFFD-fed mice. EtSF-S supplementation decreased hepatic glucose contents (29%) in both ND- and HFFD-fed mice. However, diet supplemented with EtSF-S elevated serum TG levels (up to 123%) and hepatic size (28%), but more importantly, suppressed the body weight gain (approximately 130%) in mice fed with HFFD. These findings suggested that dietary supplementation with EtSF-S as natural herbal function food may be a useful strategy for the treatment of patients with fatty liver disease or overweight without a high intake of sugar and fat.
Effects of Zn Diffusion from (Zn,Mg)O Buffer to CIGS Film on the Performance of Cd-Free Cu(In,Ga)Se2 Solar Cells

A diffusion of Zn into the CIGS film and its effects on the device performance were investigated when the atomic layer deposited (Zn,Mg)O film was used as a buffer layer of CIGS solar cells. SIMS and ICP mass analysis showed that the Zn concentration in the CIGS film was increased with increasing ALD process time. The hole concentration in the CIGS film was decreased by Zn incorporation. It was suggested that open circuit voltage degradation in CIGS cell with Zn incorporation was mainly due to enhanced recombination by Zn defects instead of Fermi-level change. The results suggest that the ALD process should be as short as possible to avoid Zn diffusion. On the other hand, a small amount of Zn incorporation on the surface of the CIGS film by post rapid thermal annealing of a (Zn,Mg)O/CIGS cell at 200 ◦ C showed an increased cell performance. However, excess Zn incorporation on the surface of the CIGS film caused degradation of cell performance due to the generation of a new defect. The generation of a deep-level defect and the change of the minority carrier lifetime were characterized by low-temperature PL and time-resolved PL, respectively. The cell performance was correlated with these results.
Breast cancer and occupational exposures: an integrative review of the literature

Occupational factors can lead to breast cancer, though the relationship between these variables is not well established. The objective of this study was to search the relevant literature for information on the association between breast cancer and exposure to occupational risk factors. For that purpose, electronic databases were searched using the following keywords: breast cancer and occupational exposures. A total of 40 articles published in the 10-year period from 2009 to 2019 were included in this review. Workers exposed to metals such as cadmium, chemical products, radiation and night work were more susceptible to breast cancer. The findings showed significant evidence to support an association between breast cancer and some chemical products, ionizing radiation and night work. However, most studies have difficulty establishing a causal relationship between these variables, pointing to the need for further investigation of these issues.