Miracle-dz/UniFAR-FTUs huggingface dataset:
On the scale-free nature of RNA secondary structure networks

A network is scale-free if its connectivity density function is proportional to a power-law distribution. Scale-free networks may provide an explanation for the robustness observed in certain physical and biological phenomena, since the presence of a few highly connected hub nodes and a large number of small- degree nodes may provide alternate paths between any two nodes on average -- such robustness has been suggested in studies of metabolic networks, gene interaction networks and protein folding. A theoretical justification for why biological networks are often found to be scale-free may lie in the well-known fact that expanding networks in which new nodes are preferentially attached to highly connected nodes tend to be scale-free. In this paper, we provide the first efficient algorithm to compute the connectivity density function for the ensemble of all secondary structures of a user-specified length, and show both by computational and theoretical arguments that preferential attachment holds when expanding the network from length n to length n + 1 structures. Since existent power-law fitting software, such as powerlaw, cannot be used to determine a power-law fit for our exponentially large RNA connectivity data, we also implement efficient code to compute the maximum likelihood estimate for the power-law scaling factor and associated Kolmogorov-Smirnov p-value. Statistical goodness-of-fit tests indicate that one must reject the hypothesis that RNA connectivity data follows a power-law distribution. Nevertheless, the power-law fit is visually a good approximation for the tail of connectivity data, and provides a rationale for investigation of preferential attachment in the context of macromolecular folding.
Analysis on Metabolic Functions of Stored Rice Microbial Communities by BIOLOG ECO Microplates

Microbial contamination has been a pervasive issue during the rice storage and triggers extensive researches. The metabolism of microorganisms was proved as an indicator to mirror the degree of microbial contamination. It is necessary to develop a scientific method to analyze the metabolism of rice microbial communities, thereby monitoring the microbial contamination. In this study, the metabolism of rice microbial communities in different storing-year were investigated by BIOLOG ECO microplates. The three rice samples were respectively stored for 1–3 years. The related indicators of BIOLOG ECO microplates were determined, including average well-color development (AWCD) of carbon sources and three metabolic functional diversity indices. The results showed that there were significant differences in the AWCD of all carbon sources among the three rice microbial communities (p < 0.05), and the functional diversity indices except Simpson index showed significant differences (p < 0.05). Additionally, the three rice microbial communities differed significantly in the metabolic utilization of carboxylic acids and miscellaneous (p < 0.05), and there were, however, no significant differences in the other four types of carbon sources. Furthermore, principal component analysis revealed that the microbial communities of stored rice had obviously different metabolic functions in different storage period. Therefore, the study indicated that the BIOLOG ECO microplate was applicable to evaluate the metabolic functions of rice microbial communities, and carboxylic acids and miscellaneous were two crucial parameters of carbon sources to identify the metabolic differences of microbial communities, a case in which it reflected the conditions of rice microbial contamination.
Higher Concentrations of BCAAs and 3-HIB Are Associated with Insulin Resistance in the Transition from Gestational Diabetes to Type 2 Diabetes

Aim Determine the metabolic profile and identify risk factors of women transitioning from gestational diabetes mellitus (GDM) to type 2 diabetes mellitus (T2DM). Methods 237 women diagnosed with GDM underwent an oral glucose tolerance test (OGTT), anthropometrics assessment, and completed lifestyle questionnaires six years after pregnancy. Blood was analysed for clinical variables (e.g., insulin, glucose, HbA1c, adiponectin, leptin, and lipid levels) and NMR metabolomics. Based on the OGTT, women were divided into three groups: normal glucose tolerance (NGT), impaired glucose tolerance (IGT), and T2DM. Results Six years after GDM, 19% of subjects had T2DM and 19% IGT. After BMI adjustment, the IGT group had lower HDL, higher leptin, and higher free fatty acid (FFA) levels, and the T2DM group higher triglyceride, FFA, and C-reactive protein levels than the NGT group. IGT and T2DM groups reported lower physical activity. NMR measurements revealed that levels of branched-chain amino acids (BCAAs) and the valine metabolite 3-hydroxyisobyturate were higher in T2DM and IGT groups and correlated with measures of insulin resistance and lipid metabolism. Conclusion In addition to well-known clinical risk factors, BCAAs and 3-hydroxyisobyturate are potential markers to be evaluated as predictors of metabolic risk after pregnancy complicated by GDM.
Improved Techniques for Learning to Dehaze and Beyond: A Collective Study

Here we explore two related but important tasks based on the recently released REalistic Single Image DEhazing (RESIDE) benchmark dataset: (i) single image dehazing as a low-level image restoration problem; and (ii) high-level visual understanding (e.g., object detection) of hazy images. For the first task, we investigated a variety of loss functions and show that perception-driven loss significantly improves dehazing performance. In the second task, we provide multiple solutions including using advanced modules in the dehazing-detection cascade and domain-adaptive object detectors. In both tasks, our proposed solutions significantly improve performance. GitHub repository URL is: this https URL
Photolytic degradation of chloramphenicol in different aqueous matrices using artificial and solar radiation: reaction kinetics and initial transformation products

The photodegradation of cloramphenicol (CAP) in ultrapure water (UW), untreated surface water (USW), and treated effluent from sewage treatment plant (TESTP) in laboratory scale and pilot scale, was evaluated using solar and artificial radiation. The results show, in all cases, that the CAP degradation occurs according to pseudo-first order kinetics, with the apparent degradation rate constants (kapp) following the order UW ≡ USW > TESTP. The kapp and half-life were strongly influenced by the radiation source. Mono- and di-hydroxyl transformation products were identified in UW after 40 min of solar irradiation, while the acute toxicity to Artemia salina increased from 35% to 100%, respectively after 180 and 1440 min of artificial and solar irradiation (94 and 132 kJ L-1), when 99.2 and 97.7% of CAP degradation occurred. The transformation products did not present antimicrobial activity.
Next-generation sequencing-based detection of EGFR, KRAS, BRAF, NRAS, PIK3CA, Her-2 and TP53 mutations in patients with non-small cell lung cancer

In recent years, the incidence of non-small cell lung cancer (NSCLC) has become the highest lethal rate of cancer worldwide. Molecular assays of EGFR, KRAS, BRAF, NRAS, PIK3CA and Her-2 are widely used to guide individualized treatment in NSCLC patients. Somatic mutations in 112 NSCLC patients, including 7 oncogenic driver genes, were detected by Iontorrent personal genome machine (PGM). Sanger sequencing was used to test and verify the results of PGM. Apart from uncommon mutations of EGFR, 101 NSCLC specimens were tested by droplet digital PCR (ddPCR). According to NGS results, mutations were detected in EGFR (58/112, 51.79% of tumors), KRAS (10/112, 8.93%), BRAF (2/112, 1.79%), NRAS (2/112, 1.79%), Her-2 (2/112, 1.79%), PIK3CA (6/112, 5.36%) and TP53 (31/112, 27.69%). There were 27 samples without any somatic mutations in all genes while 24 samples harboured mutations in two or more genes. A total of 61 samples had one or more mutations in a single gene. All alterations of 7 genes were presented and the overall detection rate of NGS and Sanger sequencing was determined to be 51.79% (58/112) and 37.50% (42/112), respectively (χ2=5.88, P=0.015). Compared with Sanger sequencing, the total sensitivity and specificity of NGS assays was 95.24% (40/42) and 77.14% (54/70), respectively. The overall detection rate of NGS and ddPCR was 45.54% (46/101) and 47.52% (48/101), respectively (χ2=0.000598, P=0.98). Compared with ddPCR, the overall sensitivity and specificity of NGS assays was 95.83% (46/48) and 98.11% (52/53), respectively. The findings indicated that the positive mutation rate of EGFR tested by NGS was significantly lower than that by Sanger sequencing, but the difference between ddPCR and NGS was not statistically significant. The high degree of agreement of reportable variants is proposed in both NGS and ddPCR analysis, suggesting the performance of NGS assays in routine clinical detection may be useful in determining the treatment decisions in NSCLC patients.
Supporting End-User Understanding of Classification Errors

Classifiers are applied in many domains where classification errors have significant implications. However, end-users may not always understand the errors and their impact, as error visualizations are typically designed for experts and for improving classifiers. We discuss a visualization design that addresses the specific needs of classifiers' end-users. We evaluate this design with users from three levels of expertise, and compare it with ROC curves and confusion matrices. We identify key difficulties with understanding the classification errors, and how visualization designs addressed or aggravated them. The main issues concerned confusions of the actual and predicted classes (e.g., confusion of False Positives and False Negatives). The machine learning terminology, complexity of ROC curves, and symmetry of confusion matrices aggravated the confusions. The end-user-oriented visualization reduced the difficulties by using several visual features to clarify the actual and predicted classes, and more tangible metrics and representation. Our results contribute to supporting end-users' understanding of classification errors, and informed decisions when choosing or tuning classifiers.
The role of experience on techno-entrepreneurs’ decision making biases

Article history: Received March 26, 2012 Accepted 15 June 2012 Available online June 18 2012 Entrepreneurs are the driving force behind the prospect and growth of the societies. Sound and wise decisions pave the way for them to carry out these highly important functions. Entrepreneurs are to discover and exploit opportunities. Therefore, they must gather sufficient and pertinent information. Entrepreneurs, like most human beings face complex and ambiguous decision-making situations, not to mention their lack of time and source to gather and process the data. Under these circumstances, entrepreneurs are prone making biases decisions. There are many reasons identified for this entrepreneurial decision making biases, such as the high cost of rational decision making, limitations in information processing, differences in their styles and procedures, or information overload, environmental complexity, environmental uncertainty. These biases are neither totally harmful nor completely useful and have to be seen as natural human characteristics. What makes entrepreneurial decision-making biases important is their effects on the decisions and thus the outcome of the enterprises. Entrepreneurial decision-making biases, deliberate or unintentional can seal the fate of the enterprises, therefore studying them meticulously is crucial. Literature has shown that experience could be an effective factor in decision-making biases. In this paper, we try to find out the impact of experience in Iranian high tech entrepreneurs’ major decision-making biases by a qualitative approach. Finally, it was concluded that experience is influential in shaping overconfidence bias. © 2012 Growing Science Ltd. All rights reserved.
Integrating Social Values into Software Design Patterns

Software Design Patterns (SDPs) are core solutions to the recurring problems in software. However, adopting SDPs without taking into account their value implications may result in breach of social values and ultimately lead to user dissatisfaction, lack of adoption, and financial loss. An example is the airline system that overcharged people who were trying to escape from the Hurricane Irma. though not intentional, overlooking social values in the design of the airline system resulted in a significant dissatisfaction and loss of trust. To mitigate such value breaches in software design we propose explicitly taking into account social values in SDPs. To achieve this, we outline a collaborative framework that allows for (i) specifying the value implications of the SDPs, (ii) developing or extending SDPs for integrating social values, (iii) providing guidance on the value-conscious adoption of design patterns, (iv) collecting and analyzing insights from collaborators, (v) maintaining an up-to-date library of the valufied design patterns, and (vi) incorporating lessons learned from the real-world adoption of valuefied design patterns into the proposed framework for its continuous improvement in integrating social values into software design.
The Parsonsburg Sand in the central Delmarva Peninsula, Maryland and Delaware

———————Introduction ——————Acknowledgments Lithology————————Sand composition Internal structure ——Weathering——————River dunes ——————Upland dunes—————• Age and origin————References cited ———• Cl 1 3 3 3 5 6 9 10 13 14
Sexual violence, institutional betrayal, and psychological outcomes for LGB college students.

Individuals who identify as lesbian, gay, or bisexual (LGB) are at an elevated risk of experiencing potentially traumatic events compared with the general population, particularly sexual abuse and assault (Brown & Pantalone, 2011; Rothman, Exner, & Baughman, 2011). Considering this trauma, in addition to the stress of discrimination (e.g., Marshal et al., 2015), it is perhaps unsurprising that LGB people typically report more mental health problems than heterosexual people (Mayer et al., 2008). Research further shows that institutional betrayal, or institutional failure to prevent or respond appropriately to sexual assault, may exacerbate negative outcomes for assault survivors (Smith & Freyd, 2013). The aim of this study was to determine whether LGB individuals experience higher rates of institutional betrayal compared with heterosexuals and whether this added harm may be disproportionate to individuals who are sexual minorities. In a self-report survey study of 299 undergraduates (90.3% heterosexual, 9.7% LGB-identified), LGB participants reported significantly higher rates of sexual harassment and sexual assault than heterosexual participants. LGB respondents also reported significantly higher rates of institutional betrayal, even when controlling for incidences of sexual harassment and assault. Finally, LGB participants exhibited significantly more negative psychological outcomes, including posttraumatic stress symptoms, depression, and lower collective self-esteem, related to their sexual identities. These results support prior research suggesting that LGB individuals experience more traumas and show the importance of sexual identity as a risk factor for institutional betrayal.
Secure Transmission to the Strong User with Optimal Power Allocation in NOMA

With non-orthogonal multiple access(NOMA), we tackle the maximization of the secrecy rate for the strong user subject to a maximum allowable secrecy outage probability, while guaranteeing a constraint on the transmission rate to the weak user. For the first time, the dependence between the eavesdropper's ability to conduct successive interference cancellation and her channel quality is considered. We determine the optimal power allocation and the redundancy rate, based on which the cost of security in terms of the reduction in the strong user's secrecy rate is examined and the benefits of NOMA for secure transmissions are explicitly revealed.
On the Timing Synchronization under 1-Bit Quantization and Oversampling

As the demand for communication systems with high data rates is increasing, large bandwidths, and thus high sampling rates, are required. As a consequence, the energy consumption of conventional high resolution analog-to-digital converters increases drastically. On the contrary, high resolution in time domain is less difficult to achieve than high resolution in amplitude domain. This motivates the design of communication systems with 1-bit quantization and oversampling. It has been shown that utilizing run-length limited sequences and faster-than-Nyquist signaling is beneficial in terms of achievable rate. However, it is an open question how receiver synchronization can be performed in such systems. In this work we assume perfect frame, frequency and phase synchronization and investigate the effect of a fixed but unknown time shift. Due to 1-bit quantization, standard timing estimation and interpolation cannot be applied. We show that oversampling w.r. t. the signaling rate compensates for the error introduced by the time shift. If the oversampling factor is an integer value, estimating the time shift becomes obsolete if the oversampling rate is sufficiently high.
Better and faster catheter position optimization in HDR brachytherapy for prostate cancer using multi-objective real-valued GOMEA

The recently-introduced Gene-pool Optimal Mixing Evolutionary Algorithm (GOMEA) family has been shown to be capable of excellent performance on academic benchmark problems, outperforming other state-of-the-art EAs, especially when efficient partial evaluations are possible. This holds true also for the latest extension, the Multi-Objective Real-Valued GOMEA (MO-RV-GOMEA). In this paper, we apply MO-RV-GOMEA to the real-world multi-objective optimization problem of catheter placement in High-Dose-Rate (HDR) brachytherapy for prostate cancer, a problem that is non-trivial to solve and has high real-world importance and relevance. Due to the underlying geometric structure of the real-valued variables, partial evaluations can be performed, allowing MO-RV-GOMEA to exploit this structure. The performance of MO-RV-GOMEA is tested on three real-world patient cases and compared to a recent state-of-the-art mixed-integer EA that is aimed at a restricted version of the problem. We find that with MO-RV-GOMEA better solutions can be found much faster, making our proposed approach much more realistic to be used in clinical practice, and enabling new insights into both catheter placement for prostate brachytherapy and on objectives used for automated treatment planning. First results indicate that richer problem models are needed to better match real-world clinical preferences.
Virtual Orientation Overrides Physical Orientation to Define a Reference Frame in Spatial Updating

Previous studies showed that people could use either an egocentric or allocentric reference frame in spatial updating with body-based cues (i.e., physical body movements), but the adopted reference frame was anchored by the physical egocentric front when body-based cues were constrained. A recent study (He et al., 2018) showed that even without body-based cues, the orientation participants initially faced in the virtual environment (VE; initial heading) could be used to establish a reference frame, suggesting that the physical egocentric front could be overridden by a virtual orientation. In the current project, we aimed to: (a) replicate He et al.’s (2018) finding; (b) examine when the reference frame defined by the virtual initial heading was established; and (c) investigate the cognitive processes in establishing the initial heading as a reference frame. In four experiments, we were able to replicate the previous findings and found that the reference frame defined by the initial heading was established during spatial updating. More importantly, the reference frame defined by the initial heading was egocentric and participants did not need to know the orientation of their initial heading at the beginning of spatial updating to be able to use it. We discuss the cognitive processes of reference frame selection in spatial updating when body-based cues are absent.
Effects of Dietary Soy Protein Concentrate on Growth, Digestive Enzymes Activities and Target of Rapamycin Signaling Pathway Regulation in Juvenile Soft-Shelled Turtle, Pelodiscus sinensis

Soft-shelled turtle, Pelodiscus sinensis is important aquatic species in China, and searching for alternatives protein resources to fish meal (FM)-based feeds in feed has become urgent and important for its sustainability development. The present study was conducted to assess the effects of dietary soy protein concentrate (SPC) on growth, digestive enzymes and target of rapamycin (TOR) signaling pathway of juvenile P. sinensis (4.56 ± 0.09 g). SPC was applied to replace FM protein at 0%, 15%, 30% and 60% (designated as T0, T15, T30 and T60, respectively), and each diet was fed to triplicate groups. The results showed that there was no significant difference in growth performance and feed utilization except of the turtles fed with T60 diet, of which showed poorer daily weight gain and feed conversion rate. The pepsin/trypsin and Na+-K+ ATP-ase activities decreased dramatically when SPC level increased, and lipase activities in liver and intestinal tract also showed decline tendency. However, amylase activities were unaffected. No significant differences were observed in TOR, S6K1 and 4E-BP1 genes mRNA expression level of TOR signaling pathway among the treatments. However, the relative phosphorylated level of these proteins decreased significantly when SPC level increased. The present study indicated that high SPC substitution level would suppress digestive enzymes and TOR signaling pathway proteins phosphorylated level and eventually result in growth reduction of P. sinensis.
Fairness Definitions Explained

Algorithm fairness has started to attract the attention of researchers in AI, Software Engineering and Law communities, with more than twenty different notions of fairness proposed in the last few years. Yet, there is no clear agreement on which definition to apply in each situation. Moreover, the detailed differences between multiple definitions are difficult to grasp. To address this issue, this paper collects the most prominent definitions of fairness for the algorithmic classification problem, explains the rationale behind these definitions, and demonstrates each of them on a single unifying case-study. Our analysis intuitively explains why the same case can be considered fair according to some definitions and unfair according to others.
Coping strategies used by the elderly regarding aging and death: an integrative review

Objective: to identify and synthesize studies that approach the coping strategies used by the elderly to deal with aging and death. Method: an integrative review was performed in seven databases with the following descriptors: psychological adaptation, the elderly, death and aging. Results: 73 articles were identified. After applying the inclusion and exclusion criteria, six articles that identified multiple losses experienced by the elderly and included coping strategies were selected and analyzed. The main losses were: loss of health; physical capacity and functionality; loss in quality of emotional relationships; Palavras-chave: Adaptação Psicológica. Idoso. Morte. Envelhecimento. http://dx.doi. org/10.1590/1981-22562017020.170083