Miracle-dz/UniFAR-FTUs huggingface dataset:
Software quality attributes and trade-offs

Preface This compendium was produced in a Ph.D. course on " Quality attributes and trade-offs ". The 11 Ph.D. students that followed the course all worked in the same research project: BESQ (Blekinge – Engineering Software Qualities), see http://www.bth. se/besq. The goal of the course is to increase the competence in key areas related to engineering of software qualities and by this establish a common platform and understanding. The latter should in the long run make it easier to perform future cooperation and joint projects. We will also discuss techniques and criteria for reviewing scientific papers and book chapters. The course is divided into a number of sections, where one (or a group of) student(s) is responsible for each section. Each section should be documented in written form. This compendium is organized in 8 chapters: 1. Software Quality Models and Philosophies, by D. Milicic This chapter gives an overview to different quality models. It also discusses what quality is by presenting a number of high-profile quality gurus together with their thoughts on quality (which in some cases actually results in a more or less formal quality model). 2. The software industry constantly seeks ways to optimize product development after what is expected from their customers. One effect of this is an increased need to become better at predicting and measuring management related attributes that affect company success. This chapter describes a set of such management related attributes and their relations and trade-offs. 4. This chapter focuses on developer-oriented quality attributes, such as: Maintainability, Reusability, Flexibility and Demonstrability. A list of developer-oriented quality attributes is synthesized from a number of common quality models: McCall's quality model, Boehm's quality model and ISO 9126-1. 5. In the three previous chapters, various quality attributes are discussed from different perspectives. This chapter aims to merge these three different perspectives and discuss the relations between them. 6. Dealing with decisions concerning limited resources typically involves a trade-off of some sort. This chapter discusses the concept of trade-off techniques and practices as a basis for decision support. In this context a trade-off can become a necessity if there are limited resources and two (or more) entities require the consumption of the same resource, or if two or more entities are in conflict. 7. Trade-off examples inside software engineering and computer science, by F. Mårtensson During software development, tradeoffs are made on a daily basis by the people participating …
Primary Screening of Antioxidant Activity, Total Polyphenol Content, Carotenoid Content, and Nutritional Composition of 13 Edible Flowers from Japan

Thirteen edible flowers, which are used as food ingredients in Japan, were evaluated as possible sources of antioxidants and biological compounds. The nutritional composition, total polyphenol content (TPC), carotenoid content, and antioxidant activity of the edible flowers were determined based on the oxygen radical absorbance capacity (ORAC). Water was the main constituent of edible flowers, and carbohydrates were the primary macronutrients. The TPC of the edible flowers varied from 1.47 to 13.08 mg gallic acid equivalent/g fresh weight (FW). Carotenoids, including β-carotene and β-cryptoxanthin, were detected mainly in the edible flowers with petal colors ranging from yellow to orange, but especially in primula and cosmos yellow flowers, which have yellow petals. The ORAC value of the hydrophilic extract (HORAC) of edible flowers was higher than the ORAC value of the lipophilic extract (LORAC). The total antioxidant capacity (TAC) ranged from 33.03 to 320.36 μM Trolox equivalent/g FW. The highest TPC and TAC were observed in cosmos yellow flowers. On the basis of Pearson’s correlation coefficient, the HORAC value and the TPC of the analyzed edible flowers were highly correlated (r=0.736). This preliminary study indicates that edible flowers are a potential source of antioxidants, and the addition of edible flowers to the human diet may be associated with health benefits.
Markov Logic Networks for Knowledge Base Completion: A Theoretical Analysis Under the MCAR Assumption

We study the following question. We are given a knowledge base in which some facts are missing. We learn the weights of a Markov logic network using maximum likelihood estimation on this knowledge base and then use the learned Markov logic network to predict the missing facts. Assuming that the facts are missing independently and with the same probability, can we say that this approach is consistent in some precise sense? This is a non-trivial question because we are learning from only one training example. In this paper we show that the answer to this question is positive.
HPLC-DAD Phenolic Profiling and In Vitro Antioxidant Activities of Three Prominent Nigerian Spices

Spices and herbs have antioxidant, anti-inflammatory, and anti-microbial properties, amongst others. These characteristics are attributable to their composition, such as high polyphenol and flavonoid contents that are responsible for their antioxidative properties. Methanolic extracts of Ocimum basilicum (OB), Xylopia aethiopica (XA), and Piper guineensis (PG) were evaluated to profile their phenolic compounds and in vitro antioxidant properties. High performance liquid chromatography with diode-array detection phenolic compounds profiling revealed that quercetin, quercitrin, and isoquercitrin are the most prevalent phenolic compound in OB, XA, and PG, respectively. All the extracts possessed good antioxidant activity. XA showed the highest total phenolic content of 29.50 mg gallic acid equivalents/g, a total flavonoid content of 21.17 mg quercetin equivalents/g, 2,2-diphenyl-1-picrylhydrazyl and 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulphonic acid) radical scavenging abilities of 29% and 88.23%, respectively, and a nitric oxide scavenging activity of 44.13 mg/g. Thus, the XA methanolic extract demonstrated a high content of phenolic compounds and significant antioxidative properties, with prospective potency to prevent oxidative damage and promote better cardiovascular health.
The Impact of Math Innovations in Elementary Mathematics Classrooms in Georgia Vision Project Districts

The purpose of this dissertation was to study how teachers and school leaders perceived a specific set of classroom math innovations, and how those innovations impacted instruction in relation to the Georgia Vision Project (GVP) standards and recommendations. This was a qualitative study conducted in two GVP districts. The participants in the study were five elementary teachers, two school administrators, and two district leaders. The participants were interviewed to gain an understanding of their perceptions of recent math innovations. The innovations included (a) math instruction using manipulatives (such as counting objects and puzzles) that utilize the Concrete Representational Abstract (CRA) model, which engages students to conceive from the concrete to the abstract; (b) differentiation through flexible student grouping; (c) information about how different subgroups of students learn mathematics; and (d) math professional learning. Previous research had focused on these innovations separately. However, no research study had grouped these innovations together to see how teachers perceived them within the context of a math classroom, and how teachers implemented them in their classrooms in order to increase student achievement.
Efficient Neural Network Verification with Exactness Characterization

Remarkable progress has been made on ver-iﬁcation of neural networks, i.e., showing that neural networks are provably consistent with speciﬁcations encoding properties like adversarial robustness. Recent methods developed for scalable neural network veriﬁcation are based on computing an upper bound on the worst-case violation of the speciﬁca-tion. Semideﬁnite programming (SDP) has been proposed as a means to obtain tight upper bounds. However, SDP solvers do not scale to large neural networks. We introduce a Lagrangian relaxation based on the SDP formulation and a novel algorithm to solve the relaxation that scales to networks that are two orders of magnitude larger than the off-the-shelf SDP solvers. Although veriﬁcation of neural networks is known to be NP-hard in general, we develop the ﬁrst known sufﬁcient conditions under which a polynomial time veri-ﬁcation algorithm (based on the above relaxation) is guaranteed to perform exact veriﬁcation (i.e., either verify a property or establish it is untrue). The algorithm can be implemented using primitives available readily in common deep learning frameworks. Experiments show that the algorithm is fast, and is able to compute tight upper bounds on the error rates under adversarial attacks of convolutional networks trained on MNIST and CIFAR-10.
Simultaneous localisation and mapping using a single camera

This thesis describes a system which is able to track the pose of a hand-held camera as it moves around a scene. The system builds a 3D map of point landmarks in the world while tracking the pose of the camera relative to this map using a process called simultaneous localisation and mapping (SLAM). To achieve real-time performance, the map must be kept sparse, but rather than observing only the mapped landmarks like previous systems, observations are made of features across the entire image. Their deviation from the predicted epipolar geometry is used to further constrain the estimated inter-frame motion and so improves the overall accuracy. The consistency of the estimation is also improved by performing the estimation in a camera-centred coordinate frame. As with any such system, tracking failure is inevitable due to occlusion or sudden motion of the camera. A relocalisation module is presented which monitors the SLAM system, detects tracking failure, and then resumes tracking as soon as the conditions have improved. This relocalisation process is achieved using a new landmark recognition algorithm which is trained on-line and provides high recall and a fast recognition time. The relocalisation module can also be used to achieve place recognition for a loop closure detection system. By taking into account both the geometry and appearance information when determining a loop closure this module is able to outperform previous loop closure detection techniques used in monocular SLAM. After recognising an overlap, the map is then corrected using a novel trajectory alignment technique that is able to cope with the inherent scale ambiguity in monocular SLAM. By incorporating all of these new techniques, the system presented can perform as a robust augmented reality system, or act as a navigation tool which could be used on a mobile robot in indoor and outdoor environments.
Social Reinforcement Learning to Combat Fake News Spread

In this work, we develop a social reinforcement learning approach to combat the spread of fake news. Speciﬁcally, we aim to learn an intervention model to promote the spread of true news in a social network—in order to mitigate the impact of fake news. We model news diffusion as a Multivariate Hawkes Process (MHP) and make interventions that are learnt via policy optimization. The key insight is to estimate the response a user will get from the social network upon sharing a post, as it indicates her impact on diffusion, and will thus help in efﬁcient allocation of incentive. User responses also depend on political bias and peer-inﬂuence, which we model as a second MHP, interleaving it with the news diffusion process. We evaluate our model on semi-synthetic and real-world data. The results demonstrate that our proposed model outperforms other alternatives that do not consider estimates of user responses and political bias when learning how to allocate incentives.
Ultralow power voltage reference circuit for implantable devices in standard CMOS technology

An ultralow power CMOS voltage reference for body implantable devices is presented in this paper. The circuit core consists of only regular threshold voltage PMOS transistors, thus leading to a very reduced output voltage dispersion, defined as σ/μ, and extremely low power consumption. A mathematical model of the generated reference voltage was obtained by solving circuit equations, and its numerical solution has been validated by extensive electrical simulations using a commercial circuit simulator. The proposed solution incorporates a passive RC low‐pass filter, to enhance power supply rejection (PSR) over a wide frequency range, and a speed‐up section, to accelerate the switching‐on of the circuit. The prototype was implemented in 0.18 μm standard CMOS technology and is able to operate with supply voltages ranging from 0.7 to 1.8 V providing a measured output voltage value of 584.2 mV at the target temperature of 36° C. The measured σ/μ dispersion of the reference voltage generated is 0.65% without the need of trimming. At the minimum supply of 0.7 V, the experimental power consumption is 64.5 pW, while the measured PSR is kept below –60 dB from DC up to the MHz frequency range.
Research of distributed intrusion detection system based on mobile agent

The defects of current intrusion detection systems(IDSs)are analyzed.A distributed intrusion detection system model is presented based on the mobile agents,the function of each module in the system is described,and the security problems of mobile agents are discussed.This model adopts the architecture which has no control center,avoids the problem of a single point failure completely.Agents are independent separately,while they can communicate and cooperate one another to take actions,realizes the distributed de-tection really,and strengthens flexibility and expansibility of the system.
Natural Language Question and Answer System on Semantic Health Website

Web search by using generic search engines is the most common activity on the Web. Despite a wide range of information one could gathered from the Internet, there has not been many websites reported providing facility for the user to query the information using a natural language. It is the aim of this research to develop a prototype that implements query technique based on natural language processing to answer such query, extraction and summarization technique to automatically generate paragraph level for a better time saving process. In early 2007, Cervical Cancer Organization reported that a female-related disease, particularly cervical cancer, is the 5th most common cancer in women worldwide. According to that report, the aim of this research is to ensure that the web-based tool developed in this study facilitate the knowledge sharing activities among medical practitioners and public users.
Approximate Relative Value Learning for Average-reward Continuous State MDPs

In this paper, we propose an approximate relative value learning (ARVL) algorithm for non-parametric MDPs with continuous state space and ﬁnite actions and average reward criterion. It is a sampling based algorithm combined with kernel density estimation and function approximation via nearest neighbors. The theoretical analysis is done via a random contraction operator framework and stochastic dominance argument. This is the ﬁrst such algorithm for continuous state space MDPs with average reward criteria with these provable properties which does not require any discretization of state space as far as we know. We then evaluate the proposed algorithm on a benchmark problem numerically.
Comprehension Monitoring: Identifying and Coping with Text Confusions1

Comprehension monitoring was investigated by asking college students to read and answer probed recall questions about passages that contained intentionally introduced confusions. Subjects were then told that confusions had been present and were asked to describe them and comment on how they affected comprehension. Subjects failed to report a surprisingly large proportion of the confusions. Confusions involving main points were detected more frequently than those involving details and confusions of inconsistent information and unclear reference were more often reported than inappropriate connectives. Retrospective reports revealed that failures to report confusions were often not due to failures to monitor comprehension but rather to the use of repair stategies to resolve the potential problems.
Seasonal to multiannual marine ecosystem prediction with a global Earth system model

Predicting marine futures The ability to predict how climate variations will affect marine ecosystems would allow better economic and ecosystem planning and management. Park et al. found that a global Earth system model skillfully predicted seasonal to multiannual ocean chlorophyll fluctuations in many regions. This could allow annual fish catches in some regions to be forecast 2 to 3 years in advance. Science, this issue p. 284 Earth system models could allow useful ecosystem predictions to be made as much as several years in advance. Climate variations have a profound impact on marine ecosystems and the communities that depend upon them. Anticipating ecosystem shifts using global Earth system models (ESMs) could enable communities to adapt to climate fluctuations and contribute to long-term ecosystem resilience. We show that newly developed ESM-based marine biogeochemical predictions can skillfully predict satellite-derived seasonal to multiannual chlorophyll fluctuations in many regions. Prediction skill arises primarily from successfully simulating the chlorophyll response to the El Niño–Southern Oscillation and capturing the winter reemergence of subsurface nutrient anomalies in the extratropics, which subsequently affect spring and summer chlorophyll concentrations. Further investigations suggest that interannual fish-catch variations in selected large marine ecosystems can be anticipated from predicted chlorophyll and sea surface temperature anomalies. This result, together with high predictability for other marine-resource–relevant biogeochemical properties (e.g., oxygen, primary production), suggests a role for ESM-based marine biogeochemical predictions in dynamic marine resource management efforts.
Constructing Part-task Congruent Representations to Support Coordination of Collaborative Problem-solving Tasks

This study investigated whether constructing part-task congruent domain-specific representations supports teams in establishing and maintaining a shared understanding of the knowledge domain and negotiating about it. This better coordination of team’ discussions was, in turn, expected to lead to better problem-solving performance. In triads secondary education students worked on a case-based business-economics problem in a predefined order, but differed in the representational tool(s) they received. In the matched condition, teams received the three tools in a part-task congruent manner. In the other three non-matched conditions, teams received one of the tools for all three part-tasks, thus a tool congruent to one part-task and incongruent for the other two. The results show that coordination processes were indeed better which might explain why teams in the matched condition performed better on the complex problem-solving task. However, similar results were obtained by teams who only received a tool for constructing causal representations for all part-tasks.
Preclinical evaluation of the simultaneous inhibition of MCL-1 and BCL-2 with the combination of S63845 and venetoclax in multiple myeloma

Apoptotic evasion has been postulated as one of the main mechanisms of multiple myeloma (MM) cell survival. [1][1],[2][2] The intrinsic apoptotic pathway, tightly regulated by the BCL-2 protein family, is initiated by intracellularly sensed stress signals and ultimately leads to the permeabilization
The efficacy of drug‐eluting beads bronchial arterial chemoembolization loaded with gemcitabine for treatment of non‐small cell lung cancer

Drug‐eluting beads bronchial arterial chemoembolization (DEB‐BACE) can embolize the tumor‐feeding artery and also be loaded with antitumor drugs, which can be released slowly into the local tumor environment. The effect of DEB‐BACE in patients with lung cancer remains unclear. We evaluated the efficacy and safety of DEB‐BACE with gemcitabine‐loaded CalliSpheres beads in patients with non‐small cell lung cancer (NSCLC).
Household Chaos, Maternal Emotional Responsiveness, and Child Eating Behavior: A Moderation Analysis.

OBJECTIVE To address calls for a resilience-informed approach to understand the cause and prevention of childhood obesity, the current study aims to investigate the independent and interactive associations between household chaos, maternal emotional responsiveness, and eating behavior in early childhood. METHOD A sample of (n = 108) families of 18- to 24-month-olds completed self-report surveys and consented to home visits as part of the larger STRONG Kids 2 (N = 468) study. Videotapes of family mealtimes were collected during home visits and coded for observed maternal emotional responsiveness. Mothers completed questionnaires assessing maternal emotional responsiveness, household chaos, and child eating behaviors. Moderation analyses assessed independent and interactive effects of chaos and emotional responsiveness on child appetite self-regulation. RESULTS In moderation analyses controlling for demographic covariates, higher levels of chaos were associated with more emotional overeating and with more food responsiveness, but only among children of mothers observed engaging in low levels of responsiveness at mealtimes. There was no association between chaos and eating behavior among children of mothers observed engaging in high levels of emotional responsiveness at mealtimes. There was also no independent or interactive association between chaos and child eating behaviors characterized by food avoidance. CONCLUSION Preliminary evidence suggests that maternal emotional responsiveness at mealtimes may attenuate the deleterious effects of chaos on child overeating and food responsiveness. Future research should prioritize using longitudinal designs, developing observational assessments of early childhood eating behaviors, and understanding these processes among families exposed to greater socioeconomic adversity.
circRNA_0006393 promotes osteogenesis in glucocorticoid‑induced osteoporosis by sponging miR‑145‑5p and upregulating FOXO1.

Glucocorticoids are the most common cause of glucocorticoid‑induced osteoporosis (GIOP). Moreover, the role of circular RNAs (circRNAs) in the regulation of bone metabolism remains unclear. Therefore, in the present study, it was hypothesized that hsa_circ_0006393 may play an important role in GIOP. To investigate the role of circRNAs in GIOP, treatment with dexamethasone or transfection with a vector overexpressing hsa_circ_0006393 were performed using in vitro cell and in vivo mouse models. Reverse transcription‑quantitative PCR, fluorescence in situ hybridization and western blotting were performed to investigate the function of hsa_circ_0006393 in vitro. In addition, the effects of hsa_circ_0006393 on osteogenesis were investigated. Dual‑energy X‑ray absorptiometry analysis was performed to examine the osteogenic potential of hsa_circ_0006393 in vivo. Moreover, the mechanism underlying hsa_circ_0006393‑mediated bone metabolism regulation via the microRNA (miR)‑145‑5p/forkhead box O1 (FOXO1) pathway was investigated. The present results suggested that the expression level of hsa_circ_0006393 was decreased in patients with GIOP. Furthermore, the overexpression of hsa_circ_0006393 increased the expression level of genes associated with osteogenesis. Moreover, hsa_circ_0006393 was identified to be localized mainly in the cytoplasm and nucleus of bone marrow mesenchymal stem cells. miR‑145‑5p was found to be directly targeted by hsa_circ_0006393. Collectively, hsa_circ_0006393 increases the expression levels of osteogenic genes during bone remodeling by sponging miR‑145‑5p and upregulating FOXO1.