Miracle-dz/UniFAR-FTUs huggingface dataset:
Android Malware Detection via (Somewhat) Robust Irreversible Feature Transformations

As the most widely used OS on earth, Android is heavily targeted by malicious hackers. Though much work has been done on detecting Android malware, hackers are becoming increasingly adept at evading ML classifiers. We develop <inline-formula> <tex-math notation="LaTeX">$\textsf {FARM}$ </tex-math></inline-formula>, a Feature transformation based <underline>A</underline>nd<underline>R</underline>oid <underline>M</underline>alware detector. <inline-formula> <tex-math notation="LaTeX">$\textsf {FARM}$ </tex-math></inline-formula> takes well-known features for Android malware detection and introduces three new types of feature transformations that transform these features irreversibly into a new feature domain. We first test <inline-formula> <tex-math notation="LaTeX">$\textsf {FARM}$ </tex-math></inline-formula> on 6 Android classification problems separating goodware and “other malware” from 3 classes of malware: rooting malware, spyware, and banking trojans. We show that <inline-formula> <tex-math notation="LaTeX">$\textsf {FARM}$ </tex-math></inline-formula> beats standard baselines when no attacks occur. Though we cannot guess all possible attacks that an adversary might use, we propose three realistic attacks on <inline-formula> <tex-math notation="LaTeX">$\textsf {FARM}$ </tex-math></inline-formula> and show that <inline-formula> <tex-math notation="LaTeX">$\textsf {FARM}$ </tex-math></inline-formula> is very robust to these attacks in all classification problems. Additionally, <inline-formula> <tex-math notation="LaTeX">$\textsf {FARM}$ </tex-math></inline-formula> has automatically identified two malware samples which were not previously classified as rooting malware by any of the 61 anti-viruses on VirusTotal. These samples were reported to Google’s Android Security Team who subsequently confirmed our findings.
Economic Administration and Institutional Management in a Decentralized Regime Mode: New Insights from Environmental Resources

Purpose: There are many factors causing deterioration of environmental quality and environmental damage that can be identified from observations in the field. Therefore in this paper we try to be revealed in general as a picture of environmental portraits, especially in relation to environmental management and enforcement of environmental law in the era of regional autonomy. Design/methodology/approach: By using qualitative method, the study was conducted in about six months (February to August of 2018) in West Java Province to observe Indonesian government's policy on environmental law in the era of regional autonomy. Findings: The results found that the decentralization system made environmental policy making and implementation overlapping and not uniform both horizontally and vertically. This management is also not supported by adequate management institutions, so that environmental management has not yet had a positive economic effect on the people. Practical implications: Although public understanding and awareness of the importance of the environment has been increased some people are still weak and must to be improved on this issue. The study can be used as an example to achieve this goal quite effectively. Originality/value: The study seeks to examine public administration of natural resources and management of environmental institutionalization in a state by adopting a decentralized system, which takes Indonesia as a case study using a special region in West Java Province.
Variability and Plasticity in Cuticular Transpiration and Leaf Permeability Allow Differentiation of Eucalyptus Clones at an Early Age

Background and Objectives. Water stress is a major constraining factor of Eucalyptus plantations’ growth. Within a genetic improvement program, the selection of genotypes that improve drought resistance would help to improve productivity and to expand plantations. Leaf characteristics, among others, are important factors to consider when evaluating drought resistance evaluation, as well as the clone’s ability to modify leaf properties (e.g., stomatal density (d) and size, relative water content at the time of stomatal closure (RWCc), cuticular transpiration (Ec), specific leaf area (SLA)) according to growing conditions. Therefore, this study aimed at analyzing these properties in nursery plants of nine high-productivity Eucalyptus clones. Material and Methods: Five Eucalyptus globulus Labill. clones and four hybrids clones (Eucalyptus urophylla S.T. Blake × Eucalyptus grandis W. Hill ex Maiden, 12€; Eucalyptus urograndis × E. globulus, HE; Eucalyptus dunnii Maiden–E. grandis × E. globulus, HG; Eucalyptus saligna Sm. × Eucalyptus maidenii F. Muell., HI) were studied. Several parameters relating to the aforementioned leaf traits were evaluated for 2.5 years. Results: Significant differences in stomatal d and size, RWCc, Ec, and SLA among clones (p < 0.001) and according to the dates (p < 0.001) were obtained. Each clone varied seasonally the characteristics of its new developing leaves to acclimatize to the growth conditions. The pore opening surface potential (i.e., the stomatal d × size) did not affect transpiration rates with full open stomata, so the water transpired under these conditions might depend on other leaf factors. The clones HE, HG, and 12€ were the ones that differed the most from the drought resistant E. globulus control clone (C14). Those three clones showed lower leaf epidermis impermeability (HE, HG, 12€), higher SLA (12€, HG), and lower stomatal control under moderate water stress (HE, HG) not being, therefore, good candidates to be selected for drought resistance, at least for these measured traits. Conclusions: These parameters can be incorporated into genetic selection and breeding programs, especially Ec, SLA, RWCc, and stomatal control under moderate water stress.
Adaptive Maternal Investment in the Wild? Links between Maternal Growth Trajectory and Offspring Size, Growth, and Survival in Contrasting Environments

Life-history theory predicts that investment per offspring should correlate negatively with the quality of the environment that offspring are anticipated to encounter; parents may use their own experience as juveniles to predict this environment and may modulate offspring traits, such as growth capacity and initial size. We manipulated nutrient levels in the juvenile habitat of wild Atlantic salmon (Salmo salar) to investigate the hypothesis that the egg size that maximizes juvenile growth and survival depends on environmental quality. We also tested whether offspring traits were related to parental growth trajectory. Mothers that grew fast when young produced more offspring and smaller offspring than mothers that grew slowly to reach the same size. Despite their size disadvantage, offspring of faster-growing mothers grew faster than those of slower-growing mothers in all environments, counter to the expectation that they would be competitively disadvantaged. However, they had lower relative survival in environments where the density of older predatory/competitor fish was relatively high. These links between maternal (but not paternal) growth trajectory and offspring survival rate were independent of egg size, underscoring that mothers may be adjusting egg traits other than size to suit the environment their offspring are anticipated to face.
Supply chain network design under the risk of uncertain disruptions

Facility disruptions in the supply chain often lead to catastrophic consequences, although they occur rarely. The low frequency and non-repeatability of disruptive events also make it impossible to estimate the disruption probability accurately. Therefore, we construct an uncertain programming model to design the three-echelon supply chain network with the disruption risk, in which disruptions are considered as uncertain events. Under the constraint of satisfying customer demands, the model optimises the selection of retailers with uncertain disruptions and the assignment of customers and retailers, in order to minimise the expected total cost of network design. In addition, we simplify the proposed model by analysing its properties and further linearise the simplified model. A Lagrangian relaxation algorithm for the linearised model and a genetic algorithm for the simplified model are developed to solve medium-scale problems and large-scale problems, respectively. Finally, we illustrate the effectiveness of proposed models and algorithms through several numerical examples.
Applying the Theory of Access to Food Security among Smallholder Family Farmers around North-West Mount Kenya

Access to productive resources such as land and water is fundamental for households that rely on crop and livestock production for their livelihoods. Research often assumes that agricultural production—and thus, food security—are favoured by tenure security of resources (as represented by a “bundle of property rights”). However, research has not yet elucidated how food security is influenced by additional factors, represented within a “bundle of powers”. Guided by the Theory of Access developed by Ribot and Peluso, we explore the main factors in the respective bundles of rights and powers that influence household food security around north-west Mount Kenya. We interviewed 76 households—38 food secure and 38 food insecure—who were subsampled from a previous food security survey of 380 households. Results show that household food insecurity was not exclusively the result of a lack of private property rights as many farmers had retained their property rights. Instead, a major factor preventing access to productive resources was the difficulty faced by food insecure households in accessing farm technology (i.e. hand tools and implements). Access to authority and via social relations were significantly correlated with access to technology, so improving the latter must take into account the former.
A Novel Identification Method for Apple (Malus domestica Borkh.) Cultivars Based on a Deep Convolutional Neural Network with Leaf Image Input

The innovation of germplasm resources and the continuous breeding of new varieties of apples (Malus domestica Borkh.) have yielded more than 8000 apple cultivars. The ability to identify apple cultivars with ease and accuracy can solve problems in apple breeding related to property rights protection to promote the healthy development of the global apple industry. However, the existing methods are inconsistent and time-consuming. This paper proposes an efficient and convenient method for the classification of apple cultivars using a deep convolutional neural network with leaf image input, which is the delicate symmetry of a human brain learning. The model was constructed using the TensorFlow framework and trained on a dataset of 12,435 leaf images for the identification of 14 apple cultivars. The proposed method achieved an overall accuracy of 0.9711 and could successfully avoid the over-fitting problem. Tests on an unknown independent testing set resulted in a mean accuracy, mean error, and variance of μ a c c = 0.9685 , μ ε = 0.0315 , and σ 2 = 1.89025 E − 4 , respectively, indicating that the generalization accuracy and stability of the model were very good. Finally, the classification performance for each cultivar was tested. The results show that model had an accuracy of 1.0000 for Ace, Hongrouyouxi, Jazz, and Honey Crisp cultivars, and only one leaf was incorrectly identified for 2001, Ada Red, Jonagold, and Gold Spur cultivars, with accuracies of 0.9787, 0.9800, 0.9773, and 0.9737, respectively. Jingning1 and Pinova cultivars were classified with the lowest accuracies, with 0.8780 and 0.8864, respectively. The results also show that the genetic relationship between cultivars Shoufu 3 and Yanfu 3 is very high, which is mainly because they were both selected from a red mutation of Fuji and bred in Yantai City, Shandong Province, China. Generally, this study indicates that the proposed deep learning model is a novel and improved solution for apple cultivar identification, with high generalization accuracy, stable convergence, and high specificity.
RATIONAL DECISION MAKING AND FIRM PERFORMANCE: EMPIRICAL EVIDENCE FROM SMEs IN THAILAND

The purpose of this paper is to investigate the effects of rational decision making on business performance of the SMEs in Thailand. This research was conducted by using questionnaires as research instruments for collecting data from 247 executives of the SMEs in Thailand. The research found that the rational decision making in aspect of identifying problem, gathering information and evaluating alternatives (EA) are significantly and positively correlated to the firm’s overall performance. This research can be used as a guideline for the SME executives to create a business strategy and make an effective decision on business in order to improve their firm’s performance.
Estimation of Soil Quality of under Long Term Sugar Beet-wheat Cropping System by Factor Analysis

ABSTRACT Soil quality is a measurement used to calculate how well the soil will perform its functions and ensures the assessment of soils based on their physical, chemical and biological characteristics. The aim of this study was to facilitate the determination of soil quality, with soil properties selected by multi-criteria application, in a shorter time compared to that of conventional soils tests. A soil quality index (SQI) was determined by measuring the soil parameters under laboratory and field conditions in lands where agriculture has been taking place for many years. Based on the results of the factor analysis the 12 soil characteristics were selected for assessing the SQIs of each of the soil samples. The SQI results determined from physical, chemical, and biological soil properties with regards to total weight was calculated as 35.96%, 33.92%, and 30.12%, respectively. Based on the results of this study, it was determined that only 4 physical, 5 chemical and 3 biological properties could be used to evaluate soil quality. The selected indicators can be used in subsequent studies for the assessment of soil quality in areas where intensive agriculture has been used for many years.
Social Media and Teens: A Needs Assessment Exploring the Potential Role of Social Media in Promoting Health

Aims: Social media use is widespread in teens. But, few studies have developed recommendations on how social media can be used to promote teen health. The Philadelphia Ujima™ Coalition funded by the Office on Women’s Health conducted a needs assessment to explore social media as a health communication tool. This study aimed to identify (1) social media utilization practices, (2) strategies to effectively engage teens on social media, and (3) recommendations for teen health promotion on social media. Methods: A cross-sectional mixed methods study design was used, in which a survey was administered to 152 youth (ages: 13–18 years). In addition, four focus groups were conducted with 26 teens to elaborate on the quantitative findings. Results: We found that while 94.6% of teens use social media, only 3.5% reported using it to seek health-related information. However, when asked about specific topics (i.e., fitness, sexual health, nutrition), 66.7% to 91.7% reported health information seeking. Although, many teens were not able to identify reliable sources of information. Teens felt health messages should be attractive and tailored. Conclusion: Social media holds promise as an effective health communication tool; however, information must be reliable and composed of attractive messages tailored to meet teens’ diverse needs. The findings from this study are indicative of the critical need to further explore how social media platforms enhance usage in health promotion.
Executive Turnover and the Investigation of Former Leaders in New Democracies

What prompts governments in new democracies to investigate elected leaders once they leave office? Theorizing about democratic regimes suggests that leadership turnover by constitutional means should generate few such cases: democratic entry to and exit from office are thought to prompt benign treatment from successor administrations. Yet over a third of democratically elected presidents and prime ministers who left office between 1970 and 2011 have faced investigations for malfeasance. This study analyzes the conditions that generate such cases. We find that the odds of investigation rise when there is strong evidence of former leaders’ personal culpability; but also when the executive regime is presidential, and the judiciary lacks independence from other branches. Partisanship has a more limited impact: co-partisanship with the incumbent reduces the odds of investigation for ex-prime ministers, but sharing a party label with an incumbent offers no such protection to a former president.
Preliminary Design Method for Base Bleed Unit

Base bleed is a system for base drag reduction of projectile by gas injection into base area. The gas injecting through orifice is generated by combustion of solid propellant grain. Base bleed output mass flow rate depends on the chamber pressure, the pressure into which jet exhausts, time and spin rate. An analytical interior ballistics model of base bleed developing in the paper is based on basic fluid dynamics and experimental results of measured time for base bleed burning in the field of radial acceleration. By iterative method, chamber pressure and mass flow rate can be estimated during the base bleed work. The model is verified by available experimental results.
Designing for Physician Trust: Toward a Machine Learning Decision Aid for Radiation Toxicity Risk

The application of machine learning (ML) technologies in health care is expected to improve care delivery and patient outcomes. However, there are no best practices for designing these technologies for use in clinical settings. To explore user needs and design requirements for a user interface of a ML risk prediction tool in development, we consulted with subject matter experts and physicians. We explored physician expectations of using a ML tool in clinical practice and their preferences on designs. Our process revealed physician perspectives on trusting a ML tool and opportunities to design for these considerations, while navigating ambiguity in the tool’s outputs.
In-Sample and Out-of-Sample Sharpe Ratios of Multi-Factor Asset Pricing Models

For many multi-factor asset pricing models proposed in the recent literature, their implied tang-ency portfolios have substantially higher sample Sharpe ratios than that of the value-weighted market portfolio. In contrast, such high sample Sharpe ratio is rarely delivered by professional fund managers. This makes it difficult for us to justify using these asset pricing models for performance evaluation. In this paper, we explore if estimation risk can explain why the high sample Sharpe ratios of asset pricing models are difficult to realize in reality. In particular, we provide finite sample and asymptotic analyses of the joint distribution of in-sample and out-of-sample Sharpe ratios of a multi-factor asset pricing model. For an investor who does not know the mean and co-variance matrix of the factors in a model, the out-of-sample Sharpe ratio of an asset pricing model is substantially worse than its in-sample Sharpe ratio. After taking into account of estimation risk, our analysis suggests that many of the newly proposed asset pricing models do not provide superior out-of-sample performance than the value-weighted market portfolio.
Responding to imposed job redesign: The evolving dynamics of work and identity in restructuring professional identity

How do professionals respond when they are required to conduct work that does not match with their identity? We investigated this situation in an English public services organization where a major work redesign initiative required professionals to engage in new tasks that they did not want to do. Based on our findings, we develop a process model of professional identity restructuring that includes the following four stages: (1) resisting identity change and mourning the loss of previous work, (2) conserving professional identity and avoiding the new work, (3) parking professional identity and learning the new work, and (4) retrieving and modifying professional identity and affirming the new work. Our model explicates the dynamics between professional work and professional identity, showing how requirements for new professional work can lead to a new professional identity. We also contribute to the literature by showing how parking one’s professional identity facilitates the creation of liminal space that allows professional identity restructuring.
Avaliação de Ferramentas de Apoio ao Ensino de Técnicas de Mineração de Dados em Cursos de Graduação

O mercado de trabalho requer, cada vez mais, profissionais com senso analítico para lidar com volumosos conjuntos de dados de forma a produzir conhecimento útil à tomada de decisão. O processo de Mineração de Dados (MD) está entre os principais conceitos de descoberta de conhecimento e envolve o uso de diferentes algoritmos de aprendizado de máquina, aplicados para extrair novos padrões em bases de dados, comumente apoiado por ferramentas que implementam esses diferentes algoritmos. O uso de ferramentas para MD por alunos de graduação em disciplinas como Inteligência Artificial, Mineração de Dados ou outras que abordem técnicas de aprendizado de máquina, é fundamental para que eles adquiram experiência prática. Este trabalho avalia diferentes ferramentas utilizadas no ensino de MD, no intuito de oferecer aos docentes um guia na escolha e uso dessas ferramentas, do ponto de vista da usabilidade, aferida por alunos de graduação na descoberta e compreensão dos saberes associados.
Will retinal AVR and T1 predict cardiovascular risk in hypertensive patients

TITLE: Will retinal AVR and TI predict cardiovascular risk in hypertensive patients? BACKGROUND: Arterial hypertension (AHT) is the most important and modifiable risk factor for cardiovascular morbimortality (CVMM). The risk stratification tables for cardiovascular disease (CVD) do not include the retinal examination in early stages of AHT although retinal vessel alterations have proved to be associated with higher CVD risk. Retinography shows the state of our microcirculation system in vivo and it could give us information about the CVMM of hypertensive patients. Predicting the CVD risk by the use of retinography is an accessible and non-invasive way to control hypertensive patients during the evolution of this disease. So, AVR and TI could become important tools in the stratification risk of CVD and in the prevention of future cardiovascular events. MAIN OBJECTIVE: Determine whether cardiovascular prognosis could be predicted by the use of retinography (AVR and TI) in newly diagnosed and never-treated hypertensive patients. METHODS: It is an observational and prospective cohort study which will include newly diagnosed and never-treated hypertensive patients from Girona attending the CAP’s of Angles and Cassa de la Selva meeting the inclusion criteria. All participants will be following up during a total of 7 years. They will comply the ICS protocol for the AHT monitoring and a part of this; they will be practised a retinography per eye in order to calculate the AVR and the TI.
Review of heterobranch molluscs fauna in the Boka Kotorska Bay, Montenegro

Heterobranch molluscs fauna in Montenegro has been poorly investigated so far. The aim of the present paper is to improve the knowledge about species diversity of these marine organisms in the Boka Kotorska Bay, specific fjord-like entity in the southern Adriatic Sea. New records of seven heterobranch species were obtained by field surveys in 2017, while three new records were provided by analysing underwater photographs from previous periods. The resulted checklist summarizes the knowledge of the diversity of heterobranchs in the Boka Kotorska Bay from the oldest record in 1967 to the present day and consists of a total of 62 heterobranch species.