Miracle-dz/UniFAR-FTUs huggingface dataset:
Cross-species analysis of melanoma enhancer logic using deep learning

Genomic enhancers form the central nodes of gene regulatory networks by harbouring combinations of transcription factor binding sites. Deciphering the combinatorial code by which these binding sites are assembled within enhancers is indispensable to understand their regulatory involvement in establishing a cell’s phenotype, especially within biological systems with dysregulated gene regulatory networks, such as melanoma. In order to unravel the enhancer logic of the two most common melanoma cell states, namely the melanocytic and mesenchymal-like state, we combined comparative epigenomics with machine learning. By profiling chromatin accessibility using ATAC-seq on a cohort of 27 melanoma cell lines across six different species, we demonstrate the conservation of the two main melanoma states and their underlying master regulators. To perform an in-depth analysis of the enhancer architecture, we trained a deep neural network, called DeepMEL, to classify melanoma enhancers not only in the human genome, but also in other species. DeepMEL revealed the presence, organisation and positional specificity of important transcription factor binding sites. Together, this extensive analysis of the melanoma enhancer code allowed us to propose the concept of a core regulatory complex binding to melanocytic enhancers, consisting of SOX10, TFAP2A, MITF and RUNX, and to disentangle their individual roles in regulating enhancer accessibility and activity.
A personalised mobile learning system for promoting STEM discipline teachers' TPACK development

The contemporary education presents many challenges to improve teaching quality, including instructional practices knowledge, of teachers in science, technology, engineering, and mathematics (STEM) disciplines. To promote higher teaching competency for STEM teachers, the technological pedagogical content knowledge (TPACK) framework is recognisably and essentially adopted. To help improve TPACK for teachers, we proposed a mobile learning system that personalises digital learning contents by analysing learning styles, TPACK-oriented problems, content attributes, and mobile device and network capabilities. This study explored effects of the system on 78 in-service secondary-school science teachers in the Northeast of Thailand. The results indicated that the system significantly improved participants' TPACK skills in almost all aspects. Moreover, over 65% of participants were at least well satisfied with the system, and over 90% were at least moderately satisfied. These results showed that our system is a promising learning tool to improve STEM teachers' proficiencies under the TPACK framework.
Controle LFR Discreto de Quadrirotores usando o Framework ROS

: This paper presents the development of the discrete version of the Linear Fractional Representation (LFR) control method for nonlinear systems, based on Linear Matrix Inequalities (LMIs). The main objective of the technique is to guarantee the stability of critical nonlinearities of the discrete-time system. Because of their inherent nonlinear and discrete-time properties, quadrirotors are used to illustrate the application of the method. As the LFR naturally usually has very aggressive control gains, a byproduct of the paper is the extension to avoid saturation of the control signal. An additional objective is the validation of the model/control in the ROS/Gazebo framework, which has internal models of commercial quadrirotors. This tool is based on realistic numerical simulations of systems based on their physical construction and forms, and is an excellent way of validating the dynamics equations used for the control design. Resumo : Este artigo apresenta o desenvolvimento
What evidence is there that parenting interventions reduce child abuse and neglect among maltreating families? A systematic review

In families where child abuse and neglect have already occurred, there is a strong imperative to provide interventions that reduce or eliminate harm done to children. Parenting programs lack tailoring for the needs of maltreating parents, and maltreating parents themselves are a heterogeneous group with varying needs. The literature on the effectiveness of parenting interventions for high-risk parents is limited, and this scarcity of knowledge can result in child protection cases being treated as a natural experiment. For children who experience ongoing maltreatment by their parents, the most stringent test for effectiveness goes beyond an improvement in positive parenting skills—child abuse and neglect must reduce or be eliminated. The present review addressed the research question What evidence is there that parenting interventions conducted with parents who maltreat their children, reduce the incidence of further child maltreatment? Databases were searched for trials of parenting interventions where participants were maltreating parents and outcome data included an objective measure of child abuse and neglect. Nine studies satisfied the selection criteria and are summarized. Four studies reported a statistically significant difference between groups in favor of the intervention group for two parenting interventions, Parent–Child Interaction Therapy and SafeCare. However, the review concludes that none of the reviewed parenting interventions have been demonstrated to be effective at reducing all types of child maltreatment through a high-quality RCT. Previous research is compromised by several critical methodological limitations, including low participant recruitment and retention, and narrow selection criteria. Recommendations are offered for future research on parenting interventions that aim to reduce child abuse and neglect.
A learning-based control framework for cable-driven parallel robots with unknown Jacobians

Cable-driven parallel robots have been studied by many researchers in the past decades. The Jacobian of a cable-driven parallel robot may not be determined in some applications such as rehabilitation. In order to control the pose of a fully constrained cable-driven parallel robot with unknown Jacobian and driven by torque-controlled actuators, a learning-based control framework consisting of a robust controller and a neural network in series is proposed in this article. The neural network takes over the role of the Jacobian by mapping a wrench applied on the end-effector of the cable-driven parallel robot at a pose in the task space to a set of cable tensions in the joint space. In this way, the cable-driven parallel robot can be controlled by cable tensions derived from such a mapping, rather than solving the inverse dynamics problem based on the Jacobian. As an example, a control strategy is developed to demonstrate how the proposed control framework works. The control strategy includes a proportional–integral–derivative controller and a feedforward neural network. Simulation results show that the control strategy can successfully control a cable-driven parallel robot with four cables, three degrees of freedom, and unknown Jacobian.
On the distribution and complexity of gender and numeral classifiers

This paper surveys the occurrence of gender and numeral classifiers in the languages of the world and evaluates statistically whether there is a complexity tradeoff between these two linguistic patterns. Complexity is measured as overt coding of the pattern in a language, an approach that has been shown earlier to provide a reliable first estimate for possible trade-offs between typological variables. The data come from a genealogically and areally stratified sample of 360 languages.The relationship between gender and numeral classifiers in this data was researched by constructing Generalized Linear Mixed Models. According to the results a significant inverse relationship occurs between the variables independently of genealogical affiliation and geographical areas. The distributions are explained functionally by economy, that is, the tendency to avoid using multiple patterns in the same functional domain.
Mitochondrial Haplogroup Analyses of the Madia Gond Tribe: Tracking the Past Events of Prehistory of India

Abstract The origin and spread of agriculture in India is poorly understood. To address this, we analyzed mtDNA sequences of some ethnic groups from Eurasia to check for the support for the two most prevalent models of agricultural diffusion that is, ,Demic expansion- Vs ,Cultural diffusion-. Presence of haplogroup T1 in the Madia Gond and Baluch, and its exact identity with population inhabiting in and around Mediterranean region points towards Neolithic linkages between these populations. Further, occurrence of rare haplogroup N1a in one of the Baluch individual and its identity with 7500 old Neolithic farmer sequences from Europe further reinforce dispersal of human from the Fertile Crescent region. Our phylogenetic analysis indicates clustering of Madia Gond and Baluch sequences in the distinct T1 and N1a Neolthic clusters. Application of molecular clock to this cluster yields a time depth of ~10,000 which further reconfirms its Neolithic origin. Though upper Paleolithic origin of majority of Indian population is well established, but presence of T1 and N1a haplogroup in Madia Gond and Baluch respectively supports Neolithic Demic expansion model.
Warts under the Dermoscope

Warts are common benign epidermal proliferations caused by various strains of human papillomavirus [1]. Although their diagnosis is usually based on typical clinical features, clinicians may sometimes be confronted with features that overlap with other lesions. Dermoscopic examination of these lesions may help to distinguish them [2]. Our aim was to describe dermoscopic aspects of the different types of warts: vulgaris, plane, palmoplantar and genital.
Some determinantal considerations for pentadiagonal matrices

ABSTRACT In this note, we propose a research problem and two conjectures on the determinant of pentadiagonal matrices. At the same, we recall some results on pentadiagonal matrices and use them to provide new and short proofs of some recent determinantal identities for such matrices in the symmetric and skew-symmetric cases. This unified approach can be extended to further spectral consideration. In addition, two examples of explicit formulas of two non-trivial pentadiagonal matrices are provided.
Creating a portable programming abstraction for wavefront patterns targeting HPC systems

Processor architectures have been rapidly evolving for decades. From the introduction of the first multicore processor by IBM in 2001 [2] to the massively parallel supercomputers of today, the exploitation of parallelism has become increasingly important, as the clock rates of a single core have plateaued. Heterogeneity is also on the rise since the revelation that domain-specific pieces of hardware (GPUs) could be repurposed for generalized parallel computation [10]. This shift has prompted the need to rethink algorithms, languages, and programming models in order to increase parallelism from a programming standpoint and migrate large scale applications to today’s massively powerful platforms. This is not a trivial task, as these architectures and systems are still undergoing constant evolution. More recently, supercomputing centers are transitioning toward utilizing fat-nodes (nodes with even more cores due to the presence of multiple accelerators) in order to reduce node count and the overhead associated with cross-node communication. For example, Oak Ridge National Laboratory’s TITAN supercomputer (OLCF-3), which was built in 2011, was comprised of 18,688 nodes, each containing a single NVIDIA Tesla K20x GPU accelerator [60]. In 2018, less than a decade later, ORNL constructed the Summit supercomputer (OLCF-4), consisting of 4,608 nodes, each equipped with six NVIDIA Tesla V100 GPU accelerators [67]. The trend toward fat-node based systems illustrates the importance of on-node programming models. Low-level languages like CUDA and OpenCL offer direct control over GPU hardware, but they incur a learning curve and lack portability, which are concerns for application developers. It is a huge time sink to have to learn a hardware-specific low-level language, port your code using that language, and then reimplement that same code when a newer GPU (or non-GPU) architecture emerges.
Amino acetaldehyde conformers: structure and spectroscopic properties

We present a computational study of the different conformers of amino acetaldehyde. This molecule is a precursor of glycine and also an isomer of the detected molecules acetaldehyde and methylformamide. In addition, a previous theoretical result shows that amino acetaldehyde could be formed from the gas phase reaction of formamide with CH$_{5}^{+}$. Different computational approaches, going from density functional theory (DFT) to coupled cluster (CC) calculations, are employed for the characterization of the amino acetaldehyde conformers. We locate four low-lying conformation on the singlet potential energy surface (PES), two with a synperiplanar arrangement of the carboxylic oxygen atom and the NH2 group, and the other two conformers with an anticlinal disposition. All levels of theory predict the conformer with a synperiplanar arrangement and the H atoms of the NH2 group pointing in the direction of the oxygen, denoted as in-sp-amino acetaldehyde, as the most stable. The viability of the interconversion processes between the four conformers in space is analysed. Relevant spectroscopic parameters to rotational spectroscopy with ‘spectroscopic’ accuracy at the composite level are reported. Vibrational frequencies and infrared intensities are also computed at the CC with single and double excitations (CCSD) level including anharmonic corrections. This information could help in the experimental characterization of amino acetaldehyde that could be considered as a good candidate molecule to be searched for in space.
Pyruvate kinase controls signal strength in the insulin secretory pathway

Pancreatic β-cells couple nutrient metabolism with appropriate insulin secretion. Here, we show that pyruvate kinase (PK), which converts ADP and phosphoenolpyruvate (PEP) into ATP and pyruvate, underlies β-cell sensing of both glycolytic and mitochondrial fuels. PK present at the plasma membrane is sufficient to close KATP channels and initiate calcium influx. Small-molecule PK activators increase β-cell oscillation frequency and potently amplify insulin secretion. By cyclically depriving mitochondria of ADP, PK restricts oxidative phosphorylation in favor of the mitochondrial PEP cycle with no net impact on glucose oxidation. Our findings support a compartmentalized model of β-cell metabolism in which PK locally generates the ATP/ADP threshold required for insulin secretion, and identify a potential therapeutic route for diabetes based on PK activation that would not be predicted by the β-cell consensus model. GRAPHICAL ABSTRACT The consensus model for β-cell glucose sensing supports a dominant role for OxPhos. This model doesn’t fully explain the observed metabolic and electrophysiologic oscillations associated with glucose-stimulated insulin secretion. Lewandowski et al. challenge this model by mechanistically connecting the anaplerotic PEP cycle to the electrically silent triggering phase, and OxPhos to the electrically active secretory phase. Here, the allosteric recruitment of pyruvate kinase directs metabolic traffic between the two cycles and identifies potential therapeutic strategies for diabetes based on pharmacologic pyruvate kinase activation. HIGHLIGHTS Compartmentalized pyruvate kinase (PK) activity underlies β-cell fuel sensing Membrane-associated PK closes KATP channels and controls calcium influx By lowering ADP, PK toggles mitochondria between OxPhos and PEP biosynthesis Pharmacologic PK activation increases oscillatory frequency and amplifies secretion
The effects of a single atom substitution and temperature on electronic and photophysical properties F8T2 organic material

The electronic and photophysical features of F8T2 organic semiconductor -based on a single atom substitution and temperature have been carried out by the self-consistent charge density-functional based tight-binding (SCC-DFTB) which is based on the density functional theory (DFT) and molecular dynamics (MD) methods. First of all, the heat treatment was carried out on the F8T2 from 50 K to 600 K. After that, the optoelectronic features of F8T2 by substitution of some nonmetallic single atoms, such as Fluorine (F), Bromine (Br) and Iodine (I) was studied. Herein, the dipole moments, HOMO, LUMO, bandgap and Fermi energies were searched. Also, the absorbance has been examined by time-dependent (TD)-DFTB. The obtained results of F8T2 were compared to experimental results. The HOMO value was found as -5.045 eV, which is compatible with its experimental value (-5.44 eV); the LUMO value was found -2.729 eV, which is coherent with the experimental LUMO value (-2.95 eV). Similarly, the bandgap of F8T2 (2.32 eV) was found to be compatible with measured result (2.49 eV). The bandgap for F8T2 increased from 2.32 eV (at 0 K) to 3.03 K (at 663.38 K) which is about 0.71 eV wide than that of F8T2 at 0 K. The maximum absorbance is found as 437 nm which is very well matched with experimental value (465 nm).
Financial Literacy Levels of Medium and Small Scale Businesses Owners and its Correlation with Firms’ Operating Performance: in Case of Hossana Town

Financial literacy is seen as an important instrument for the success of medium and small businesses, since it helps to understand and evaluate the information needed to make daily decisions that have financial impacts in companies’ day-to-day management. Therefore, the goal of this research is twofold: to assess the financial literacy levels of small business owners (medium and small enterprises) in the Hossana Town and to analyze the relation between these results and the operating performance of those companies, as a measure of business economic performance. The study tests the hypothesis that, all other factors being constant, a higher financial literacy level of small business owners should motivate a better performance of the company. The sample in this study is composed by medium and small businesses of the Hossana town in the three sub cities, and through questionnaires it was obtained the data needed to gauge the levels of financial literacy. The results evidence a rather level of financial literacy among small business owners. And, the data also supports the existence of a significant positive correlation between financial literacy levels and companies’ operating performance. This result highlights the importance of providing to small business owner adequate financial education on the expectation of improving their performance as business leaders.
Teacher Attrition And Retention In Exceptional Student Education: An Evaluation Of The Skills, Tips, And Routines For Teacher Success (STARTS) Initiative of Volusia County, Florida Schools

Teacher attrition affects the quality of services for students in K-12 education and poses an ongoing challenge for educational leaders, especially in the area of special education. Special educators leave the profession at higher rates than general educators. As a growing state, Florida has identified special education as a critical teacher shortage area. This study evaluated the Skills, Tips, and Routines for Teacher Success (STARTS) initiative of Volusia County Schools, a large district in east central Florida. Implemented in 2001 for new ESE teachers, STARTS offered four days of training in policies and procedures, curriculum, and classroom management. Research questions addressed whether STARTS influenced retention of new ESE teachers. Because the literature cited age, ethnicity, special education program area, and grade level assignment as factors in attrition, these were assessed as well. Incorporating employment histories from school year (SY) 1998-1999 through SY 2003-2004, the study evaluated 771 new ESE teachers. Of these, 422 teachers did not participate in STARTS; 349 teachers participated in STARTS. The study reported whether they returned the following year to an ESE position, a general education position, or exited the school system. Contingency table analysis with crosstabulation was used to evaluate statistical relationships among variables. Effect size was assessed with Cramer's V and the contingency coefficient. All analyses were conducted with an alpha of . 05. A significant difference existed between the retention rates of new ESE teachers hired before STARTS and during STARTS. In 2000-2001, the school year preceding STARTS, 54.3% of new ESE teachers returned to an ESE position whereas in the first year of STARTS, 71.1% of new ESE teachers returned to an ESE position, an increase of 51%. By SY 2003-2004, 89.7% of new ESE teachers returned to an ESE position, an increase of 65% from the SY 2000-2001 baseline.
Daddy Dearest: The Influence of Paternal Investment on Attitude toward the Advertisement

Three studies were conducted using nonstudent samples to empirically test the impact of paternal engagement and paternal sentiment (PS) on customer evaluations of advertising content. Paternal investment theory (PIT), an extension of attachment theory, states that the quality of fathering that a daughter receives provides important information about others and society. Paternal sentiment, the global perception of one’s father, is defined and introduced to the advertising literature in this project. Both constructs are examined for males and females within a marketing context for the first time. An experiment is conducted in Study 1 to establish that low paternal investment (PI) and negative paternal sentiment lead to high customer evaluations for ads with maternal referents. Results from a second experiment suggest that customers with low paternal investment are more responsive to ads with maternal referents, particularly when combined with self-focus messaging. In Study 3, subjects participate in a field study. The findings suggest that when negative paternal sentiment and low paternal investment are primed, females are more prone to emotionally regulate than males. These research outcomes should inspire advertisers to consider the father–child relationship within the family structure as a possible basis for brand positioning.
Load-Balanced and QoS-Aware Software-Defined Internet of Things

Internet of Things (IoT) offers a variety of solutions to control industrial environments. The new generation of IoT consists of millions of machines generating huge traffic volumes; this challenges the network in achieving the Quality-of-Service (QoS) and avoiding overload. Diverse classes of applications in IoT are subject to specific QoS treatments. In addition, traffic should be distributed among IoT servers based on their available capacity. In this article, we propose a novel framework based on software-defined networking (SDN) to fulfill the QoS requirements of various IoT services and to balance traffic between IoT servers simultaneously. At first, the problem is formulated as an integer linear programming (ILP) model that is NP-hard. Then, a predictive and proactive heuristic mechanism based on time-series analysis and fuzzy logic is proposed. Afterward, the proposed framework is implemented in a real testbed, which consists of the Open vSwitch, Floodlight controller, and Kaa servers. To evaluate the performance, various experiments are conducted under different scenarios. The results indicate the improved IoT QoS parameters, including throughput and delay, and illustrate the nonoccurrence of overload on IoT servers in heavy traffic. Furthermore, the results show improved performance compared to similar methods.