Miracle-dz/UniFAR-FTUs huggingface dataset:
Quantifying and manipulating the angles of light in experimental measurements of plant gas exchange

Abstract Diffuse light has been shown to alter plant leaf photosynthesis, transpiration and water‐use efficiency. Despite this, the angular distribution of light for the artificial light sources used with common gas exchange systems is unknown. Here, we quantify the angular distribution of light from common gas exchange systems and demonstrate the use of an integrating sphere for manipulating those light distributions. Among three different systems, light from a 90° angle perpendicular to the leaf surface (±5.75°) was <25% of the total light reaching the leaf surface. The integrating sphere resulted in a greater range of possible distributions from predominantly direct light (i.e., >40% of light from a 90 ± 5.75° angle perpendicular to the leaf surface) to almost entirely diffuse (i.e., light from an even distribution drawn from a nearly 0° horizontal angle to a perpendicular 90° angle). The integrating sphere can thus create light environments that more closely mimic the variation in sunlight under both clear and cloudy conditions. In turn, different proportions of diffuse light increased, decreased or did not change photosynthetic rates depending on the plant species observed. This new tool should allow the scientific community to explore new and creative questions about plant function within the context of global climate change.
Pavement noise investigation on North Carolina highways: an on-board sound intensity approach

This paper presents the findings on tire–pavement noise on various types of pavements by using an on-board sound intensity (OBSI) method. Mitigation of traffic noise has become an increasingly important consideration for highway agencies when constructing new highways or improving the existing systems. As a competitive alternative for noise mitigation, quieter pavement may provide advantages that noise barriers do not have, or to where sound barriers are not suited. The first step in developing quieter pavement is identifying the noise levels of different types of highway pavements. To reach the ultimate goals of quieter pavement development, this research has focused on the most imperative task, i.e., to measure the noise levels of different types of pavements in North Carolina (NC). Pavement noise levels of 61 highway sites including 153 test sections around 30 counties for nine types of pavements across North Carolina have been investigated. A thorough literature review was conducted and OBSI testing e.
A Influência de Aspectos Sociais das VANETs na Qualidade de Disseminação de Dados de Eventos Críticos Urbanos

O apoio e o tratamento diário de eventos críticos nas cidades estão entre os grandes desaﬁos dos centros urbanos. Logo, as informações destes eventos devem ser disseminadas eﬁcientemente às entidades competentes. As VANETs naturalmente podem apoiar o monitoramento de eventos aleatórios no tempo e espaço. Além disso, os relacionamentos sociais entre usuários dos veículos estabelecem comunidades locais, cuja inteligência social pode ser aplicada na disseminação dos dados coletados pela VANET a ﬁm de apoiar a gestão pública no reconhecimento de eventos. Este trabalho investiga como os parâmetros sociais inﬂuenciam na qualidade de disseminação de dados de eventos críticos urbanos. Analisou-se o impacto das estratégias inﬂuência social, atividade social e amizade, e considerou-se os impactos na qualidade de serviço e de experiência. Os resultados mostram que a atividade social tem maior inﬂuência na QoS, com aumento de 106% a 175% na entrega de pacotes do que as demais em ambientes densos, e a inﬂuência social proporciona uma melhor QoE.
A New Control Strategy for Coordinated Control of Ground Vehicle Vertical Dynamics via Control Allocation

The scope of this thesis concerns the basic research and development of a coordinated control system for the control of vehicle roll and pitch dynamics using suspension forces as actuators. In this thesis, the following question is explored: How can suspension control (particularly semi-active control) be generalized to control all vertical vehicle dynamics in a coordinated way, and which would ideally be integrable with modern ESC systems? The chosen approach to this problem will be the application of the control allocation methodology for overactuated systems, which makes use of online mathematical optimization in order to realize the desired control law. Background information on vehicle dynamics and modeling, suspension control, control allocation and optimization is presented along with a brief literature review. The coordinated suspension control system (CSC) is designed and simulated. High-level controllers and control allocators are designed and their stability properties are explored. Then, the focus is shifted towards implementation and experimentation of the coordinated control system on a real vehicle. The semi-active actuators are statistically modeled along with the deployed sensors. Both the hardware and software designs are explored. Finally, experiments are designed and results are discussed. Recommendations for future inquiry are given in the conclusion of this work.
Why Computer Security Matters to ElectricalEngineers

In this paper we analyze two computer security incidents of particular interest to electrical engineers: "Stuxnet" worm attack on Iran's nuclear enrichment facility; and the "Project Aurora" by Idaho National Laboratory that exposed the vulnerability of power grids. Based on these incidents, we think that a secure system development method can mitigate security vulnerabilities in Industrial Control Systems (ICS). Such method must include systems, people and processes within an organization. Both technical and human factors should be considered. We discuss a Secure System Development Cube Cycle based on the 3P Method as a potential solution
Prediction of PM2.5 Concentration on the Basis of Multi-Time Scale Fusion

Long-term prediction of hour-concentration of PM2.5 (particles in atmospheric suspension with effective dimensions equal or lower than 2.5 microns) is of great significance for environmental protection and people’s health. At present, the prediction of hour-concentration of PM2.5 is mostly single-step prediction, which is to predict PM2.5 concentration at a future time point based on a period of historical data. In this paper, a model based on multi-time scale fusion is proposed to study single-step prediction and multi-step prediction, respectively. Experimental results show that the proposed model is better than stacked LSTM and CNN-LSTM in predicting PM2.5 hour-concentration.
Studies of DNA demethylation

DNA methylation is an epigenetic event which regulates gene expression by transcriptional repression and plays an important role in the biological phenomena of imprinted genes and X inactivation. On the other hand, the reversal of DNA methylation, DNA demethylation, is not as well understood. DNA demethylation has been demonstrated to occur as an active process during embryo development, tumourigenesis and hormone-induced gene activation, or via a replication-dependent passive route. However, the molecular mechanism of active DNA demethylation is yet to be determined, and a precise role of DNA demethylation in vivo remains obscure. Interestingly, bacteriophage T3 has been reported to express S-adenosylmethionine hydrolase (SAMase) during the early stage of phage infection. In order to overcome the restriction-modification (R-M) system, SAMase destroys the modification cofactor S-adenosylmethionine (SAM) and hydrolyses SAM into homoserine and methylthioadenosine (MTA). Since SAM is also the major donor of the methyl groups incorporated in DNA methylation, this SAM cleaving activity may be utilized as a demethylating agent, which helps us to understand the mechanism of DNA demethylation. However, the reaction mechanism of T3 SAMase has not been very well studied. To further elucidate this mechanism, experiments were carried out to purify recombinant SAMase and to enable attempts to solve the crystal structure of this enzyme. In addition, we aimed to observe effects of DNA demethylation in mammalian cells by using this hydrolase activity to reduce the cellular level of SAM. SAMase was also chosen to substitute the more commonly used demethylating agent, 5-azaC, in order to avoid the highly toxic impact on drug-receiving cells. Additionally, RNA interference (RNAi), was utilised to explore the impact of DNA demethylation. Using small interfering RNA (siRNA), we depleted the mRNA of the enzyme responsible for maintenance methylation, DNA methyltransferase 1 (Dnmtl), and observed a correlation between DNA demethylation and Xist expression when the methyl-binding protein MBD2 was removed. Furthermore, the oxidative DNA repair has been suggested as a candidate pathway, which involves demethylation of the 1-methyladenine and 3-methylcytosirie via a hydroxmethyl intermediate. To explore this possible mechanism, we investigated the candidate pathway by searching for a putative intermediate of hydroxymethyl cytosine during active DNA demethylation in vivo.
The Effects of Antidepressant Therapy on Health-Related Quality of Life in Patients with a Chronic Obstructive Pulmonary Disease and Depressive Symptoms

Abstract Background. Symptoms of depression are often present in patients with chronic obstructive pulmonary disease (COPD) and treatment of depression may substantially improve the quality of life of such patients. The aim of our study was to investigate factors that influence the efficacy of antidepressant therapy in terms of the quality of life in patients with COPD and a depressive disorder. Materials and Methods. The study was designed as a prospective cross-sectional study and conducted between October 2016 and December 2019 in the Primary Health Center, Kragujevac, Serbia. The study sample included 87 patients. Associations between putative risk factors and change in the quality-of-life score were tested by a multivariate linear regression model and interpreted by the regression coefficients. Results. Our study showed a clear positive effect of therapy with SSRIs on the severity of depression symptoms and the quality of life of patients with co-occurrence of COPD and depression. However, multiple linear regression shows that the effect of SSRIs was more prominent in patients with a higher degree of COPD severity since patients with lower FEV1 values had a more extensive increase in the Q-LES-Q-SF score (B=-0,034; p=0,020). Conclusion. Treatment of depression that accompanies COPD is an important segment of managing such patients, which significantly improves HRQoL. Patients with more severe COPD would especially benefit from such treatment since their response to SSRIs is more pronounced.
Artificial Emotional Intelligence in Socially Assistive Robots for Older Adults: A Pilot Study

This paper presents our recent research on integrating artificial emotional intelligence in a social robot (Ryan) and studies the robot's effectiveness in engaging older adults. Ryan is a socially assistive robot designed to provide companionship for older adults with depression and dementia through conversation. We used two versions of Ryan for our study, empathic and non-empathic. The empathic Ryan utilizes a multimodal emotion recognition algorithm and a multimodal emotion expression system. Using different input modalities for emotion, i.e., facial expression and speech sentiment, the empathic Ryan detects users’ emotional state and utilizes an affective dialogue manager to generate a response. On the other hand, the non-empathic Ryan lacks facial expression and uses scripted dialogues that do not factor in the users’ emotional state. We studied these two versions of Ryan with 10 older adults living in a senior care facility. The statistically significant improvement in the users’ reported face-scale mood measurement indicates an overall positive effect from the interaction with both the empathic and non-empathic versions of Ryan. However, the number of spoken words measurement and the exit survey analysis suggest that the users perceive the empathic Ryan as more engaging and likable.
A theory of entropic bonding

Significance Computer simulations of hard, polyhedrally shaped particles predict a great diversity of complex colloidal crystal structures via self-assembly. The structural similarities between colloidal crystals and atomic crystals suggest that they should be describable within analogous, although different, conceptual frameworks. Like the chemical bonds that hold atoms together in crystals, the statistical, emergent forces that hold together hard colloidal particles should be describable using the language of bonding. Whereas atomic crystals can be predicted a priori by solving Schrödinger’s equation, we present a theory of entropic bonding that permits prediction of colloidal crystals by solving a different eigenvalue equation, facilitated by the use of mathematically constructed shape orbitals analogous to atomic orbitals. Entropy alone can self-assemble hard nanoparticles into colloidal crystals of remarkable complexity whose structures are the same as atomic and molecular crystals, but with larger lattice spacings. Molecular simulation is a powerful tool used extensively to study the self-assembly of ordered phases from disordered fluid phases of atoms, molecules, or nanoparticles. However, it is not yet possible to predict colloidal crystal structures a priori from particle shape as we can for atomic crystals from electronic valency. Here, we present such a first-principles theory. By calculating and minimizing excluded volume within the framework of statistical mechanics, we describe the directional entropic forces that collectively emerge between hard shapes, in familiar terms used to describe chemical bonds. We validate our theory by demonstrating that it predicts thermodynamically preferred structures for four families of hard polyhedra that match, in every instance, previous simulation results. The success of this first-principles approach to entropic colloidal crystal structure prediction furthers fundamental understanding of both entropically driven crystallization and conceptual pictures of bonding in matter.
Spatial Environment Affects HNF4A Mutation-Specific Proteome Signatures and Cellular Morphology in hiPSC-Derived β-Like Cells

Studies of monogenic diabetes are particularly useful because we can gain insight into the molecular events of pancreatic β-cell failure. Maturity-onset diabetes of the young 1 (MODY1) is a form of monogenic diabetes caused by a mutation in the HNF4A gene. Human-induced pluripotent stem cells (hiPSCs) provide an excellent tool for disease modeling by subsequently directing differentiation toward desired pancreatic islet cells, but cellular phenotypes in terminally differentiated cells are notoriously difficult to detect. Re-creating a spatial (three-dimensional [3D]) environment may facilitate phenotype detection. We studied MODY1 by using hiPSC-derived pancreatic β-like patient and isogenic control cell lines in two different 3D contexts. Using size-adjusted cell aggregates and alginate capsules, we show that the 3D context is critical to facilitating the detection of mutation-specific phenotypes. In 3D cell aggregates, we identified irregular cell clusters and lower levels of structural proteins by proteome analysis, whereas in 3D alginate capsules, we identified altered levels of glycolytic proteins in the glucose sensing apparatus by proteome analysis. Our study provides novel knowledge on normal and abnormal function of HNF4A, paving the way for translational studies of new drug targets that can be used in precision diabetes medicine in MODY.
Cloud Computing based Disaster Recovery: An Introduction

Disaster never comes with prior warning. Business model in the new era has changed. The security and availability of business data has been become most important requirement in this time. For solving the problem related to business database services like storage, security, stability, load, scalability and many other issues cloud based database platform were used. Services related to data were put on the cloud and the powerful operating systems and platform were used to process the data. This survey paper describe the different methods and architecture of cloud storage and present the disaster recovery based on the cloud computing.
BCR-ABL1 Tyrosine Kinase Complex Signaling Transduction: Challenges to Overcome Resistance in Chronic Myeloid Leukemia

The constitutively active BCR-ABL1 tyrosine kinase, found in t(9;22)(q34;q11) chromosomal translocation-derived leukemia, initiates an extremely complex signaling transduction cascade that induces a strong state of resistance to chemotherapy. Targeted therapies based on tyrosine kinase inhibitors (TKIs), such as imatinib, dasatinib, nilotinib, bosutinib, and ponatinib, have revolutionized the treatment of BCR-ABL1-driven leukemia, particularly chronic myeloid leukemia (CML). However, TKIs do not cure CML patients, as some develop TKI resistance and the majority relapse upon withdrawal from treatment. Importantly, although BCR-ABL1 tyrosine kinase is necessary to initiate and establish the malignant phenotype of Ph-related leukemia, in the later advanced phase of the disease, BCR-ABL1-independent mechanisms are also in place. Here, we present an overview of the signaling pathways initiated by BCR-ABL1 and discuss the major challenges regarding immunologic/pharmacologic combined therapies.
Automating Genetic Algorithm Mutations for Molecules Using a Masked Language Model

Inspired by the evolution of biological systems, genetic algorithms have been applied to generate solutions for optimization problems in a variety of scientific and engineering disciplines. For a given problem, a suitable genome representation must be defined along with a mutation operator to generate subsequent generations. Unlike natural systems, which display a variety of complex rearrangements (e.g., mobile genetic elements), mutation for genetic algorithms commonly utilizes only random pointwise changes. Furthermore, generalizing beyond pointwise mutations poses a key difficulty as useful genome rearrangements depend on the representation and problem domain. To move beyond the limitations of manually defined pointwise changes, here we propose the use of techniques from masked language models to automatically generate mutations. As a first step, common subsequences within a given population are used to generate a vocabulary. The vocabulary is then used to tokenize each genome. A masked language model is trained on the tokenized data in order to generate possible rearrangements (i.e., mutations). In order to illustrate the proposed strategy, we use string representations of molecules and use a genetic algorithm to optimize for drug-likeness and synthesizability. Our results show that moving beyond random pointwise mutations accelerates genetic algorithm optimization.
Impact of Mutual Coupling and Polarization of Antennas on BER Performances of Spatial Multiplexing MIMO Systems

This paper is aimed to study the impact of mutual coupling,matching networks and polarization of antennas on Bit-Error-Ratio(BER) performance of MIMO systems employing spatial multiplexing based Bell lab LAyered Space-Time(BLAST) coding technique.An accurate signal analysis framework based on circuit network parameters is presented to describe the transmit/receive characteristics of the matched/unmatched antenna array,and Monte-Carlo numerical simulation are used to study the BER performance of spatial multiplexing MIMO systems.The studied arrays consist of matched/unmatched compact array and polarization diversity array.The simulation results demonstrate that the use of matching networks can reduce the BER of spatial multiplexing MIMO systems,and the BER performance deteoriation can also be compensated by use of polarization diversity antenna arrays.
Preparation of Spin-Coated Poly(vinyl alcohol)/
chitosan/ Gold Nanoparticles Composite
and Its Potential for Colorimetric Detection
of Cyanide in Water

The rampant use of cyanide in mining activities has posed a substantial hazard to aquatic ecosystems and human health. Herein, a composite film of poly(vinyl alcohol)/chitosan (PVA/CS) with gold nanoparticles was synthesized as a potential colorimetric sensor for cyanide ions detection in water. The utilized AuNPs with a mean diameter of 14.32±3.49 nm were synthesized by chemical reduction using polyethyleneimine. Ultraviolet-visible spectroscopy revealed the characteristic peak of AuNPs at around 530 nm in the spectrum of PVA/CS/AuNP film, while SEM microscopy revealed the integration AuNPs across the polymer substrate. A color change from red to colorless was observed on the composite film after the addition of water samples with cyanide ions with a visual detection limit between 0.1-1 ppm. The sensor also exhibited good selectivity towards cyanide against the tested water samples containing e-mail: rey.capangpangan@msunaawan.edu. ph DOI: 10.15244/pjoes/140276 ONLINE PUBLICATION DATE: 2022-01-18 Budlayan M.L. M. , et al. 1570
Leakage and field emission in side-gate graphene field effect transistors

We fabricate planar graphene field-effect transistors with self-aligned side-gate at 100 nm from the 500 nm wide graphene conductive channel, using a single lithographic step. We demonstrate side-gating below 1 V with conductance modulation of 35% and transconductance up to 0.5 mS/mm at 10 mV drain bias. We measure the planar leakage along the SiO2/vacuum gate dielectric over a wide voltage range, reporting rapidly growing current above 15 V. We unveil the microscopic mechanisms driving the leakage, as Frenkel-Poole transport through SiO2 up to the activation of Fowler-Nordheim tunneling in vacuum, which becomes dominant at higher voltages. We report a field-emission current density as high as 1 μA/μm between graphene flakes. These findings are important for the miniaturization of atomically thin devices.