Miracle-dz/UniFAR-FTUs huggingface dataset:
Physiologic Responsiveness to Social Interaction in Mothers with and without a History of Depression

Maternal depression is associated with child psychiatric illness, especially in adolescent girls. Depressed mothers have difficulty regulating their own emotions and display diminished emotional reactivity when interacting with their children. In order to better understand the role that such interpersonal difficulties may play in the intergenerational transmission of depression, the present study examined vagal responsiveness, a physiologic indictor of emotion regulation, via measurement of high-frequency heart rate variability (HF-HRV) in pairs of mothers and adolescent daughters during interaction tasks in which they discussed pleasant events and disagreements. Participants included 23 mother-daughter pairs in which both mother and daughter had a history of depression and 23 non-psychiatric control pairs in which neither mother nor daughter had a history of psychiatric illness. Separate piecewise linear growth models were used to compare slopes of HF-HRV between groups of mothers and daughters. Results showed that control mothers and daughters displayed positive slopes in HF-HRV during both pleasant events and disagreement discussions, and negative slopes during rest periods following the discussions. In contrast, mothers and daughters with a history of depression showed minimal vagal responsiveness during discussion and rest periods. These results suggest that while control mothers and daughters displayed vagal flexibility and activation during both discussion tasks—which may facilitate positive socio-emotional engagement and development—depressed individuals exhibited a lack of flexible and sensitive vagal responsiveness. Finally, exploratory analyses examined the covariation of vagal responsiveness between mother-daughter pairs. During the pleasant events discussion, a strong positive correlation was obtained among control dyads and no association was found for controls during the disagreement discussion. In contrast, during both discussions, a negative association between mothers’ and daughters’ patterns of responsiveness was obtained among dyads with a history of depression. The inverse correlations found in dyads with a history of depression suggest that in these individual dyads, mothers and daughters experienced the discussions in different ways, whereas the positive correlation found for control dyads suggests that control mothers and daughters experienced the pleasant events discussion similarly. Treatment strategies aimed at eliciting and sustaining mutual positive emotional interactions may be beneficial for depressed dyads.
Memory Leak Detection in Distributed System

Due to memory leaks, often-valuable system memory gets wasted and denied for other processes thereby affecting the computational performance. If an application’s memory usage exceeds virtual memory size, it can leads to system crash. Current memory leak detection techniques for clusters are reactive and display the memory leak information after the execution of the process (they detect memory leak only after it occur). This paper presents a Dynamic Memory Monitoring Agent (DMMA) technique. DMMA framework is a dynamic memory leak detection, that detects the memory leak while application is in execution phase, when memory leak in any process in the cluster is identified by DMMA it gives information to the end users to enable them to take corrective actions and also DMMA submit the affected process to healthy node in the system. Thus provides reliable service to the user. DMMA maintains information about memory consumption of executing processes and based on this information and critical states, DMMA can improve reliability and efficaciousness of cluster computing. Keywords—Dynamic Memory Monitoring Agent (DMMA), Cluster Computing, Memory Leak, Fault Tolerant Framework, Dynamic Memory Leak Detection (DMLD).
Inequality and Human Rights: Who Controls What, When, and How

This article tests the empirical relationship between inequality and the protection of personal integrity rights using a cross-national time-series data set for 162 countries for the years 1980–2004. The data comprise measures of land inequality, income inequality, and a combined factor score for personal integrity rights protection, while the analysis controls for additional sets of explanatory variables related to development, political regimes, ethnic composition, and domestic conflict. The analysis shows robust support for the empirical relationship between income inequality and personal integrity rights abuse across the whole sample of countries as well as for distinct subsets, including non-communist countries and non-OECD countries. The hypothesized effect of land inequality is also born out by the data, although its effects are less substantial and less robust across different methods of estimation. Additional variables with explanatory weight include the level of income, democracy, ethnic fragmentation, domestic conflict, and population size. Sensitivity analysis suggests that the results are not due to reverse causation, misspecification or omitted variable bias. The analysis is discussed in the context of inequality and rights abuse in specific country cases and the policy implications of the results are considered in the conclusion.
Use of Phonon Confinement Model in Simulation οf Raman Spectra of Nanostructured Materials

The simulation of the Raman spectra of nanostructured materials, where the effects of frequency shift and asymmetric broadening of the Raman modes play an important role, can be very useful in systematic characterization of these materials. Use of phonon confinement model for calculating Raman spectra of different nanomaterials is considered both from the viewpoint of different confinement function and the confinement strength, as well as the dimensionality of the confinement model. The phonon dispersion relations and the choice of their approximation are also studied. The influence of particle size distribution on the shape of the calculated spectra is discussed and contributions of Gaussian and asymmetric Gaussian distribution are compared. The effects of average and inhomogeneous strain on the behavior of simulated Raman spectra are also discussed. The results of the phonon confinement model are compared to the experimental spectra of CeO2 and anatase TiO2 nanopowders.
Predicting Putative Target Genes of Activator Protein 1 Based on the dsDNA Microarray Data

Large scale identification of APltarget genes will be helpful for elucidating the whole biological function. But in natural enhancer regions, the sequences of API regulatory elements often deviate from the optimal recognition consensus sequence TGA(C/G) TCA. We therefore fabricated a double- stranded DNA (dsDNA) microarray with all possible single- nucleotide mutated (SNM) sequences of API consensus site and explored the binding affinity of these SNM sequences with one of API family protein, c-Jun. We selected the top four highest binding affinity SNM sequences and scanned their existences in the upstream 5 kb sequence of the known human genes in Homo sapiens. Those genes with the highest binding affinity sequence were deduced as putative target genes (PTGs) of API. Annotated with GO term relating with tumorigenesis we got some API PTGs likely correlated with carcinogenesis.
A Novel Kinematic Coupling-Based Trajectory Planning Method for Overhead Cranes

Motivated by the desire to achieve smooth trolley transportation and small payload swing, a kinematic coupling-based off-line trajectory planning method is proposed for 2-D overhead cranes. Specifically, to damp out unexpected payload swing, an antiswing mechanism is first introduced into an S-shape reference trajectory based on rigorous analysis for the coupling behavior between the payload and the trolley. After that, the combined trajectory is further tuned through a novel iterative learning strategy, which guarantees accurate trolley positioning. The performance of the proposed trajectory is proven by Lyapunov techniques and Barbalat's lemmas. Finally, some simulation and experiment results are provided to demonstrate the superior performance of the planned trajectory.
Maximum likelihood detection for the linear MIMO channel

this thesis the problem of maximum likelihood (ML) detection for the linear multiple-input multiple-output (MIMO) channel is considered. The thesis investigates two algorithms previously proposed in the literature for implementing the ML detector, namely semide nite relaxation and sphere decoding. The first algorithm, semide nite relaxation, is a suboptimal implementation of the ML detector meaning that it is not guaranteed to solve the maximum likelihood detection problem. Still, numerical evidence suggests that the performance of the semide nite relaxation detector is close to that of the true ML detector. A contribution made in this thesis is to derive conditions under which the semide nite relaxation estimate can be guaranteed to coincide with the ML estimate. The second algorithm, the sphere decoder, can be used to solve the ML detection problem exactly. Numerical evidence has previously shown that the complexity of the sphere decoder is remarkably low for problems of moderate size. This has led to the widespread belief that the sphere decoder is of polynomial expected complexity. This is however unfortunately not true. Instead, in most scenarios encountered in digital communications, the expected complexity of the algorithm is exponential in the number of symbols jointly detected. However, for high signal to noise ratio the rate of exponential increase is small. In this thesis it is proved that for a large class of detection problems the expected complexity is lower bounded by an exponential function. Also, for the special case of an i.i. d. Rayleigh fading channel, an asymptotic analysis is presented which enables the computation of the expected complexity up to the linear term in the exponent.
Acronym-Expansion Disambiguation for Intelligent Processing of Enterprise Information

An acronym is an abbreviation of several words in such a way that the abbreviation itself forms a pronounceable word. Acronyms occur frequently throughout various documents, especially those of a technical nature, for example, research papers and patents. While these acronyms can enhance document readability, in a variety of fields, they have a negative effect on business intelligence. To resolve this problem, we propose a method of acronym-expansion disambiguation to collect high-quality enterprise information. In experimental evaluations, we demonstrate its efficiency through the use of objective comparisons.
Evaluation of Industrial By-Products as Sustainable Pozzolanic Materials in Recycled Aggregate Concrete

The utilization of traditional supplementary cementitious materials (SCMs) has become more intense in the concrete industry due to their better long-term properties. This research evaluates the fresh and hardened properties of concrete that was developed using a high amount of recycled aggregate (RA) incorporated with sustainable SCMs. Rice husk ash (RHA), palm oil fuel ash (POFA) and palm oil clinker powder (POCP) were used as SCMs at 10%, 20% and 30% cement replacement levels to investigate their positive role in the performance of RA concrete. The results showed that the 10% replacement level of cement by RHA produced the highest strength at all ages tested. Although POFA and POCP were found to negatively affect the strengths at an early age, the hardened properties showed improvement after a relatively long curing time of 90 days. In addition, the targeted compressive strength of 30 MPa was achieved by using SCMs at levels up to 30%. Overall, the sustainable SCMs can reduce the quantity of cement required for concrete production, as well as reduce the conventional cement with the industrial by-products, which are considered as waste materials; thus, the concrete produced using up to 30% of SCMs as a replacement for cement could be considered as more environmentally-friendly concrete.
Control of spin injection by direct current in lateral spin valves

The spin injection and accumulation in metallic lateral spin valves with transparent interfaces are studied using dc injection current. Unlike ac-based techniques, this allows the investigation of the effects of the direction and magnitude of the injected current. We find that the spin accumulation is reversed by changing the direction of the injected current, whereas its magnitude does not change. The injection mechanism for both current directions is thus perfectly symmetric, leading to the same spin injection efficiency for both spin types. This result is accounted for by a spin-dependent diffusion model. Joule heating increases considerably the local temperature in the spin valves when high-current densities are injected ($\ensuremath{\sim}80\char21{}105\text{ }\text{K}$ for $1\char21{}2\ifmmode\times\else\texttimes\fi{}{10}^{7}\text{ }\text{A}\text{ }{\text{cm}}^{\ensuremath{-}2}$), strongly affecting the spin accumulation.
Adaptive beamforming technique for large-scale arrays with various subarray selections

An adaptive beamforming technique for large-scale arrays has been proposed recently, where a subarray with much smaller number of antenna elements is selected from the original array to perform digital sampling, and the beamforming coefflcients for the original large array are calculated by using only the data samples from the selected subarray. In this paper, we consider various selections for the subarray that meet the requirements. We evaluate the performance of this adaptive beamforming method based on different subarray selections and get some useful conclusions on how to select the subarrays. Moreover, we also consider different weight calculation algorithms that are robust to the covariance matrix mismatch. Simulations are provided to compare the results obtained by different strategies.
Low-Noise Amplifier Design and Optimization

Low-Noise Amplifiers are key components in the receiving end of nearly every communications system. The wanted input signal of these systems is usually very weak and the primary purpose of the LNA is consequently to amplify the signal while at the same time adding as little additional noise as possible. Its performance is measured in a number of figures of merit among which gain and noise figure are most notable while dynamic range, return loss and stability are examples of others. In May 2005 a four year design study entitled EISCAT_3D was initialized. Its purpose was to investigate the feasibility of a next-generation incoherent scatter radar system. One of the responsibilities of EISLAB at Lulea University of Technology is to design a receiver front-end, which include an LNA with extremely high performance requirements. For that reason a MATLAB Particle Swarm Optimization implementation was developed to iteratively find a solution to optimal component values for a user definable LNA topology. In this master's thesis, the radio frequency concepts essential to traditional LNA design as well as the design procedure itself are explained. A description to the optimizer is then given, including a chapter on 2-port noise calculations. With the objective to find an LNA design with even higher performance than the previously designed EISCAT_3D LNA, four topologies are evaluated using the optimizer while consistently targeting the EISCAT_3D specifications. These topologies include the original reference design and one that employs the inductive source degeneration design technique. The latter showed significantly improved performance with an approximate 2 dB gain increase and 0.1 dB noise figure reduction while still maintaining the return loss and stability requirements.
DeServE: delay-agnostic service offloading in mobile edge clouds: poster

The mobile edge computing platform [2, 3] generally measured the delay based on the total time required to offload the services of edge devices to edge servers. On the other hand, the service delay is also depended on the response time of edge services from different mobile applications. Hence, there exists a disparity between the actual and measured service delay experienced by the mobile edge devices. This type problem arises due to the fact that the wireless radio network infrastructure is shared by the multiple mobile devices. As a result, the congestion occurs in the network and the arrival packets are likely to be dropped by the network switches in the access network. In such situation, the real-time critical edge applications mostly care about the quality-of-service (QoS) for different mobile devices, while offloading the edge services to edge servers. Thus, we improve the QoS of edge devices using delay-agnostic service offloading scheme to meet the offloading requirements of those delay-agnostic applications. Prior works have devoted to filling the gap at edge network by introducing the priority-based computational offloading [1] or energy-efficient resource allocation [4] schemes for edge computing applications. However, the priority-based service offloading and resource allocation do not provide the fair QoS to mobile devices, as the actual bottleneck is usually existed in the delay-agnostic nature of mobile applications. Therefore, although the existing offloading schemes perform well for multi-modal applications in terms of energy efficiency and computational overhead [1]. However, in those works, they assumed that the delay requirement of services to be fixed, but in real-life the delay requirement of services may vary radically. This type of situation is considered to be delay-agnostic property for edge devices, in this poster. Looking at the above points, we propose DESERVE, which introduces a delay-agnostic service offloading scheme for mobile edge computing platform in order to improve the QoS of each individual. The overview of DESERVE is depicted in Figure 1. For the edge devices, the flexible and optimal resource allocation technique is exploited for delay-agnostic service offloading scheme in edge computing platform. The resource allocation technique is leveraged for edge devices using the advanced techniques of software defined networks (SDN). However, an adaptive service identifier is deployed specifically for the identification of critical edge applications at the edge of mobile edge platform, instead of installing centralized SDN controller. After the identification of critical edge services, the identified services are forwarded to the controller and the corresponding rules to be offloaded for those services in the edge servers of edge platform.
An optimized planning model for black-start units considering CCHP systems as start units

CCHP (combined cooling, heating and power) systems have good performance as black-start units. It is the most important black-start unit in areas which do not have hydro power units. In this paper, the CCHP system is designed and planned under extra consideration of it serving as a black-start unit. It puts forward an optimized planning (allocation) model for CCHP systems with the consideration of CCHP systems being black-start units. Based on the regional black-start units, black-start schemes and load conditions, the reliability of black-start, outage cost and investment on construction are calculated. Aiming to minimize outage cost and investment on construction, setting simulation results as constraints, building the optimized model and finally applying the Particle Swarm Optimization (PSO) method to attain the best solution. The analysis of example case indicates that the optimized planning proposed here is effective. It gives important reference for the design and planning of CCHP system.
In vitro effect of fluoroquinolones and aminoglycosides on surface hydrophobicity and motility of Salmonella enterica serotype Typhimurium DT 104

The antibacterial efficacy of five fluoroquinolones (ciprofloxacin, enoxacin, norfloxacin, ofloxacin, pefloxacin) and four aminoglycosides (amikacin, gentamicin, netilmicin, tobramycin) against a multidrug-resistant isolate S. enterica serotype Typhimurium DT104 was evaluated. The present study further investigated the ability of sub-MIC concentrations of these antibiotics to interfere with the cell-surface hydrophobicity as well as with the motility of the strain tested. Our results showed that (i) the most effective in the suppression of bacterial growth were ciprofloxacin (MIC = 0.09 μg/mL) and netilmicin (MIC = 0.39 μg/mL), (ii) of the factors contributing to the virulence of S. enterica serotype Typhimurium DT104 the cell-surface hydrophobicity evaluated by SAT assay was decreased after effect of fluoroquinolones at sub-MICs but adhesion to polystyrene was moderately inhibited only with sub-MICs of ciprofloxacin, pefloxacin, ofloxacin and norfloxacin. The Congo red binding was inhibited with sub-MICs of pefloxacin and norfloxacin. Of the aminoglycosides only sub-MICs of gentamicin expressively influenced the hydrophobicity of the bacterial strain. Sub-MIC concentrations of all aminoglycosides studied did not influence its capability to adhere to plastic, (iii) while fluoroquinolones did not inhibit the motility, aminoglycoside amikacin expressively suppressed this feature within the whole concentration range. Our results indicate that both fluoroquinolones and aminoglycosides at subMICs are capable of influencing the surface hydrophobicity and motility of multidrug-resistant S. enterica serotype Typhimurium DT104. These findings may be useful when considering the selection of appropriate antibiotics for the treatment of serious infections caused by this emerging pathogen.
MRI quantitative myocardial perfusion with compartmental analysis: A rest and stress study

K1 (first‐order transfer constant from arterial plasma to myocardium for Gd‐DTPA) and Vd (distribution volume of Gd‐DTPA in myocardium) were measured in vivo in a canine model (n = 5) using MRI‐derived myocardial perfusion curves and a compartmental model. Perfusion curves were obtained after a bolus injection of Gd‐DTPA (0.04 mM/kg) with an inversion‐prepared fast gradient echo sequence. Myocardium and blood signal intensity were converted to a concentration of Gd‐DTPA, according to a model appropriate for short (<1 s) interimage intervals characteristic of cardiac‐triggered acquisitions. Before dipyridamole‐induced stress, K1 and Vd, obtained from the fit of the MRI‐derived perfusion curves, were 6.2 ± 1.4 (mHz) and 17.5 ± 4.2%, respectively. After dipyridamole infusion, a K1 increase of a factor of 2.82 ± 0.72 was measured (P = 0.003). No change was observed in Vd (P = 0.98). These results suggest that the K1 increase after dipyridamole reflects a flow‐related effect that can be useful to quantity the MRI‐derived perfusion curves.