Miracle-dz/UniFAR-FTUs huggingface dataset:
The Developmental Characteristics of Adolescents' Family Functioning and Its Influence on Mental Health

Objective:To explore the developmental characteristics of adolescents' family functioning and its influence on mental health.Methods:928 middle school students in Xi'an were surveyed with The Chinese Family Assessment Instrument and SCL-90.Results:There were grade differences in parental control (F=7.50,P0.01)and communication dimensions (F=3.43,P0.01)of family functioning . There were gender differences in communication(2.3±0.9/2.5±0.8,t=5.86,P0.01)? parental control(2.3±1.0/2.0±1.0,t=15.8,P0.01) and communication (1.3±0.55/1.3±0.6,t=4.77,P0.05)dimensions of family functioning. We also found the middle school students' mental heath positively predicted by conflict and harmony? parental control and communication dimensions of family functioning.Conclusions: The middle school students' mental heath positively predicted by conflict and harmony? parental control and communication dimensions.
Comparison of ultraviolet radiation/hydrogen peroxide, Fenton and photo-Fenton processes for the decolorization of reactive dyes

The effectivness of UV/H2O2 process, Fenton and photo-Fenton process at decolorization of commercially important textile dyes Reactive Orange 4 (RO4) and Reactive Blue 19 (RB19) was evaluated. The effect of operational condition such as initial pH, initial H2O2 concentration, initial Fe2+ concentration and initial dye concentration on decolorization of RO4 and RB19 was studied. The photo-Fenton process is found to be more efficient than UV/H2O2 and Fenton process for decolorization of simulated dye bath effluent and solutions of the dyes in water alone under optimum conditions. In simulated dye bath the removal efficiency was slightly lower than for the solutions of the dyes in water alone for both dyes types. The results revealed that the tested advanced oxidation processes were very effective for decolorization of RO4 and RB19 in aqueous solution. [Projekat Ministarstva nauke Republike Srbije, br. TR34008]
Effect of Essential Phospholipids and Statin on Non Alcoholic Fatty Liver Disease in Rats Induced Periodontitis *

NAFLD is the most common form of chronic liver disease, it is the hepatic manifestation of metabolic syndrome. Periodontal disease may helpfully increase the risk of progression from NAFL to NASH. Effective strategies are needed to treat NAFLD and prevent progression to NASH so we conducted this study to investigate the efficacy of EPL and statin on biochemical parameters and histo-pathological finding in rats with NAFLD and periodontitis. Methods: 35 Male rats were divided into 5 groups, group 1:control group, group 2: NAFL, group 3: NAFL with periodontitis, group 4: rats with NAFL and periodontitis received EPL and group 5: rats with NAFL and periodontitis receiving statin after 30 days of treatment blood sample and mandibles were collected for biochemical analysis and histo-pathological findings. Result : group treated with statin significantly elevated (AST, ALT and ɤGGT) and lipid profile while treatment with EPL significantly reduced liver enzymes and lipid profile parameters, both EPL and Statin reduce OPG level and improved bone resorption which confirmed by histological findings. Conclusion: We confirm the efficacy of EPL in accelerating the improvement of biochemical and pathological findings, such as liver function enzymes, lipid profile and bone resorption in rats with NAFLD and periodontitis.
MONITORING OF CMV INFECTION IN KIDNEY TRANSPLANT RECIPIENTS

Human cytomegalovirus is a ubiquitous herpesvirus that establishes lifelong latency after primary infection, but can cause life-threatening disease in immunosuppressed patients. CMV invasive disease leads to significant morbidity and mortality following kidney transplantation. We tested 2 groups of patients Group A included 20 potential kidney recipients and 29 potential donors investigated by ELISA and Group B included 53 adult kidney transplant recipients all of them tested in ELISA and 24 of them tested in QRT-PCR for CMV-DNA from plasma samples. In group A 16 (80%) of 20 potential kidney recipients were anti-CMV IgG positive and 4 (20%) were antiCMV IgG negative. Twenty eight of 29 potential donors were found seropositive, and only one was not infected. In group B overall 119 ELISA tests for specific antiCMV antibodies were performed. Anti-CMV IgM negative was 68 (57%) of the tested samples, twelve (10%) showed anti-CMV IgM equivocal results and 39 samples (33%) were with anti-CMV IgM positive. Seven of them (13,2%) showed repeatedly anti CMV IgM positive results. All 119 (100%) displayed ànti-CMV IgG positive results. Overall 41 PCR analyses from plasma samples of 24 kidney transplant recipients (group B) were performed. CMVDNA replication was detected in 5 plasma samples obtained from 3 patients (12.5%) at a different time from 20 days till almost 8 years after the transplantation. Despite the high seroprevalence to CMV 20% of the potential recipients were at high risk of primary infection when receiving a kidney from a seropositive donor. Positive serological results during the regular posttransplantation monitoring complemented with or without clinical data are indicative and require further QRT-PCR analysis.
Big Data Analytics Embedded Smart City Architecture for Performance Enhancement through Real-Time Data Processing and Decision-Making

The concept of the smart city is widely favored, as it enhances the quality of life of urban citizens, involving multiple disciplines, that is, smart community, smart transportation, smart healthcare, smart parking, and many more. Continuous growth of the complex urban networks is significantly challenged by real-time data processing and intelligent decision-making capabilities. Therefore, in this paper, we propose a smart city framework based on Big Data analytics. The proposed framework operates on three levels: data generation and acquisition level collecting heterogeneous data related to city operations, data management and processing level filtering, analyzing, and storing data to make decisions and events autonomously, and application level initiating execution of the events corresponding to the received decisions. In order to validate the proposed architecture, we analyze a few major types of dataset based on the proposed three-level architecture. Further, we tested authentic datasets on Hadoop ecosystem to determine the threshold and the analysis shows that the proposed architecture offers useful insights into the community development authorities to improve the existing smart city architecture.
Disturbance compensation using CTC with NDOB for formation control of mobile robots

This paper proposed CTC (Computed Torque Control) with NDOB (Non-linear Disturbance Observer) to compensate disturbance for formation control of mobile robot. The kinematics models of robot is used to solve the formation control problem. The robot formation was formed using the SBC (Separation-Bearing Control) approach. However, in this paper also used SSC (Separation-Separation Control), because SSC approach can avoid collision between follower if one of the follower affected by disturbance. In this case, CTC is used to control the dynamics of the robot, but the controller has poor performance when the robot was affected by disturbance, consequently the formation that has been formed is interrupted when tracking trajectory. Under these conditions, NDOB is designed to estimate disturbance in robots. The simulation results show that CTC with NDOB succeeds to reducing the effect of disturbance on the robot so that the formation can be maintained when any follower was affected by disturbance.
Cognitive–behavioural therapy for psychosis

I am writing to comment on this debate ( [Turkington & McKenna, 2003][1]) from the point of view of a practising clinician who regularly works with people who are experiencing or recovering from psychotic symptoms. I find both cognitive–behavioural and psychodynamic models useful in my work. Many
Edit Distance between Unrooted Trees in Cubic Time

Edit distance between trees is a natural generalization of the classical edit distance between strings, in which the allowed elementary operations are contraction, uncontraction and relabeling of an edge. Demaine et al. [ACM Trans. on Algorithms, 6(1), 2009] showed how to compute the edit distance between rooted trees on $n$ nodes in $\mathcal{O}(n^{3})$ time. However, generalizing their method to unrooted trees seems quite problematic, and the most efficient known solution remains to be the previous $\mathcal{O}(n^{3}\log n)$ time algorithm by Klein [ESA 1998]. Given the lack of progress on improving this complexity, it might appear that unrooted trees are simply more difficult than rooted trees. We show that this is, in fact, not the case, and edit distance between unrooted trees on $n$ nodes can be computed in $\mathcal{O}(n^{3})$ time. A significantly faster solution is unlikely to exist, as Bringmann et al. [SODA 2018] proved that the complexity of computing the edit distance between rooted trees cannot be decreased to $\mathcal{O}(n^{3-\epsilon})$ unless some popular conjecture fails, and the lower bound easily extends to unrooted trees. We also show that for two unrooted trees of size $m$ and $n$, where $m\le n$, our algorithm can be modified to run in $\mathcal{O}(nm^2(1+\log\frac nm))$. This, again, matches the complexity achieved by Demaine et al. for rooted trees, who also showed that this is optimal if we restrict ourselves to the so-called decomposition algorithms.
Preconditions for Successful Knowledge Creation in the Context of Academic Innovation Projects

This paper assumes that the key to understanding successes and failures in knowledge creation (KC) by academic innovation teams in a scenario of university–industry relations is to identify and evaluate preconditions, needed for efforts to flourish. We examine the synergistic intervention of individual competence, information literacy, innovation culture and communication in academic project team work while KC occurs, resulting in technological innovation. Our in-depth research with 20 university project teams has led us to a more differentiated picture of KC in academic innovation projects. The qualitative technique of categorical content analysis was used. As the main contributions, we present in a four-dimensional perspective the resulting relationships between the knowledge created by the teams and the critical factors that influence its creation. Moreover, deriving from these relations, six patterns of behaviour were found in the study.
Space-time adaptive wavelet methods for parabolic evolution problems

With respect to space-time tensor-product wavelet bases, parabolic initial boundary value problems are equivalently formulated as bi-infinite matrix problems. Adaptive wavelet methods are shown to yield sequences of approximate solutions which converge at the optimal rate. In case the spatial domain is of product type, the use of spatial tensor product wavelet bases is proved to overcome the so-called curse of dimensionality, i.e., the reduction of the convergence rate with increasing spatial dimension.
Factors Determining the Success and Failure of eHealth Interventions: Systematic Review of the Literature

Background eHealth has an enormous potential to improve healthcare cost, effectiveness, and quality of care. However, there seems to be a gap between the foreseen benefits of research and clinical reality. Objective Our objective was to systematically review the factors influencing the outcome of eHealth interventions in terms of success and failure. Methods We searched the PubMed database for original peer-reviewed studies on implemented eHealth tools that reported on the factors for the success or failure, or both, of the intervention. We conducted the systematic review by following the patient, intervention, comparison, and outcome framework, with 2 of the authors independently reviewing the abstract and full text of the articles. We collected data using standardized forms that reflected the categorization model used in the qualitative analysis of the outcomes reported in the included articles. Results Among the 903 identified articles, a total of 221 studies complied with the inclusion criteria. The studies were heterogeneous by country, type of eHealth intervention, method of implementation, and reporting perspectives. The article frequency analysis did not show a significant discrepancy between the number of reports on failure (392/844, 46.5%) and on success (452/844, 53.6%). The qualitative analysis identified 27 categories that represented the factors for success or failure of eHealth interventions. A quantitative analysis of the results revealed the category quality of healthcare (n=55) as the most mentioned as contributing to the success of eHealth interventions, and the category costs (n=42) as the most mentioned as contributing to failure. For the category with the highest unique article frequency, workflow (n=51), we conducted a full-text review. The analysis of the 23 articles that met the inclusion criteria identified 6 barriers related to workflow: workload (n=12), role definition (n=7), undermining of face-to-face communication (n=6), workflow disruption (n=6), alignment with clinical processes (n=2), and staff turnover (n=1). Conclusions The reviewed literature suggested that, to increase the likelihood of success of eHealth interventions, future research must ensure a positive impact in the quality of care, with particular attention given to improved diagnosis, clinical management, and patient-centered care. There is a critical need to perform in-depth studies of the workflow(s) that the intervention will support and to perceive the clinical processes involved.
The Influence of Intrinsic Framework Flexibility on Adsorption in Nanoporous Materials

For applications of metal–organic frameworks (MOFs) such as gas storage and separation, flexibility is often seen as a parameter that can tune material performance. In this work we aim to determine the optimal flexibility for the shape selective separation of similarly sized molecules (e.g., Xe/Kr mixtures). To obtain systematic insight into how the flexibility impacts this type of separation, we develop a simple analytical model that predicts a material’s Henry regime adsorption and selectivity as a function of flexibility. We elucidate the complex dependence of selectivity on a framework’s intrinsic flexibility whereby performance is either improved or reduced with increasing flexibility, depending on the material’s pore size characteristics. However, the selectivity of a material with the pore size and chemistry that already maximizes selectivity in the rigid approximation is continuously diminished with increasing flexibility, demonstrating that the globally optimal separation exists within an entirely rigid pore. Molecular simulations show that our simple model predicts performance trends that are observed when screening the adsorption behavior of flexible MOFs. These flexible simulations provide better agreement with experimental adsorption data in a high-performance material that is not captured when modeling this framework as rigid, an approximation typically made in high-throughput screening studies. We conclude that, for shape selective adsorption applications, the globally optimal material will have the optimal pore size/chemistry and minimal intrinsic flexibility even though other nonoptimal materials’ selectivity can actually be improved by flexibility. Equally important, we find that flexible simulations can be critical for correctly modeling adsorption in these types of systems.
Evaluation of the performance of a machine learning algorithms in Swahili-English emails filtering system relative to Gmail classifier

In recent years, means of communication has changed from writing the letter and sending it by ordinary post to electronic mail. The unsolicited mails is among the security threat in this new technology, with millions of spam distributed daily. The social means of fighting against spammers are there but not effective and so the automatic spam filtering algorithms has been introduced to reduce the effects that are caused by spammers. This paper compares three algorithms that are running using the machine learning (ML) tool called Waikato Environment for Knowledge Analysis (WEKA) by using English-Swahili dataset that author created and the results are then compared with Gmail results that are calculated manually. The algorithms are Naïve Bayes, Sequential Minimal Optimization (SMO) and J48. The findings show that SMO gives good result compared to other algorithms with accuracy of 93.23% followed by Naïve Bayes 88.47% and J48 87.22%. Also, all three algorithms come out with good results ahead of Gmail filter has 86.26% accuracy.
An identification of success of academic system application using Delone and McLean design (Case study at Wira Husada school of health science Yogyakarta)

Academic information system is a system that is very important to be applied to every college, the system is used in order to assist college operators in processing students' grade data, lectures, and lecturers' data. Wira Husada School of health science is one of the colleges that has implemented academic information system, but the system implemented has not worked as it should be. This research aims to identify factors that influence the success of the application of academic information system that has been applied by Wira Husada School of health science using Delone and Mclean design by measuring six variables which are information quality, service quality, system quality, user, user satisfaction and net benefit. Researcher distributes questionnaires to 280 students of Wira Husada School of health science as the main users of the system, and then the data from the questionnaires are analyzed using SPSS and AMOS Program. The result of this research shows that the quality of information and system does not affect the user, but it affects user satisfaction, service quality affects user and user satisfaction, user satisfaction affects user, user affects net benefit and user satisfaction affects net benefit.
Hand gesture recognition using force myography of the forearm activities and optimized features

Hand gesture recognition has emerged as an attractive and promising method in human-machine interaction. Applying the simple, efficient and inexpensive devices is necessary for this kind of the application. In this paper, we propose a novel hand gesture recognition by investigating the forearm muscles movement data processing sensed by an array of 8 Force Sensor Resistor (FSR). The acquired data is sent by the wireless device to the processing unit that is more convenient for users. The feature extraction scheme is proposed to get some useful information about the data. A graph of the FSR sensed signals are constructed by considering the extracted features from them. Weights of the graph edge are computed by finding the differences between correspondents pair of sensors. Multiobjective optimization is applied to find the optimum parameters and providing the best description of the sensors' relations in each class. The proposed approach will be evaluated by conducting experiments. 10 volunteered persons participated in gathering FMG data in different classes of the hand gestures. As the results show the proposed method has good performance to recognize hand gestures and has almost 93% accuracy in the overall.
Interpersonal reactions toward depression and anger

Two studies examined the effect of interpersonal attitude on reactions toward others' expression of anger or depression, Participants read a story in which their schoolmate experienced a negative event and expressed anger or depression, and reported their perceptions, affective reactions, and behavioural intentions such as support or rejection. The results indicated that an expression of anger elicited more negative reactions than an expression of depression only when a person whom participants disliked expressed the emotion. Furthermore, structural equation modelling indicated that the effect of interpersonal attitude on sympathy, blame, and support intention was mediated by the perception of the distressfulness of the event. The discussion considered the processes through which the expression of negative emotions evokes positive or negative interpersonal reactions.
How to Love Change and Lead It

Abstract We challenge the belief that people resist change while embracing the idea that change is necessary to lead. Cultivating leaders to orchestrate conflict with deliberate intention is a skill leaders can learn. Yet, skill alone is insufficient to lead. Using three models, Communicative Intelligence, Adaptive Leadership, and Adaptive Schools, we tell the story of how we developed leaders to think adaptively and communicate authentically to collaborate across diverse communities to bring their visions to fruition. This chapter describes the models and their integration from three perspectives illustrating how we focused the cultivation of leaders. First, the personal development of their dispositions related to communication, collaboration, and systems thinking. Second we worked on developing the skills to build relationships and think politically. And third, we focused on identifying and implementing systems to address the critical issues facing their schools.
Feeding behaviour in dairy cows with and without the influence of clinical diseases or subclinical disorders

Abstract. The objective of this study was to describe and compare circadian pattern of feed intake and feeding behaviour in healthy and diseased dairy cows. Test animals (n=138) were separated into two groups according to their health status. Health and management data were used to exclude cows with clinical or subclinical diseases. Fifteen cows of the test herd complied with the defined criteria and formed the reference group »healthy«. The behaviour of the remaining 123 cows was compared with the reference group. Both groups were used to analyse the feed intake and feeding behaviour on a daily base and in the course of 24 h. During a defined time range from day 28 post-partum to day 56 post-partum behavioural differences within these groups were analysed. There were no significant differences in daily feed intake (40.7 vs. 41.9 kg fresh matter per day, P=0.42). However, feeding behaviour pattern differed between the two groups (daily feeder visits, daily feeding time, number of daily feeder visit, number of daily meals, meal duration, feeding time within a meal, feeder visits per meal). For example, average feeder visit was shorter in the group with subclinical/ clinical health disorders than in the reference group (7.2 vs. 8.1 min, P=0.024). Differences in circadian feeding behaviour could be detected by analysing the feed intake and feeding time over the course of the day. Linear regression analyses showed strong correlations between feeding time and feed intake on hourly base (R² = 0.8) and on daily base (R² = 0.7).