Miracle-dz/UniFAR-FTUs huggingface dataset:
Cognitive-behavioral therapy for Internet gaming disorder: A systematic review and meta-analysis.

OBJECTIVE Although there is sufficient research and clinical evidence to support the inclusion of gaming disorder in the latest revision of the International Classification of Diseases, relatively little is known about the effectiveness of first-line psychological treatment for gaming disorder or internet gaming disorder (IGD) as it is listed in the Diagnostic and Statistical Manual. This systematic review employed meta-analytic techniques to determine the effectiveness of cognitive-behavioural therapy (CBT) for IGD on four key outcomes: IGD symptoms, anxiety, depression, and time spent gaming. METHOD A database search identified 12 independent CBT studies. Effect size estimates (Hedges' g) with associated confidence intervals, prediction intervals, and p values for each pre-post treatment outcome, were calculated. Study reporting quality was evaluated in accordance with the Consolidated Standards of Reporting Trials guidelines. Subgroup and moderator analyses were undertaken to investigate potential sources of heterogeneity. RESULTS CBT demonstrated high efficacy in reducing IGD symptoms (g = 0.92; [0.50, 1.34]) and depression (g = 0.80, [0.21, 1.38]), and showed moderate efficacy in reducing anxiety (g = 0.55, [0.17, 0.93]) at post-test. There was insufficient power to determine whether CBT was capable of reducing time spent gaming. Treatment gains at follow-up were nonsignificant across the four treatment outcomes. CONCLUSIONS The pooled findings suggest that CBT for IGD is an effective short-term intervention for reducing IGD and depressive symptoms. However, the effectiveness of CBT for reducing actual time spent gaming was unclear. Given the limitations of this evidence base, there is a need for more rigorous studies to determine the potential long-term benefits of CBT for IGD. PUBLIC HEALTH SIGNIFICANCE STATEMENT Given the rise in treatment demand for internet gaming disorder (IGD) and problematic gaming, it is necessary to determine which treatments are most effective for whom and under which conditions. This review shows that cognitive-behavioural therapy for IGD, which is often considered the first-line therapy, can improve IGD symptoms and comorbid depression. However, treatment gains tend to be short-term and their effect in reducing time spent gaming is unclear. Programs that target problematic gaming may be improved by additional support beyond the standard program of therapy sessions. More funding and resources are needed to support the development of a more rigorous evidence base on IGD and its treatment.
Emergent Failures: Rethinking Cloud Reliability at Scale

Since the conception of cloud computing, ensuring its ability to provide highly reliable service has been of the upmost importance and criticality to the business objectives of providers and their customers. This has held true for every facet of the system, encompassing applications, resource management, the underlying computing infrastructure, and environmental cooling. Thus, the cloud-computing and dependability research communities have exerted considerable effort toward enhancing the reliability of system components against various software and hardware failures. However, as these systems have continued to grow in scale, with heterogeneity and complexity resulting in the manifestation of emergent behavior, so too have their respective failures. Recent studies of production cloud datacenters indicate the existence of complex failure manifestations that existing fault tolerance and recovery strategies are ill-equipped to effectively handle. These strategies can even be responsible for such failures. These emergent failures-frequently transient and identifiable only at runtime-represent a significant threat to designing reliable cloud systems. This article identifies the challenges of emergent failures in cloud datacenters at scale and their impact on system resource management, and discusses potential directions of further study for Internet of Things integration and holistic fault tolerance.
Serine integrase recombinational engineering (SIRE): A versatile toolbox for genome editing

Chromosomal integration of biosynthetic pathways for the biotechnological production of high‐value chemicals is a necessity to develop industrial strains with a high long‐term stability and a low production variability. However, the introduction of multiple transcription units into the microbial genome remains a difficult task. Despite recent advances, current methodologies are either laborious or efficiencies highly fluctuate depending on the length and the type of the construct. Here we present serine integrase recombinational engineering (SIRE), a novel methodology which combines the ease of recombinase‐mediated cassette exchange (RMCE) with the selectivity of orthogonal att sites of the PhiC31 integrase. As a proof of concept, this toolbox is developed for Escherichia coli. Using SIRE we were able to introduce a 10.3 kb biosynthetic gene cluster on different locations throughout the genome with an efficiency of 100% for the integrating step and without the need for selection markers on the knock‐in cassette. Next to integrating large fragments, the option for multitargeting, for deleting operons, as well as for performing in vivo assemblies further expand and proof the versatility of the SIRE toolbox for E. coli. Finally, the serine integrase PhiC31 was also applied in the yeast Saccharomyces cerevisiae as a marker recovery tool, indicating the potential and portability of this toolbox.
Relationship of Duration of Wait for Surgery and Postoperative Patient-Reported Outcomes for Hallux Valgus Surgery

Background: Little is known about the effect of delayed access to bunion correction (hallux valgus) surgery on patient-reported outcomes. The objective of this study was to measure the association between preoperative wait time for bunion correction surgery and postoperative patient-reported outcomes. Methods: This study prospectively recruited patients to complete preoperative patient-reported outcomes measuring depression, pain, and foot and ankle health, including the Patient Health Questionnaire–9 (PHQ-9); the pain intensity (P), interference with enjoyment (E) of life and general (G) instrument (ie, PEG); and the Foot and Ankle Outcome Score (FAOS), a condition-specific instrument. Patients complete the same patient-reported outcomes 6 months postoperatively. Regression models measured patient-reported outcomes as a function of wait time, adjusting for baseline health, age category, sex, comorbidities, and socioeconomic status. This study included 87 participants, a response rate of 53% among eligible patients. Results: Longer waits for bunion correction surgery, adjusting for other factors, were associated with smaller gains in health in 4 of the 5 domains of the FAOS. There was no relationship between postoperative depression and pain scores with duration of wait time, adjusting for patient characteristics. Conclusion: At the 6-month postoperative time point, prolonged preoperative wait times were detrimental to foot and ankle outcomes in 4 of the 5 domains of the foot and ankle–specific PRO. Policies for expediting access for symptomatic hallux valgus are warranted to mitigate poorer postoperative outcomes. Further study is required to understand if failure to improve is a permanent finding in the postoperative period. Level of Evidence: Level II, prospective comparative study.
Stacked K-Means Hashing Quantization for Nearest Neighbor Search

Nowadays, with such a huge amount of information available online, one key challenge is how to retrieve target data efficiently. A recent state-of-art solution, k-means hashing (KMH), codes data via a string of binary code obtained by iterative k-means clustering and binary code optimizing. To deal with high dimensional data, KMH divides the space into low-dimensional subspaces, places a hypercube in each subspace and finds its proper location by the mentioned optimizing process. However, the complexity of the optimization increases rapidly when the dimension of the hypercube increases. To address this issue, we propose an improved hashing method stacked k-means hashing (SKMH). The main idea is to increase the approximation by a coarse-to-fine multi-layer lower-dimensional cubes. With these kinds of lower-dimensional cubes, SKMH can achieve a similar approximation ability via a less optimizing time, compared with KMH method using higher-dimensional cubes. Extensive experiments have been conducted on two public databases, demonstrating the performance of our method by some common metrics in fast nearest neighbor search.
Relay-Races with Rigid Schedules

Multistage corporative-concurrent systems organized inside a corporation as conveyor, and outside of corporation as concurrent system, is considered. It is shown, that adequate abstraction for description of such a systems is the M-parallel semi-Markov process, which has a number of specific features due to rigid schedule of conveyor operation, based on the properties of degenerative distribution, which is used for description of time intervals between relay points. Recurrent method of M-parallel semi-Markov process evolution analysis, which accounts for the rigidity of schedule and possibility of three possible competition outcomes (win, lose, draw), is worked out. Using the concept of distributed forfeit and proposed recurrent procedure of rigid schedule relay-races analysis, the method of calculation of summing forfeit, which one of competing teams receives from other teams, is proposed. It is shown, that for a forfeit optimization the exact knowledge of schedules of all competitive teams is essential.
Conceiving Extrinsic Information Transfer Charts for Stochastic Low-Density Parity-Check Decoders

Stochastic low-density parity-check decoders (SLDPCs) have found favor recently both for correcting transmission errors as well as for improving the hardware efficiency. The main drawback of these decoders is that they require hundreds of time periods to decode each frame, but their chip area is smaller than that of their fixed-point counterparts, so they can achieve higher hardware efficiency and may consume less energy. In this paper, we propose a novel extrinsic information transfer chart technique for characterizing the iterative decoding convergence of all the sequences involved in the SLDPC. We have conceived a new model, which takes into consideration not only the sequences exchanged between the decoders but also the sequences generated inside the variable-node decoder (those which are stored in the edge memories). In this way, the model is able to predict the number of decoding iterations required for achieving iterative decoding convergence, as confirmed by own decoder simulations. The proposed technique offers new insights into the operation of SLDPCs, which will facilitate improved designs for the research community.
Development and Evaluation of Two Learning-Based Personalized Driver Models for Pure Pursuit Path-Tracking Behaviors

Establishing a personalized driver model to predict the driving behavior plays a significant role in the promotion of driver assistance system and automated driving system. In this paper, we propose two different learning-based pathtracking personalized driver models to predict the lookahead distance based on pure pursuit algorithm using the naturalistic driving data collected from BIT intelligent vehicle platform. Based on Gaussian Mixture Model (GMM), one stochastic driver model is the velocity-based Gaussian Mixture Regression (GMR) approach established by combining Gaussian classification process and Gaussian mixture regression, while another driver model is the general GMR approach. The predicting results obtained from the stochastic models are analyzed based on the numbers of GMM components. Statistical analyses show that both personalized driver models perform well, and the velocity-based GMR approach demonstrate higher accuracy than general GMR approach in predicting lookahead distance with the preferred number of the GMM components 10-12 and better performance in tracking the given path.
Automated Information System for Quality Control of Products Using Fractal Signs of Images

The analysis of the problem of visualization and digital processing of defectoscopic images is carried out in the automation of the tasks of non-destructive quality control of products. It is shown that improving the quality of products can be achieved by creating and implementing algorithms and methods for the digital processing and analysis of flaw detection information. The necessity of using new image analysis algorithms for the automated processing of defectoscopic images is shown. An automated subsystem for fractal processing and analysis of defectoscopic images has been developed, which implements the developed algorithms for fractal image analysis. The subsystem allows reducing the processing time of defectoscopic images of the metal surface by an average of 2–3 times in comparison with the analysis of the operator-defectoscopist.
Smart Urban Mobility: Conceptual analysis for proposal model

Increased concentration of people in large cities has been recorded since the 19th century. This leads cities to face an ever greater challenge in providing suitable management of the different resources and services necessary to attend their citizens. The development of the modern city with their huge amount of vehicles and saturation of people caused the development of even greater stress to cities population, with extreme stress conditions occurring with respect to urban mobility. In fact, the citizen finds the streets congested, insecure and overcrowded by a polluted environment (air, visual and noise pollution). For this reason it is necessary to study, develop and implement alternatives of managing mobility to improve the quality of life of people leaving in cities. This research focus on analyzing experiences from several cities that are reference in the subject of mobility in order to study evolution of mobility and describe a model, based on computational intelligence, for making analytic predictions on urban mobility.
The Role of Sustained Photoprotective Non-photochemical Quenching in Low Temperature and High Light Acclimation in the Bloom-Forming Arctic Diatom Thalassiosira gravida

Thalassiosira gravida is a major Arctic diatom responsible for the under-ice spring bloom. We investigated T. gravida physiological plasticity growing it at two temperatures (0°C and 5°C) and under different light intensities typically found in its natural environment. T. gravida showed remarkable thermal- and photo-acclimatory plasticity including: low light saturation parameter for growth (KE) and photosynthesis (EK), low μmax but relatively high Chl a/C, low C/N and decreasing light-saturated carbon fixation rate (PCm) with increasing growth irradiance. T. gravida also showed remarkable photoprotective features, namely a strong sustained non photochemical quenching (NPQs, hour kinetics relaxation) supported by a high amount of xanthophyll cycle pigments. T. gravida growth remained possible under a wide range of irradiances but photosynthetic plasticity was higher at moderately low light (up to ~50 µmol photon m-2 s-1), nevertheless corresponding to the mean in situ conditions under which it predominates, i.e. underneath the spring thin-ice punctuated with melting ponds. The potential role of NPQs in the photophysiological plasticity of T. gravida is discussed.
IoT-KEEPER: Securing IoT Communications in Edge Networks

The increased popularity of IoT devices have made them lucrative targets for attackers. Due to insecure product development practices, these devices are often vulnerable even to very trivial attacks and can be easily compromised. Due to the sheer number and heterogeneity of IoT devices, it is not possible to secure the IoT ecosystem using traditional endpoint and network security solutions. To address the challenges and requirements of securing IoT devices in edge networks, we present IoT-Keeper, which is a novel system capable of securing the network against any malicious activity, in real time. The proposed system uses a lightweight anomaly detection technique, to secure both device-to-device and device-to-infrastructure communications, while using limited resources available on the gateway. It uses unlabeled network data to distinguish between benign and malicious traffic patterns observed in the network. A detailed evaluation, done with real world testbed, shows that IoT-Keeper detects any device generating malicious traffic with high accuracy (0.982) and low false positive rate (0.01). The results demonstrate that IoT-Keeper is lightweight, responsive and can effectively handle complex D2D interactions without requiring explicit attack signatures or sophisticated hardware.
The Race to 5G Era; LTE and Wi-Fi

We are on the brink of a new era for the wireless telecommunications, an era that will change the way that business is done. The fifth generation (5G) systems will be the first realization in this new digital era where the various networks will be interconnected forming a unified system. With support for higher capacity as well as low-delay and machine-type communication services, the 5G networks will significantly improve performance over the current fourth generation (4G) systems and will also offer seamless connectivity to numerous devices by integrating different technologies, intelligence, and flexibility. In addition to ongoing 5G standardization activities and technologies under consideration in the Third Generation Partnership Project (3GPP), the Institute of Electrical and Electronic Engineers (IEEE)-based technologies operating on unlicensed bands, will also be an integral part of a 5G eco-system. Along with the 3GPP-based cellular technology, the IEEE standards and technologies are also evolving to keep pace with the user demands and new 5G services. In this paper, we provide an overview of the evolution of the cellular and Wi-Fi standards over the last decade with a particular focus on the Medium Access Control and Physical layers, and highlight the ongoing activities in both camps driven by the 5G requirements and use-cases.
Influence of the keratinized mucosa on the stability of peri‐implant tissues and brushing discomfort: A 4‐year follow‐up study

OBJECTIVE The purpose of the present prospective follow-up study was to evaluate the long-term influence of the peri-implant keratinized mucosa (KM) on marginal bone level (MBL), peri-implant tissues health, and brushing discomfort. MATERIAL AND METHODS Eighty patients were initially recruited during their maintenance visit from January to October 2013 and allocated in two groups according to KM width around implants: Wide Group (KM ≥ 2 mm) and Narrow Group (KM < 2 mm). In the four-year follow-up examination (T4), marginal bone level (MBL), modified plaque index (mPI), probing depth (PD), clinical attachment level (CAL), bleeding on probing (BoP), and brushing discomfort (BD) were reassessed and compared to the initial assessments (T0). Mann-Whitney, Wilcoxon signed-rank test, and a multilevel model were used for the statistical analysis. RESULTS Fifty-four patients with 202 implants returned at T4. Mean mPI (0.91 ± 0.60), BoP (0.67 ± 0.21), and BD (12.28 ± 17.59) were higher in the Narrow Group than in the Wide Group (0.54 ± 0.48, 0.56 ± 0.26, and 4.25 ± 8.39, respectively). Marginal bone loss was higher in the Narrow Group (0.26 ± 0.71) than in the Wide Group (0.06 ± 0.48). Multilevel analysis suggested that KM width and time in function had a statistically significant effect on MBL. CONCLUSIONS The findings of the present study indicate that KM width had an effect on MBL, plaque accumulation, tissue inflammation, and brushing discomfort over the studied period. Thus, the presence of a KM ≥ 2 mm around implants appears to have a protective effect on peri-implant tissues.
Enterprise Investments for Transition from Automation to Digitization

The paper considers the stages of information-and-technological development of an enterprise from automation to digitization. The task is set to determine the appropriate moment when an enterprise shall come to its activity digitization. An early or late transition threatens with the reduction of the enterprise efficiency achieved due to information technology use. The paper presents the policy of making an investment decision on transition from automation to digitization for an operating enterprise based on the investment efficiency assessment and the Gompertz distribution.
Technology-Facilitated Detection of Mild Cognitive Impairment: A Review

Early diagnosis and management of dementia require accurate detection of symptoms and incidents in the pre-dementia stage of mild cognitive impairment (MCI). With the recent development of smart sensing technologies and machine learning algorithms, researchers have started exploring the possibility of automatically detecting symptoms of MCI based on home activity distributions. In this paper, we provide a brief review of the current state of the art in this line of research. We first present an overview of clinical studies on MCI. We then describe various technologies that have been used to collect data regarding patients cognitive levels and behaviors, and methods used to detect patterns and the deviation from these patterns. We also highlight the limitations of the current research work and outline future research tasks, including the development of cheaper and easily portable solutions, as well as personalized tracking technologies.
Intracameral antibiotics for prophylaxis of postoperative endophthalmitis in Australia: a review

Postoperative endophthalmitis is a severe complication which may result in loss of vision. Intracameral antibiotics have been shown to reduce the risk of this complication and are extensively used worldwide, with vancomycin, cefuroxime and moxifloxacin most commonly used. Choices in Australia are currently limited to vancomycin and cefazolin, since cefuroxime and moxifloxacin are not available. Vancomycin has been safely and effectively used in our department for more than two decades. Recent publications have risen concerns regarding the association of haemorrhagic occlusive retinal vasculitis a potentially blinding complication with intracameral vancomycin. This concern has driven us to review the safety and efficacy of currently available antibiotics in the context of Australian practice.
Nanonewton Force Measurements Based on Electromagnetic Force Compensated Balances (EMFC)

This paper gives an overview of microbalances that measure forces in the range of nanonewton and their applications. A loading force produces a deflection of the balance that is compensated by an actuator. The current (electromagnetic) or voltage (electrostatic) that is necessary to equalize the balance is a measure for the applied force. The TV-Ilmenau achieved a force resolution of less than 1 nN with a system that is working according to the electromagnetic force compensating principle. The force resolution is dependent on the stiffness of the balance joints and on the resolution of the balance deflection measurement. In order to increase the force resolution, the TV- Ilmenau develops a new system with a lower stiffness and a higher resolution of the position sensor.