Miracle-dz/UniFAR-FTUs huggingface dataset:
Singular Conditional Autoregressive Wishart Model for Realized Covariance Matrices

Abstract Realized covariance matrices are often constructed under the assumption that richness of intra-day return data is greater than the portfolio size, resulting in nonsingular matrix measures. However, when for example the portfolio size is large, assets suffer from illiquidity issues, or market microstructure noise deters sampling on very high frequencies, this relation is not guaranteed. Under these common conditions, realized covariance matrices may obtain as singular by construction. Motivated by this situation, we introduce the Singular Conditional Autoregressive Wishart (SCAW) model to capture the temporal dynamics of time series of singular realized covariance matrices, extending the rich literature on econometric Wishart time series models to the singular case. This model is furthermore developed by covariance targeting adapted to matrices and a sector wise BEKK-specification, allowing excellent scalability to large and extremely large portfolio sizes. Finally, the model is estimated to a 20-year long time series containing 50 stocks and to a 10-year long time series containing 300 stocks, and evaluated using out-of-sample forecast accuracy. It outperforms the benchmark models with high statistical significance and the parsimonious specifications perform better than the baseline SCAW model, while using considerably less parameters.
Effectiveness of virtual reality as therapeutic complement in the rehabilitation of upper limbs in people with spinal cord injury

In the space of just a few years, the literature has advanced from articles which primarily described the potential benefits of using virtual reality technology, to articles that describe the development of actual working systems, testing of prototypes, and early clinical results with patients who have used some of these systems. A few findings appear to be solidly emerging from the virtual reality work to date, as they have appeared repeatedly in multiple studies by different research groups. These findings are that: (1) patients with disabilities appear capable of motor learning within virtual environments; (2) movements learned in VR by patients with disabilities transfer to real world equivalent motor tasks in most cases, and in some cases even generalize to other untrained tasks; and (3) in the few studies that have compared motor learning in real versus virtual environments, some advantage for virtual reality training has been found in the most cases. However, the published clinical studies, for the most part, still consist of small studies without control groups, or with small samples of patient. Furthermore, at present these devices are not considered a treatment in themselves, but only new technologies tools that can be exploited to enhance motor retraining. Much work remains to be done to identify which types of patients will benefit most from these treatments, which system features are critical, and what types of training routines will work best. This understanding will be the key to designing appropriate virtual reality system features and successful treatment interventions combination. The main objective of this thesis was to assess the efficacy of the application of virtual reality-based therapy, as rehabilitation complement to upper limbs function in people with tetraplegia. Furthermore, we wanted to verify the capacity of virtual reality systems to detect upper limbs kinematic and functional changes.
Impact of HRM practices on employee engagement and employee performance with special reference to academicians and work professionals

The purpose of this study is to explore the employee performance factors which are highly influenced by HRM practices through different dimensions. Moreover, this study proposes a model in the area of human resource practices to be used for testing and improving the performance of employees in the universities. An integrated model was developed highlighting the relationship between the HRM practice variables (Training, R&D, and Performance Appraisal) and employee performance. 281 responses have been collected from various academicians and work professional working in universities. Partial least square (PLS) – Structural equation modeling (SEM) is implemented using Smart PLS 3.0 to validate the hypothesized relationship by evaluating the responses of employees working in the universities. The findings of this study demonstrate a strong relationship between HRM practices and employee performance in the universities and also can be used by managers and HR professionals for organizing exclusive relevant programs for improving employee's performance based on the dimensions used in this paper. The present study provides an empirical and theoretical explanation of different dimensions associated with HRM Practices and employee performance.
Identification of lncRNAs expression and their regulatory networks associated with development and growth of skeletal muscle in sheep using RNA-Seq

Article Info Importance of the work : Sheep are a major source of mutton production. Therefore, recognizing the genes that influence muscle growth rates in sheep is useful in breeding programs. Objectives : To identify the genes regulated by long non-coding RNAs (lncRNAs) that are effective in sheep skeletal muscle growth and development. Materials & Methods : In total, 141,079,400 short reads for 12 muscle tissue (longissimus dorsal) samples of 6 young animals and 6 adults from domestic sheep were used as input for the FastQC and Trimmomatic software packages. Expression analysis was investigated using Cuffdiff. The ClueGO plug-in in Cytoscape was used for gene ontology. Novel lncRNAs were distinguished using Cuffcompare. Results : Of the 82 lncRNA genes, 15 genes were up-regulated and 67 genes were down-regulated in adults compared with young animals and there was a higher expression of the lncRNA genes in the young than in the adult individuals based on cluster analysis. There were 26 genes of Gene Ontology classified as Biological Processes that significantly enriched the regulation of muscle development and differentiation. The findings showed that lncRNAs regulated both miRNAs and mRNAs that chiefly participate in the muscle growth and development in Texel sheep. lncRNA transcripts correlation other novel lncRNA transcripts, TCONS_00033645, correlation with miRNAs. Main finding : New candidate regulator genes were identified for future molecular and genetic studies on sheep muscle growth and development. This might be helpful in selection programs to improve mutton production.
Integration of Deep Learning and Active Shape Models for More Accurate Prostate Segmentation in 3D MR Images

Magnetic resonance imaging (MRI) has a growing role in the clinical workup of prostate cancer. However, manual three-dimensional (3D) segmentation of the prostate is a laborious and time-consuming task. In this scenario, the use of automated algorithms for prostate segmentation allows us to bypass the huge workload of physicians. In this work, we propose a fully automated hybrid approach for prostate gland segmentation in MR images using an initial segmentation of prostate volumes using a custom-made 3D deep network (VNet-T2), followed by refinement using an Active Shape Model (ASM). While the deep network focuses on three-dimensional spatial coherence of the shape, the ASM relies on local image information and this joint effort allows for improved segmentation of the organ contours. Our method is developed and tested on a dataset composed of T2-weighted (T2w) MRI prostatic volumes of 60 male patients. In the test set, the proposed method shows excellent segmentation performance, achieving a mean dice score and Hausdorff distance of 0.851 and 7.55 mm, respectively. In the future, this algorithm could serve as an enabling technology for the development of computer-aided systems for prostate cancer characterization in MR imaging.
Using Natural Language Processing to Identify Effective Influencers

Identifying the right influencers for brands is often the starting point for a successful influencer campaign. However, influencer identification is understudied, and most previous studies have only discussed visible characteristics of influencers and their social networks, overlooking content-based metrics. Combining interdisciplinary theories and techniques from marketing, linguistics, and computer science, we propose a data-driven automated text analysis framework to identify characteristics of effective influencers using influencer posts. Specifically, we propose a model that incorporates influencer personality traits captured by natural language processing, accounting for traditional covariates, such as network structure and follower engagement. In addition, we use a dataset that attributes influencer social media activities to customer purchases to address fake engagement and showcase our automated textual analysis. The proposed framework can help marketers develop influencer profiles and predict optimal influencers for their campaigns.
SISTEM INFORMASI E-LEARNING Di SEKOLAH

The learning process is generally carried out directly, but now can be done without a process-face in directly between teachers and students, because now online learning has become a trend at schools, now a national exam using the online system. Development of an e-learning information system created using the waterfall method is to analyze the needs of the system, creation of information systems, to testing. after going through the circuit produced an e-learning information system that can facilitate the learning process between teachers and students online
Temperature-aware computing

In the future, the peak temperature of a chip will be a primary design constraint. Higher temperatures can accelerate various chip failure mechanisms, reducing the lifetime of the system. These high temperatures also place additional burden on cooling systems, which must prevent thermal runaways due to increased standby power consumption. Consequently, temperature must be considered in the earliest phases of the design process. Many existing thermal management techniques focus on reducing the overall power consumption of the chip by throttling performance, eventually resulting in an overall reduction in chip temperature. These techniques, while effective, often do not address location-specific temperature problems referred to as hotspots. Recent research into hotspots has shown that different functional units in general purpose processors can have significantly different temperature profiles, and that moving workloads between units can reduce the creation of hotspots on the die. Using a newly developed thermal analysis tool, HS3d, this work explores the thermal profile of modern processor architectures, and discusses the types and characteristics of hotspots in future technologies, as process variation, multi-core design, and multi-wafer stacking techniques become prevalent. Means of mitigating these hotspots are presented, including workload migration for homogenous architectures, and means of reducing hotspots near the integer ALU. One proposed method, integer offloading to floating-point, redirects integer operations to the floating-point hardware, slightly increasing latency and power consumption, but distributing heat more evenly across the die. Finally, a model of the impact of temperature on circuit timing is presented, and the impact of temperature gradients on multi-core processors is explored, showing that by the 45nm technology node, thermally-induced timing variations of 5% per 10°C are possible. Traditional worst-case design techniques, which assume a single high temperature for the entire device, can therefore not take full advantage of the much more common typical-case conditions. This thesis discusses how thermal-aware design can be incorporated into the automated design flow, allowing variable frequency systems to achieve maximal performance across a wide operating range.
Comparing Digital Therapeutic Intervention with an Intensive Obesity Management Program: Randomized Controlled Trial

In this study, we evaluated whether the digital program Vitadio achieves comparable results to those of an intensive in-person lifestyle intervention in obesity management. This is a 12-month prospective, randomized controlled trial. Obese patients with insulin resistance, prediabetes or type 2 diabetes were included. The intervention group (IG) used Vitadio. The control group (CG) received a series of in-person consultations. Body weight and various metabolic parameters were observed and analyzed with ANOVA. The trial is ongoing and the presented findings are preliminary. Among 100 participants (29% men; mean age, 43 years; mean BMI, 40.1 kg/m2), 78 completed 3-month follow-up, and 51 have completed the 6-month follow-up so far. Participants significantly (p < 0.01) reduced body weight at 3 months (IG: −5.9 ± 5.0%; CG: −4.2 ± 5.0%) and 6 months (IG: −6.6±6.1%; CG: −7.1 ± 7.1%), and the difference between groups was not significant. The IG achieved favorable change in body composition; significant improvement in TAG (−0.6 ± 0.9 mmol/l, p < 0.01), HDL (0.1 ± 0.1%, p < 0.05), HbA1c (−0.2 ± 0.5%, p < 0.05) and FG (−0.5 ± 1.5 mmol/l, p < 0.05); and a superior (p = 0.02) HOMA-IR reduction (−2.5 ± 5.2, p < 0.01). The digital intervention achieved comparable results to those of the intensive obesity management program. The results suggest that Vitadio is an effective tool for supporting patients in obesity management and diabetes prevention.
Investigation of Lightning-Initiated Flashover Faults in Medium Voltage Overhead Lines - Modelling and Experimental Evaluation

lightning activity is one of the main causes of interruptions and voltage sags on overhead distribution networks. A reliable operation of the distribution network can be ensured by properly coordinating the electric strength of insulation system with the expected overvoltage stress. This thesis investigates the stress caused by lightning overvoltages, which consequently results in the flashover of line insulation. Accordingly, the characteristics of lightning-initiated flashover faults have been studied so that more elaborate models that describe the flashover phenomena could be proposed. Particularly, the significant contribution of this work is to predict the occurrence probability of the single-phase and multiphase flashover faults. Finally, appropriate measures for the effective reduction of the flashover faults in medium voltage lines are proposed with special emphasis on multiphase flashovers as they have a detrimental effect on the quality of electricity delivered to the consumers. A ato-D D 7 0 /2 16
Irrigating urban green space for cooling benefits: the mechanisms and management considerations

Evapotranspiration is an important cooling mechanism in urban green space (UGS). Irrigating vegetated surfaces with potable water, collected stormwater or recycled sewage water has the potential to increase the cooling effect of UGS by increasing evapotranspiration. Such cooling effect may not always be strong because evapotranspiration is dependent on local and regional factors such as background climate, seasonality and vegetation type. When using irrigation for cooling, city managers also need to consider management issues such as irrigation water supply and amenity use of the UGS. This study aims to develop a theoretical framework that explains the physical and energetic mechanisms of irrigation cooling effect and a framework to assist city managers to make decision about the use of irrigation for urban cooling. This is achieved by reviewing the impacts of irrigation on local climate reported in the literature and identifying the regional and local factors that influence irrigation cooling effect in warm seasons. The literature suggests that irrigation can potentially reduce daily maximum air temperature and ground surface temperature by approximately 2.5 °C and 4.9 °C, respectively, depending on weather conditions and irrigation amount. Background climate is an important factor that influences the cooling potentials of irrigation. Cities with dry and warm climates have the highest cooling potentials from irrigation. The cooling potentials are also influenced by seasonality and weather, vegetation type, irrigation time of day and irrigation amount. Cities with a dry and warm season can consider using irrigation to mitigate urban heat within UGS because such climatic conditions can increase cooling potentials. To maximise irrigation cooling effect, cities with abundant irrigation water supply can use a soil moisture-controlled irrigation regime while those with limited supply can use a temperature-controlled regime. More studies are required to understand the cooling potentials of irrigating small, individual UGS.
Using Direct Assessment to Resolve TAC/ABET Criterion 3 Program Outcomes

The focus of the assessment process was on developing and administering reliable and valid direct methods to assess student outcomes. The direct methods of assessment, based on the list of direct measures recognized at the 2008 TAC Commission Summit, developed by the Computer Engineering Technology (CET) faculty included tests, constructed with a test blueprint, and performance appraisals with scoring rubrics. These direct assessment measures provided evidence of student learning which subsequently guides faculty in identifying its program weaknesses. Furthermore, CET faculty found the interpretation of the data much easier with these measures of assessment. The assessment process developed for the program not only included the traditional summative approach, but also included formative assessment within the overall Continuous Quality Improvement (CQI) model. The inclusion of formative assessment within the overall CQI model provides an opportunity for early intervention for program-level attrition. Specifically, this paper provides information regarding assessment planning, the assessment process, the development of assessment instruments, and the challenges encountered by the department and should provide information that will benefit other engineering and engineering technology programs seeking accreditation or re-accreditation.
An Experimental Study on the Effectiveness of Students’ Learning in Scientific Courses through Constructive Alignment—A Case Study from an MIS Course

This study aimed to explore students’ effectiveness in scientific courses that have adopted the framework of constructive alignment. The researchers conducted an experimental study in the education sector to compare two different teaching models—traditional and following constructive alignment—and used statistical tools to analyse differences in students’ learning effectiveness. The course “Management Information System” (MIS) was specifically chosen to investigate how constructive alignment initiatives used in the course influenced students’ learning effectiveness. Two groups of students were selected as the control group and the experimental group, respectively. In the experimental group, the intended learning outcomes, teaching and learning activities, and assessment tasks were always aligned by the instructor. The learning effectiveness of the two groups was evaluated by the Course Experience Questionnaire Survey and academic grades. After this study, it was found that significant improvement—in terms of students’ learning experience scores and academic grades—was seen in the experimental group compared with the control group. This study has further verified that implementing a constructive alignment template can significantly improve students’ learning effectiveness in scientific courses, hence providing theoretical and practical references for teaching and learning in scientific courses.
Modelling and evaluation of wind speed time series for reliability analysis of offshore wind farms.

This paper outlines proposed testing criteria for wind speed time series (WSTS) models. The objective is to assess their suitability for reliability analysis that is dependent on an accurate representation of weather patterns. Two WSTS models were analysed for their suitability against these criteria. The Markov model was found to be suitable for resource assessment, but would require modification before it could represent weather patterns, whilst the random sampling model could represent weather patterns more accurately, but could not be used for resource assessment.
Influence of Overall Equipment Effectiveness on Print Quality, Delivery and Cost: A System Dynamics Approach

The success of the printing industry will depends on the printing equipment performance, which can result in cost-effective process. Today equipment maintenance is considered as an essential function, even in printing industry. Hence the purpose of this paper is to propose a System Dynamic model for analysing the influence of Overall Equipment Effectiveness (TPM) on delivery, cost and quality of the printed product and thus also prove that TPM is a strategy and not a cost centre. Methodology-In this research System Dynamic methodology is used in which a causal loop diagram is constructed for Total Productive Maintenance and then the stock and flow diagram is developed. Findings-The SD model represented in this paper revel the influence of Total Production Management on required printing performance like: cost, delivery and quality. Research limitations-It is also found that the blend of TQM, JIT and TPM can reflect in reliable manufacturing practice, which is having the ability to produce efficient production. Hence, the present model can include the variables related to TQM and JIT. Practical implications-The practical implication concern the efficient decision making system in multi-colour sheet feed offset printing, regarding the maintenance plan and production parameters.
Identification and Clarification of VrCYCA1: A Key Genic Male Sterility-Related Gene in Mungbean by Multi-Omics Analysis

Heterosis has been utilized in crops for a long time, and although crop fertility is the basis for the utilization of heterosis, there is limited information concerning the genic male sterility (GMS) of mungbean. Therefore, based on the genic male sterile mutant, M1, obtained by EMS mutagenesis of the Weilyu cultivar, this project used multi-omics analysis to detect the male sterile site and further identify its candidate gene, and then the mechanism of the candidate gene was discussed. As a result, one locus region (Chr5: 6,835,001–6,935,000 bp) associated with GMS was identified, and nine genes were found within the 100 Kb region. The candidate gene, VrCYCA1, around the above loci had a TATA box deletion approximately 4.7 Kb upstream of the gene, and this was evidenced by comparative genomics, transcriptome analysis, and RT-qPCR analysis. The expression level of VrCYCA1 was significantly downregulated (log2FC = −2.06, p-value = 0.025) in the ms lines compared with the control group. Moreover, 6653 genes showed differential expression between the Weilyu lines and mutant lines as well as 165 metabolites with significant differences in their concentration levels. Among those differentially expresses genes, 226 were annotated with functional categories involved in flowering and endosperm development, and six genes had protein–protein interactions with VrCYCA1. Seven categories of metabolites and seven genes participated in the relationship between reproductive growth and vegetative growth, which might have caused the sterility of mungbean in the mutant plants. This study used multi-omics data to mine a mungbean GMS-related gene, VrCYCA1, and constructed a GMS genetic network to explore the molecular mechanism of VrCYCA1. The results lay a solid foundation for further molecular biology research and utilization in mungbean male sterility.