Miracle-dz/UniFAR-FTUs huggingface dataset:
Findings from The Marketing Theatre Approach in an MBA Programme

An approach to teaching marketing theory and skills was developed in the MBA programme at the University of Canterbury. The Marketing Theatre Approach was created and implemented in 2008 as a collaborative effort among a marketing lecturer, a higher education lecturer, and two actor-facilitators from a local theatre company. The marketing instructor asked the actors to deliver two improvisational sessions in order to have students learn marketing objectives through experiential means. Data was collected from students’ openended responses to questions before and after the sessions and from observations during and after the sessions. The findings suggest that students’ experiences aligned with the intended objectives and also provided specific ways in which to improve the approach for its next iteration.
Recognition of Fetal Facial Expressions Using Artificial Intelligence Deep Learning

Fetal facial expressions are useful parameters for assessing brain function and development in the latter half of pregnancy. Previous investigations have studied subjective assessment of fetal facial expressions using four-dimensional ultrasound. Artificial intelligence (AI) can enable the objective assessment of fetal facial expressions. Artificial intelligence recognition of fetal facial expressions may open the door to the new scientific field, such as “AI science of fetal brain”, and fetal neurobehavioral science using AI is at the dawn of a new era. Our knowledge of fetal neurobehavior and neurodevelopment will be advanced through AI recognition of fetal facial expressions. Artificial intelligence may be an important modality in current and future research on fetal facial expressions and may assist in the evaluation of fetal brain function.
The Effects of Social Stigma on Smartphone Addiction of Out-of-School Adolescents: Serial Multiple Mediating Effects of Self-Esteem and Depression

본 연구에서는 학교 밖 청소년의 사회적 낙인감과 스마트폰 중독의 관계에서 자아존중감과 우울의 연속다중매개효과를 살펴보았다. 이를 위해 한국청소년정책연구원에서 제공하는 ‘학업중단청소년패널조사’ 2차년도 조사(2014)의 청소년 데이터를 활용하여 분석하 였다. 연구결과, 첫째, 사회적 낙인감은 스마트폰 중독에 정적으로 유의한 영향을 미치는 것으로 나타났다. 둘째, 사회적 낙인감과 스 마트폰 중독의 관계를 자아존중감이 매개하지 않는 것으로 나타났다. 셋째, 사회적 낙인감과 스마트폰 중독의 관계를 우울이 매개하 는 것으로 나타났다. 넷째, 사회적 낙인감과 스마트폰 중독의 관계를 자아존중감과 우울이 연속적으로 다중매개하는 것으로 나타났 다. 본 연구결과를 토대로 하여 학교 밖 청소년의 스마트폰 중독의 대처와 예방에 있어서 사회적 낙인감, 자아존중감, 우울 등에 대한 사회적 대책을 모색하고 논의하였다. 또한 본 연구결과가 가진 함의 및 한계점을 살펴보고, 후속연구에 대해 제언하였다. This study examined the mediating effects of self-esteem and depression on the relationship between social stigma and smartphone addiction of out-of-school adolescents. To this end, we analyzed adolescents data from the second year (2014) of the ‘Drop out Youth Panel Survey’ provided by the National Youth Policy Institute. As a result of the study, first, social stigma was found to have a significant and positive effect on smartphone addiction. Second, it was found that self-esteem did not mediate the relationship between social stigma and smartphone addiction. Third, it was found that depression mediates the relationship between social stigma and smartphone addiction. Fourth, it was found that self-esteem and depression sequentially multiple mediate the relationship between social stigma and smartphone addiction. Based on the results of this study, social countermeasures for social stigma, self-esteem, and depression were sought and discussed in coping and prevention of smartphone addiction of out-of-school adolescents. In addition, the implications and limitations of the results of this study were reviewed, and research that needs to be followed was suggested.
An Attention-Based Model for Travel Energy Consumption of Electric Vehicle with Traffic Information

Mileage anxiety is one of the most important factors that affect the driving experience due to the limitation of battery capacity. Robust and accurate prediction of the energy consumption of the journey of the electric vehicle can guide the driver to allocate the power rationally and relieve the anxiety of the mileage. Since vehicle sharing is the biggest application scenario of electric vehicles, it is a critical challenge in share mobility research area. In this paper, a travel energy consumption prediction model of electric vehicles is proposed in order to improve the mobility of shared cars and reduce the anxiety of drivers because they are worried about insufficient power. A recurrent neural network with attention mechanism and deep neural network is used to build the model. To validate the proposed model, a simulation is demonstrated based on both traffic and vehicle information. After the simulation, experimental results show that the proposed model has high prediction accuracy, and we also show through visualization how the model finds high relevant road segments of the road network while dealing with corresponding traffic state input.
From Data to Wisdom: A Case Study of OPOP Model

The purpose of this research is to: (1) clarify the scope and connotation of the OPOP (One Product/Project/Performance, One Paper) model comprehensively; (2) show its application in design and creative teaching; (3) introduce this model to more people. First, the author reviews the design doctoral education system and its shortcomings and analyzes the similarities and differences between “Ph.D. of Design” and “Master of Design”; second, the researcher discusses the DIKW (Data, Information, Knowledge, Wisdom) pyramid, cognition and communication theory separately. The author also interviewed the two teachers who created the OPOP model to clarify its core meaning and goals. Finally, the author invited students who participated in an OPOP forum to fill out a questionnaire in order to analyze and understand their responses and suggestions. The OPOP model allows participants to realize that “creativity” and “interpretation” are equally important and to gradually learn to use academic papers to transform personal “tips” and “experience” into “knowledge” that can be imparted. The author hopes that the OPOP model and the general frameworks mentioned in this study can inspire all readers, enabling them to continuously explore the connotation and further possibilities of OPOP in light of the actual situation.
Decentralized load frequency based on H∞ control

This paper presents a decentralized load frequency control (LFC) based on H∞ optimal control theory with an observer. A few LFC schemes have been proposed based on the optimal control theory, but they have not considered the change of system parameters in operation and the characteristics of load disturbances in a target system. In this paper, H∞ robust control is introduced to address such problems. Owing to its practical merit, the proposed control scheme is a decentralized LFC. Employing observer theory, the proposed method requires only frequency and tie‐line power deviation in each area. Numerical simulations are shown to demonstrate the effectiveness of the proposed method. H∞ control was proven to show greater effectiveness of damping disturbance over the conventional optimal control by the design of control systems aimed at restricting the H∞ norm of its transfer function. In particular, when a decentralized LFC is applied, by reducing the system size, H∞ norm is easier to dampen; thus H∞ control is more effective in the decentralized control. Future research topics include the design of H∞ control system with a weight on frequency response. © 2001 Scripta Technica, Electr Eng Jpn, 136(3): 28–38, 2001
Oscillator-based walking assistance: Optimization & validation Part I: Optimization by simulations

In this paper, a control strategy for a lower extremity exoskeleton is developed to provide intuitive support during steady-state human walking using simulations and optimizations. This support should be user specic, compliant, robust to sensor noise and should not disturb the users’ gait. The oscillator-based controller can give such a support under the assumption that the joint movements are cyclic. The basic elements of the oscillator-based control strategy are adaptive oscillators, which learn and estimate periodic angle and velocity trajectories during walking. After learning, the trajectories are known in advance and can function as an attractor for the current angle respectively velocity. The phase shift of the reference trajectories is time variable and optimized. In addition, the stiness and damping trajectories for the impedance control are optimized, all in a one-stage optimization minimizing the stiness and the power to nd a minimal disturbed gait. The simulation results show that the hip and knee joint angle trajectories and the ankle joint torque in simulations are similar to recorded human data. The optimization algorithm nds the same reference angles over multiple optimization runs. The stiness of the controller can vary in one gait cycle between two values and the optimization retrieves a separation between swing and stance phase without explicit prior knowledge. This research improves on previous work because it optimized the control parameters of the oscillatorbased controller, support is applied to the hip, knee and ankle joints and the support can be linear scaled. The performance of the designed control strategy is validated on humans in part II of this paper.
Design of a sinusoidal current source using a sliding-mode-controlled asymmetrical full-bridge multilevel converter

An analysis and design of an asymmetrical full-bridge multilevel converter in sliding-mode operation for inverter applications in small power systems are presented. A five-level sinusoidal current source inverter is proposed with the lowest number of controllable devices and the simplest control electronics. The current source nature of the inverter is achieved by means of a sliding-mode control loop forcing the inverter output current to track a sinusoidal reference. The theoretical predictions have been verified by experiments in a 1 kW prototype in both stand-alone and grid connection operations.
Addressing the Dilemmas of Long-Term Mining Impacts Using a Framework of Sustainability and Adaptive Management

Many operating hard-rock sulfide mines are predicted to require perpetual post-closure management to prevent environmental degradation. Causes include evaporative concentration of metals and other solutes in pit lakes, and acid rock drainage from sulfide waste-rock, tailings, and pit benches. Dilemmas posed by the prospect of perpetual management include: 1. uncertainty in predictive models typically prevents reliable bounding on forecasts for the timing or magnitude of environmental impacts; 2. comprehensive closure designs that can meet environmental standards may not be economically possible, particularly when applied retroactively to mines permitted under less stringent closure requirements; 3. the publication of site-specific environmental analyses in peer-reviewed journals are discouraged in the current regulatory environment, hindering scientific advancement; and 4. the durability of financial and government institutions cannot be assured for the long-time horizons over which mine impacts are predicted to occur. Re-evaluating mine closure in a framework of sustainable development (as proposed by the Mining Mineral Sustainable Development forum), can resolve, in part, these dilemmas. Key sustainability goals include: assurance of the social and economic well-being of the local community; assurance of the long-term environmental integrity of the region; and establishment of institutions capable of addressing (and learning from) long-term environmental management. Under a sustainability framework, impractical plans for immediate attainment of perpetually-stable closure may be replaced with a fund for long-term management of environmental impacts (eg through contaminant migration controls and exposure barriers), and a set-aside long-term growth reserve intended to eventually fund more complete closure. Fund expenditures would follow Adaptive Management—a template for environmental-management institutions in which knowledge accumulated and uncertainty acknowledged explicitly. Under adaptive management, trusts would be flexible entities, supporting an evolving program of monitoring, predictive model refinement, and treatment. Periodic value of information analyses would target data collection efforts, refining the balance between predictable cost and uncertainty. This framework could overcome present-day financial shortcomings, enhance the field of environmental science, and meet the needs of future generations through the propagation of capita.
Design of Beam-Columns Using Artificial Neural Networks

In this paper, manual design of beam-columns, based on the procedure adopted by american society of steel construction, is described. an attempt has been taken to apply artificial neural network to the design of steel beam-columns of hot-rolled shapes. for this purpose, a set of data have been generated using the software package staad pro, and then used in training and testing the neural network. the results showed that artificial neural network after successful learning could specify the proper sections with relatively high accuracy.
Study of Cardiovascular Parameters and Heart Rate Variability (Frequency Domain Analysis) in 1St Trimester of Normal Pregnant Women and Pregnant Women with Risk Factors for PIH in Western Rajasthan

Background: The role of sympathovagal imbalance (SVI) and CV risk in pregnancy-inducedhypertension (PIH) has been reported, and their association during early trimesters of gestation in PIHhas not been studied. Therefore, in the present study, we have investigated the maternal cardiovascularparameters and frequency domain indices of Heart rate variability (HRV) between normal pregnantwomen and women with risk factors for PIH in their 1st trimester of gestation.Methods: Two hundred twenty subjects each (220 of normotensive pregnant women i.e., control groupand 220 of pregnant women with risk factor for PIH i.e., study group) of 1st trimester of gestation wererecruited from the obstetrics & gynecology department of Umaid hospital, associated with Dr. S. N.Medical College, Jodhpur, Rajasthan. Physical examination was done and anthropometric measurementlike height & weight were taken. The collected data was statistically analyzed using HRV analysissoftware.Results: Significant difference in body mass index was observed between the two groups. Systolic bloodpressure, Diastolic blood pressure, Pulse pressure, Rate pressure product and Mean arterial pressure ofstudy group was significantly higher than control group. Values of LF and LF/HF ratio components offrequency domain analysis of HRV were significantly increased but HF component is non significantlydecrease in 1st trimester of the pregnant women with risk factor for PIH than normal pregnant women.Conclusion: The present study indicates that the cardiovascular parameters in 1st trimester of pregnantwomen with risk factor for PIH were increased highly significantly than the normal pregnant women.The highly significant (HS) (p<0.000) increase in the LF (nu) & LF/HF ratio and non significant (NS)(p<0.552) decrease in HF (nu) of pregnant women with risk factors for PIH was observed than normalpregnant women this indicate that sympathetic tone was increased in 1st trimester of pregnant womenwith risk factor for PIH. Vagal withdrawal and sympathetic exaggeration may be the possible cause ofPIH in pregnant women with its risk factors.
An Evolutionary Based Strategy for Predicting Rational Mutations in G Protein-Coupled Receptors

Capturing conserved patterns in genes and proteins is important for inferring phenotype prediction and evolutionary analysis. The study is focused on the conserved patterns of the G protein-coupled receptors, an important superfamily of receptors. Olfactory receptors represent more than 2% of our genome and constitute the largest family of G protein-coupled receptors, a key class of drug targets. As no crystallographic structures are available, mechanistic studies rely on the use of molecular dynamic modelling combined with site-directed mutagenesis data. In this paper, we hypothesized that human-mouse orthologs coding for G protein-coupled receptors maintain, at speciation events, shared compositional structures independent, to some extent, of their percent identity as reveals a method based in the categorization of nucleotide triplets by their gross composition. The data support the consistency of the hypothesis, showing in ortholog G protein-coupled receptors the presence of emergent shared compositional structures preserved at speciation events. An extreme bias in synonymous codon usage is observed in both the conserved and non-conserved regions of many of these receptors that could be potentially relevant in codon optimization studies. The analysis of their compositional structures would help to design new evolutionary based strategies for rational mutations that would aid to understand the characteristics of individual G protein-coupled receptors, their subfamilies and the role in many physiological and pathological processes, supplying new possible drug targets.
WDM knockout switch with multi-output-port wavelength-channel selectors

This paper proposes the photonic knockout switch that uses wavelength division multiplexing (WDM). The proposed switch uses two types of WDM switching: broadcast-and-select (B and S) switching and wavelength routing. To extend the size of the knockout switch concentrator, a multi-output-port wavelength-channel selector is used, which enables us to reduce the number of optical gates and wavelength routers. Simple and distributed contention control becomes possible in the optical domain through the use of the wavelength-routing switch. In this switch, coherent crosstalk is a serious problem. We measured the bit error rates of a four-output-port wavelength-channel selector. The power penalty due to the presence of coherent crosstalk is less than 1 dB.
The effect of (NH4)2SO4 on the freezing properties of non-mineral dust ice nucleating substances of atmospheric relevance

Abstract. A wide range of materials including mineral dust, soil dust, and bioaerosols have been shown to act as ice nuclei in the atmosphere. During atmospheric transport, these materials can become coated with inorganic and organic solutes which may impact their ability to nucleate ice. While a number of studies have investigated the impact of solutes at low concentrations on ice nucleation by mineral dusts, very few studies have examined their impact on non-mineral dust ice nuclei. We studied the effect of dilute (NH4)2SO4 solutions on immersion freezing of a variety of non-mineral dust ice nucleating substances including bacteria, fungi, sea ice diatom exudates, sea surface microlayer, and humic substances using the droplet freezing technique. We also studied the effect of (NH4)2SO4 on immersion freezing of mineral dust particles for comparison purposes. (NH4)2SO4 had no effect on the median freezing temperature of nine of the ten tested non-mineral dust materials. There was a small but statistically significant decrease in the median freezing temperature of the bacteria X. campestris (change in median freezing temperature ∆T_50 = -0.43 ± 0.19 °C) in the presence of (NH4)2SO4 compared to pure water. Conversely, (NH4)2SO4 increased the median freezing temperature of four different mineral dusts (Potassium-rich feldspar, Arizona Test Dust, Kaolinite, Montmorillonite) by 3 °C to 8 °C. This significant difference in the response of mineral dust and non-mineral dust ice nucleating substances when exposed to (NH4)2SO4 suggests that they nucleate ice and/or interact with (NH4)2SO4 via different mechanisms. This difference suggests that the relative importance of mineral dust to non-mineral dust particles for ice nucleation in mixed-phase clouds could increase as these particles become coated with ammonium sulfate in the atmosphere. This difference also suggests that the addition of (NH4)2SO4 to atmospheric samples of unknown composition could be used as an indicator or assay for the presence of mineral dust ice nuclei.
Layer-4 Load Balancer for Flow Size Prediction with TCP/UDP Separation Using P4

Nowadays, datacenters become more complicated and handle many more users’ requests. Custom protocols are becoming more demanded, and an advanced load balancer to distribute the requests among servers is essential to serve the users quickly and efficiently. P4 introduced a new way to manipulate all packet headers. Therefore, by making use of the P4 ability to decapsulate the transport layer header, a new algorithm of load balancing is proposed. The algorithm has three main parts. First, a TCP/UDP separation is used to separate the flows based on the network layer information about the used protocol in the transport layer. Second, a flow size prediction technique is adopted, which relies on the service port number of the transport layer. Lastly, a probing system is considered to detect and solve the failure of the link and server. The proposed load balancer enhances response time of both resources usage and packet processing of the datacenter. Also, our load balancer improves link failure detection by developing a custom probing protocol.
A Case of CD5-Positive Primary Cutaneous Diffuse Large B-Cell Lymphoma, Leg Type Secondary to Chronic Lymphedema

Abstract: Primary cutaneous lymphoma occurring at the site of lymphedema is a rare complication. A total of 13 cases of primary cutaneous lymphoma associated with chronic lymphedema have been reported in international studies. We reported a case of cutaneous diffuse large B-cell lymphoma (DLBCL) (leg type) secondary to chronic lymphedema of the lower limbs. Histopathology showed hyperkeratosis of epidermis, acanthosis, and significant edema in the superficial dermis, with diffuse mononuclear infiltration in the dermis. Immunohistochemical studies revealed the expression of CD5, CD20, Pax-5, Bcl-2, Bcl-6, MUM-1, c-myc, and Ki-67. Therefore, the diagnosis of cutaneous DLBCL (leg type) was made. The study further confirmed the association between lymphoma and lymphedema. Especially, it showed CD5 expression. CD5-positive DLBCLs is a specific subgroup of DLBCLs, only approximately 10% of DLBCLs express CD5.
And…Action! Setting the Scene for Accurate Visual CFD Comparisons Using Ray Tracing

Increased graphical capabilities of contemporary computer hardware make ray tracing possible for a much wider range of applications. In science, and numerical fluid mechanics in particular, visual inspections still play a key role in both understanding flows, predicted by computational fluid dynamics, exhibiting features observable in real-life, such as interfaces or smoke, and when comparing such flows against experimental observations. Usually, little attention is paid to the visualisation itself, unless when the render is used solely for its eye-catching appearance. In this work, we argue that the use of ray tracing software can help make comparisons between computational and experimental fluid dynamics more robust and meaningful, and that, in some cases, it is even a necessity. Several visualisation problems which can be overcome through application of this methodology are discussed, and the use of ray tracing is exemplified for several common test cases in the maritime field. Using these examples the benefits of ray tracing are shown, and it is concluded that ray tracing can improve the reliability of scientific visual comparisons.
Design of slotless-type PMLSM for high power density using divided PM

A slotless permanent magnet linear synchronous motor (PMLSM) has a low power density due to having a large air-gap structurally. In this paper, an increase of power density of the slotless-type PMLSM is presented by inserting the core between each phase windings. The permanent magnet (PM) is divided into two pieces to reduce detent force and eliminate high-order space harmonics affecting the thrust ripples. All analysis values are calculated with two-dimensional finite-element method.