Miracle-dz/UniFAR-FTUs huggingface dataset:
Biomarker Geochemical Evaluation of Organic Rich Shales in Mamfe Basin, Cameroon

The Mamfe Basin is an intra-continental basin in southwestern Cameroon. Shale from Cretaceous strata in the Mamfe Formation has been poorly characterized in terms of their palaeo-environmental conditions and origin of the organic matter. Also, the thermal maturity of the shale has not been well established. The aim of this study is to determine the origin of the organic matter, evaluate the thermal maturity, palaeo-environmental conditions, and thereby deduce their hydrocarbon generative potential. Biomarker geochemical analyses was carried out on the organic matter extracts of some selected shale samples from Mamfe Formation having total organic carbon content ranging from 0.69 and 4.50 wt. % (av. =1.82 wt. %). Base on the total organic carbon content, the shales are described to have good hydrocarbon generative potentials. Thermal maturity parameters base on 20S/(20S +20R), and ββ/(ββ + αα) C29 sterane ratios along with CPI and OED indicate that the analysed samples from Mamfe Formation sit at mature oil window generation. The origin of the organic matter have been deduced to be mainly of terrestrial plant source with minor lacustrine and marine influences. Palaeo-environmental conditions were decipher to be of sub-oxic to anoxic conditions that have preserved the organic matter. This study have highlight valuable insight based on the biomarker geochemistry of the shales of the Mamfe Basin thereby reducing petroleum exploration risk.
Comparative Analysis of ORC and Condensing Heat Engines for Low Grade Waste Heat Recovery

The re-use of low-grade waste heat has the potential to contribute significantly to a better energy efficiency of our economies. There is a resource of around 100 TWhr per year in this area in Europe alone. The technology development in this area is still ongoing. Organic Rankine Cycle systems are considered the most promising technology. However, a nearly forgotten technology, the condensing engine (CE), was recently re-discovered. CEs use water as working fluid, with an operating temperature of 100°C at atmospheric pressure. The water is evaporated, and then condensed in the engine, where the arising vacuum is employed to generate power. Condensing engines were built until the late 19th Century, and then disappeared. Results from tests conducted in 1885 with a 0.735 kW commercial engine showed a mechanical efficiency of 3.7%, with a second law efficiency of 24.7%. For comparison, four typical experimental studies of Organic Rankine Cycle systems with power ratings between 0.5 and 1.4 kW were reviewed. Their thermal efficiencies ranged from 4.2 to 6.8%. The ORC systems’ second law efficiencies ranged from 20 to 35%, with an average of 27.5%. The comparative analysis showed that the CE’s performance is comparable to modern systems. Theoretical work suggests that it has significant further development potential. The CE’s simplicity combined with good efficiency, the use of a very simple working fluid, reduced safety requirements and the development potential makes this a technology which can become important again.
The Effect of Auditory Distraction on the Auditory Word Repetition Performance of Children with ADHD

Educators have observed and suggested that an appropriate seating arrangement is vital for the classroom performance of children with Attention Deficit Hyperactivity Disorder (CADHD). The current study attempts to find a cognitive reason for this observation by exploring whether CADHD are distracted by classroom noises from different locations. The current study attempts to create an experimental setting, which is on the one hand intuitively related to the classroom situation, while also maintaining experimental control, exploring the causal relation and using a task which does not require excessive attentional resources to focus on the impact of distracters rather than on task difficulty. We explored whether CADHD are more vulnerable to auditory distracters from different locations even if an attended task does not demand excessive executive resources. CADHD and normal children verbally repeated auditorily presented familiar words. Auditorily presented random numbers from the front, left, or right of the participants were presented randomly as distracters. The results showed that the effect of distracter on error rate was significant as was the interaction effect of distracter and group. However, only distracters from the front led to significantly more errors for CADHD. The findings suggest that CADHD are vulnerable to distracters from the auditory modality even when they have to perform a simple auditory task such as repeating familiar words – in a situation intuitively akin to the classroom setting.
Subcortical Structures and Creative Divergent Thinking: A Resting-State functional MRI Analysis

This study aimed to testify whether spontaneous fluctuations in the subcortex contribute to creative divergent thinking. Individuals at high- and low levels of creativity were recruited and the resting-state fMRI data was collected. Seed-wise and dynamic functional connectivity (FC) were used to identify differences between the two groups. The topological properties of the subcortical network were measured, and their relationship with performance of creative divergent thinking was calculated using brain-behaviour correlation analyses. The results revealed higher FC between the putamen, pallidum, and thalamus in high creativity group (HCG) compared to low creativity group (LCG) within the subcortex. Whole-brain FC results showed stronger connection across subcortical (i.e., the thalamus and pallidum) and cerebral regions (i.e., the insula, middle frontal gyrus, and middle temporal gyrus) in HCG compared to LCG. In addition, the subcortical FC demonstrated a positive correlation with performance of creative thinking across the pallidum, putamen, and thalamus. Our findings may provide novel insights into the relationship between creative divergent thinking and the activities of the subcortex. It is likely that not only fronto-striatal dopaminergic pathways, but also “motor” pathways, are involved in creative thinking processing.
The Form of Justice in Resolving Capital Market Dispute Resolution

The Indonesia Capital Market Arbitration Board (BAPMI), established to settle capital markets disputes when there is a written agreement between the disputing parties. is the article aims to explain that BAPMI is expected to resolve disagreements capital markets more effective than court and managed by people who understand the ins and outs of the stock market, due to a prolonged dispute resolution will only cause harm and increase business risk. The parties may apply to the District Court to cancel if it is suspected that the decision contains a misleading message, letter, or forged documents. BAPMI is the effective way and the best place to resolve capital market dispute. BAPMI is one of Alternative Dispute Resolution (ADR), it can be concluded that ADR is a new form of justice that society should pursue in the future.
Numerical Analysis of Ampicillin Release from Electrospun Nanofibrous Mats

Elektrospun nanofibroz mat, ilac salim calismalari icin guncel bir tekniktir. Bu nedenle, mevcut sorunlarin ustesinden gelmek ve yeni ilac salim sistemleri olusturmak icin bu tur sistemlerin ilac salim davranisini incelemek onemlidir. Bu makalede, bu gerekliligin karsilanmasi icin sayisal bir calisma yapilmis ve mevcut sayisal veriler literaturde bulunan deneysel calisma sonuclari ile dogrulanmistir. Gecici Langmuir-Freundlich adsorpsiyon-desorpsiyon izotermi, elektrospun nanofibroz sistemin mukemmel kuyu kosullari altinda ilac salim davranisini aciklamak icin kullanilmistir. Difuzyonun etkisi de hesaba katilmistir. Ilac salim oranlari, farkli ilk ilac konsantrasyonlari, gozenek degerleri, gecirgenlik kutle katsayilari ve mat yuzey alanlari icin arastirilmistir. Ayrica gozenek ve ilk ilac konsantrasyonu arasindaki iliski de bu calismada verilmistir. Cesitli baslangic ilac konsantrasyonlari ve gozenekler vasitasiyla ilac salim oranlarinda bazi onemli degisikliklerin meydana geldigi gorulmustur. Ilac salim hizi, gecirgenlik katsayisi veya yuzey alani ile degismekle birlikte, bu degisimlerde yukarida bahsedilen parametrelere gore kucuk farkliliklar gozlenmektedir. Sayisal kodun sonuclari deneysel verilerle uyumludur.
Using automatic speech recognition technology to enhance EFL learners’ oral language complexity in a flipped classroom

The present study examined the effects of using automatic speech recognition (ASR) technology on oral complexity in a flipped English as a Foreign Language (EFL) course. A total of 160 undergraduates were enrolled in a 14-week quasi-experiment. The experimental group (EG) and the control group (CG) were taught with a flipped approach, but the EG students needed to undertake an additional pre-class task with ASR technology. In each unit, all students’ in-class task performance was recorded, based on which the metrics of oral complexity were coded and computed. A two-way between- and within-subjects repeated measures design was conducted to examine the effects of the group factor, the time factor and the group × time interaction effects. The results showed that the EG students performed statistically better than their counterparts in the CG on lexical complexity and syntactic complexity. Moreover, significant improvement in phrasal complexity was witnessed over time in both groups. Significant group × time interaction effects were witnessed on overall complexity or subordination complexity. The gradients of the EG trajectories of the two metrics were greater than those of the CG. However, on phrasal complexity, the interaction effect was not significant.
I Like My Relational Machine Teacher: An AI Instructor’s Communication Styles and Social Presence in Online Education

ABSTRACT New advancements in technology have made machines teachers, or technology-powered robots or AI that assist in the overall learning experience, a possibility. Though adoption rates are currently low, colleges and universities will likely incorporate some aspects of machine teachers (e.g., AI, robots) in their curriculums in the foreseeable future. However, little is known about how to create an effective machine teacher-based education. As an initial step, the present study examines whether an AI instructor’s communication style would have an impact on students’ perceptions about an AI instructor-based education. To test this inquiry, the study conducted an online experiment using a 2 (communication styles: functional vs. relational) x 2 (course topic: natural science vs. social science) between-subjects design. Primary results indicate that students develop more favorable perceptions about an AI instructor-based education when the AI instructor is relational rather than functional. This tendency is particularly strong when listening to a social science lecture. Further, social presence of an AI instructor functions as a mediator, which explains the reason why a relational AI instructor leads to more favorable perceptions about an AI instructor-based education is because of one’s social presence of an AI instructor. Collectively, the study’s findings indicate the importance of communication styles and social presence of an AI instructor.
Expectancy Violations about Physical Properties of Animated Objects in Dogs

Dogs are not particularly known for complex physical cognitive abilities. However, a number of recent violation-ofexpectation studies have challenged this view. In the current eye-tracking study, we further investigated dogs’ (N=15) reaction to physically implausible events, particularly in the context of support, occlusion, and launching events. In Experiment 1, the dogs watched a rolling ball moving over a gap in a surface either falling down or hovering over the gap. In Experiment 2, the dogs saw a ball rolling behind a narrow pole either disappearing behind it or re-appearing on the other side. In Experiment 3, the dogs observed launching events either with or without contact between the balls. The dogs’ pupil dilation response and looking times suggest that they form implicit expectations about occlusion and launching events but not about gravity-related events at least in the context of animated objects on a screen.
Modulating Crystal Packing and Magnetic Properties of Nitroxide Free Radicals by Halogen Bonding

By combining a halogen bonding donor of 1,4-diiodotetrafluorobenzene (1,4-DITFB) or 1,2-diiodotetrafluorobenzene (1,2-DITFB) with 4-benzoyloxy-2,2,6,6-tetramethyl-piperidine-1-oxy free radical (BTEMPO, 1), two novel cocrystals, BTEMPO·1,4-DITFB (2) and BTEMPO·2(1,2-DITFB) (3), featuring a one-dimensional (1D) zigzag chain and a cyclic tetrameric structure, respectively, were constructed via halogen bonding. Furthermore, by tuning the halogen bonding between BTEMPO and halogen bonding donors, the packing modes of organic free radicals in both 2 and 3 are successfully modulated to result in side-by-side 1D mode in 2 and head-to-head dimer manner in 3. Magnetic studies reveal that in all compounds the organic radicals are antiferromagnetically coupled; however, the magnetic coupling in 2 and 3 is stronger than that in 1, indicating the modulating effect of halogen bonding on magnetic properties that are further confirmed by quantum chemistry calculations.
MRI Modality-based Brain Tumor Segmentation Using Deep Neural Networks

The tumor detection is major challenging task in brain tumor quantitative evaluation. In recent years, owing to non-invasive and strong soft tissue comparison, Magnetic Resonance Imaging (MRI) has gained great interest. MRI is a commonly used image modality technique to locate brain tumors. An immense amount of data is produced by the MRI. Heterogeneity, isointense and hypointense tumor properties restrict manual segmentation in a fair period of time, thus restricting the use of reliable quantitative measures in clinical practice. In the clinical practice manual segmentation task is quite time consuming and their performance is highly depended on the operator’s experience. Accurate and automated tumor segmentation techniques are also needed; however, the severe spatial and structural heterogeneity of brain tumors makes automatic segmentation a difficult job. This paper proposes fully automatic segmentation of brain tumors using encoder-decoder based convolutional neural networks. The paper focuses on well-known semantic segmentation deep neural networks i.e., UNET and SEGNET for segmenting tumors from Brain MRI images. The networks are trained and tested using freely accessible standard dataset, with Dice Similarity Coefficient (DSC) as metric for whole predicted image i.e., including tumor and background. UNET’s average DSC on test dataset is 0.76 whereas for SEGNET we got average DSC 0.67. The evaluation of results proves that UNET is having better performance than SEGNET.
The Relationship of Behavioral Factors with Investment Performance of Individual Investors in the Nepali Stock Market

In recent years, the market anomalies and irrational behavior of investors have influenced the stock market worldwide. The impact of investor behavior on the stock market is more prominent in small and less efficient capital markets. The study is based on the questionnaire survey of 203 investors from Kathmandu and Pokhara. The study uses Exploratory Factor Analysis (EFA) to explore the underlying dimensions of investor behavior employing Principal Component Analysis and Varimax rotation. The suitability of the data for the factor analysis has been examined using KMO and Barlett’s Test of Sphericity. The EFA extracted four factors of investor behavioral dimensions categorized as: heuristics, prospects, market factors and herding effect. The factor scores obtained from the EFA was used to examine the correlation of these behavioral factors with investment performance. The results reveal that behavioral biases like heuristics, prospects, market factor and herding effect are present among individual investors in Nepal. Among the factors, the investment performance of investors is found to be influenced by heuristics and market factors. The heuristic behaviors are found to have the highest and positive influence on the investment performance. Finally, the results depict that following the herd behavior in the market and prospects does not result in the improved investor performance. The findings are helpful to understand the role of investor behavior in the stock market and formulation of appropriate policies that limit the possibility of behavioral biases affecting the stock market adversely.
From protest to progress through partnership with students: Being human in STEM (HSTEM)

In Fall 2015, Amherst College students held a four-day sit-in in unity with student protests occurring all over the United States highlighting barriers to inclusion of underrepresented and marginalized students.Following appeals for action, students partnered with faculty and staff in science, technology, engineering, and mathematics (STEM) to develop the Being Human in STEM (HSTEM) Initiative. HSTEM involves exploring past diversity and inclusion efforts in STEM, sharing one’s own experiences in STEM with others, and developing student-driven projects to improve belonging in STEM. In this student, faculty, and staff co-authored paper, we describe the origin of HSTEM; share student, faculty and staff reflections on our experiences with HSTEM; and present two inquiry projects examining HSTEM impact. We discuss lessons learned and recommendations for diversity and inclusion efforts in higher education, both in and beyond STEM, emphasizing the power of an initiative that was originated by and remains driven by student partners.
Novel Wireless Sensor Network Routing Protocol Performance Evaluation using Diverse Packet Size for Agriculture Application

As the wireless sensor networks (WSNs) progress with newer and more advanced technologies, so do the demands for them in a growing number of applications. Precision agricultural environment monitoring is one of the most prominent applications that require feasible wireless support systems, particularly in the protection and condition control of the crops. This paper focuses on the grid nodes arrangement of WSN, considering the wide dissemination of the plantation areas in the agriculture industry. Due to the different types of sensors used and their data size, the study on the impact of the varied packet size on the performance of the small and large network has been carried out using AODV and OLSR routing protocols. No significant differences in terms of performance can be seen as the packet size is varied. However, compared to the small network, more performance issues have occured in the large network, such as more packet loss, higher throughput degradation, higher energy consumption, worse unfairness, and more overhead production. The OEG routing protocol has been proposed to enhance the network performance by reducing the strain due to the saturated traffic. When solely compared to AODV, OEG routing protocol is able to enhance the network performance with at most 27% more packet delivery ratio, 31kbps more throughput, and 0.991J lesser energy consumed in the network.
Response Surface Methodology Optimization in Asphalt Mixtures: A Review

The application of statistical modeling and optimization approaches such as response surface methodology (RSM) is important for the excellent potential to tackle different constraints and goals and the analysis of the relationships between independent factors influencing a particular response. This chapter provides a simple yet detailed literature review on the utilization of RSM for the design of experiments, modeling, and optimization of virgin and alternative materials into asphalt binder and mixtures for sustainability. Meanwhile, an in-depth analysis based on the literature reviewed in terms of asphalt binder modification employing RSM with various independent parameters were summarized. Also, a critical review of the application of RSM to optimize the engineering and mechanical performance characteristics of asphalt concrete mixtures is presented in this chapter. The current chapter concluded that the use of RSM statistical analysis in a highway materials perspective provides a broader understanding of the factors that control pavement performance throughout the pavement service life.
Does a Test Ride Influence Attitude towards Autonomous Vehicles? A Field Experiment with Pretest and Posttest Measurement

Autonomous vehicles have the potential to disrupt the mobility system. Therefore, it is important to understand attitude formation towards autonomous vehicles. The focus of this study is on the private user’s technology acceptance of an autonomous vehicle. The study applies the determinants of technology acceptance to capture users’ attitude towards and intention to adopt autonomous vehicles. A field experiment with 27 participants was conducted to assess changes in determinants before and after a test ride with a level 2 automated vehicle. The automated vehicle was equipped with technology that allowed a hands-off, feet-off experience on a public road in real traffic. The results show that a ride has a positive and significant effect on attitudes towards autonomous vehicles. Additionally, participants with higher ratings of technology anxiety show a remarkable increase in attitude towards autonomous vehicles after the ride compared to participants with lower levels of technology anxiety. These findings indicate that experience with a partially automated vehicle has a potentially positive effect on the acceptance of autonomous vehicles. As such, our study illustrates the importance of continuous pilot testing with private automated vehicles to increase future user acceptance of autonomous vehicles.
Comparison between optical and computer vision estimates of visibility in daytime fog

This paper investigates visibility in daytime fog as estimated optically with a visibility sensor and computationally with an image sensor. We use a database collected on a weather observation site equipped with both a forward scatter visibility meter and a CCTV camera. We implement a computer vision method based on the contrast sensitivity function of the human visual system to estimate the visibility level (VL) of targets located at different distances in the scene, and we study the relationship of the results with the extinction coefficient of the atmosphere, derived from the meteorological optical range (MOR) provided by the optical sensor. We show that Koschmieder's law, which predicts exponential reduction of visibility as a function of optical depth, applies not only to dark objects against the sky, but to other types of contrast as well.