Miracle-dz/UniFAR-FTUs huggingface dataset:
Object-Based Geometric Distortion Metric for Viewport Rendering of 360° Images

To visualize omnidirectional (or 360°) visual content, a sphere to plane projection is employed, that maps pixels from the observed sphere region to a 2D image, called as viewport. However, this projection introduces geometrical distortions on the rendered image, such as object shape stretching, or shearing, and bending of straight lines, which may affect the user’s quality of experience (QoE). This paper proposes an object-based quality metric to assess the subjective impact of the objects shape deformation. The metric uses semantic segmentation to identify the relevant objects in the viewport, where the stretching distortion has a higher perceptual impact, and computes the stretching distortion for each object. Two distinct approaches were exploited and evaluated: the first one, directly computes and compares object shape measures on the sphere and on the viewport; the second one is based on Tissot indicatrices, which are computed for individual objects in the viewport. The experimental results show that while the Tissot based method performs slightly better than the direct shape measurement, both approaches outperform benchmark solutions; furthermore, they are able to classify the viewport quality, with respect to quality scores obtained in a subjective crowdsourcing study, with a correct decision percentage close to 90%. Additionally, the Tissot based approach was used in a global quality metric that finds out the Pannini projection parameters that result in the least perceivable geometric distortion. It is shown that the automatically tuned Pannini projection results in viewports with a more pleasant visual quality than the considered benchmark projections.
Tearing Down to Take Up Space: Dismantling White Spaces in the United States

With this concluding article, we build off the scholarship from this two-part special issue on white space to recommend meaningful interventions that seek to challenge and dismantle white spaces at the organizational, institutional, and structural levels of U.S. society. We focus on two broad arenas of social space, one geographical (residential neighborhoods) and one institutional (education), in the hopes of generating more engagement from scholars of race and racism in conversations about policies that can meaningfully transform white space. We share experiences from the Systemic Justice Seminar and student activism at Harvard to highlight some innovative ideas about challenging, disrupting, and resisting white space. We suggest ways to think about policies and actions that make visible the tacitly exclusionary mechanisms within white spaces and create ways for BIPOC people and communities to take up space. Lastly, we encourage academic and public communities to continue exploring the best methods for deconstructing white space on the way to creating a more racially equitable society.
The Impact of Coworker and Supervisor Support on Stress among Malaysian School Teachers during the COVID-19 Pandemic

In the current COVID-19 crisis, teaching is difficult. The demands from students, parents, the government, and school administrators may be overwhelming. Many Malaysian teachers are experiencing growing mental strain, and they are reluctant to seek help due to social stigma. This quantitative study explored the impact of coworker and supervisor support on stress among primary and secondary school teachers in Malaysia. In addition, the study examined the spill-over impact of stress on teachers’ turnover intention. A sample of 250 Malaysian school teachers completed a questionnaire. The data were analysed using correlation and regression analyses. Results re emphasized the positive impact of coworker support on reducing teachers’ stress, but not supervisor support. Furthermore, it was found that teacher stress was linked to a higher likelihood of turnover. Therefore, it is important for school administrators and policymakers to strengthen the role of coworkers in reducing stress among Malaysian school teachers.
NSVQ: Noise Substitution in Vector Quantization for Machine Learning

Machine learning algorithms have been shown to be highly effective in solving optimization problems in a wide range of applications. Such algorithms typically use gradient descent with backpropagation and the chain rule. Hence, the backpropagation fails if intermediate gradients are zero for some functions in the computational graph, because it causes the gradients to collapse when multiplying with zero. Vector quantization is one of those challenging functions for machine learning algorithms, since it is a piece-wise constant function and its gradient is zero almost everywhere. A typical solution is to apply the straight through estimator which simply copies the gradients over the vector quantization function in the backpropagation. Other solutions are based on smooth or stochastic approximation. This study proposes a vector quantization technique called NSVQ, which approximates the vector quantization behavior by substituting a multiplicative noise so that it can be used for machine learning problems. Specifically, the vector quantization error is replaced by product of the original error and a normalized noise vector, the samples of which are drawn from a zero-mean, unit-variance normal distribution. We test our proposed NSVQ in three scenarios with various types of applications. Based on the experiments, the proposed NSVQ achieves more accuracy and faster convergence in comparison to the straight through estimator, exponential moving averages, and the MiniBatchKmeans approaches.
TFF1 in Aqueous Humor—A Potential New Biomarker for Retinoblastoma

Simple Summary Retinoblastoma is the most common pediatric intraocular malignancy with high cure rates in developed countries. Nevertheless, useful predictive biomarkers providing reliable evidence for therapy decisions are urgently needed to optimize therapy regimes. TFF1 is a promising candidate as it is expressed in a more advanced subtype of retinoblastoma. Additionally, TFF1 is a naturally secreted peptide. Thus, TFF1 might be detectable in the aqueous humor of RB patients’ eyes, providing the opportunity to determine its expression prior to therapy without the necessity of a tumor biopsy. We therefore investigated for the first time aqueous humor samples of retinoblastoma patients in order to test for the availably and expression status of TFF1 as well as to compare it with the original tumor and established corresponding primary cell cultures. Abstract Retinoblastoma (RB) is the most common childhood eye cancer. The expression of trefoil factor family peptide 1 (TFF1), a small secreted peptide, has been correlated with more advanced RB stages and it might be a promising new candidate as a RB biomarker. The study presented addressed the question of if TFF1 is detectable in aqueous humor (AH) of RB patients’ eyes, providing easy accessibility as a diagnostic and/or therapy accompanying predictive biomarker. The TFF1 expression status of 15 retinoblastoma AH samples was investigated by ELISA and Western blot analyses. The results were correlated with the TFF1 expression status in the tumor of origin and compared to TFF1 expression in established corresponding primary tumor cell cultures and supernatants. Nine out of fifteen AH patient samples exhibited TFF1 expression, which correlated well with TFF1 levels of the original tumor. TFF1 expression in most of the corresponding primary cell cultures reflects the levels of the original tumor, although not all TFF1-expressing tumor cells seem to secret into the AH. Together, our findings strongly suggest TFF1 as a reliable new RB biomarker.
Studies on Linguistic Stylistic Analysis of Suicide Notes and Suicidal Thought Posts

A suicide note is a piece of writing written or posted online by someone who dares to end his/her life and admits that he/she did it intentionally and willingly for different reasons, which vary according to each person and his/her circumstances. Suicidal people usually explain this behavior by leaving suicide notes in which they will either express their feelings to their lovers or blame someone or just have a chance to say their last words. Different studies deal with suicide notes from different perspectives; most of these studies belong to psychology but to have a full understanding of what suicide notes are all about, most of the scholars in these studies have used linguistic analysis to examine the content of suicide notes. Thus, the researchers include some of these studies within this paper. This study draws on the other previous studies that deal with the content of suicide notes and the stylistics studies aiming to extract the linguistic features of particular texts; the researchers will describe these studies in detail within this study. Then, the researchers will present the most prominent scholars and the influential studies related to linguistic suicide analysis.
Short-Term Effects of Temperature and Thyrotropin-Releasing Hormone Stimulation on Adrenocorticotropin Stability in Horses

Simple Summary Approximately 20% of older horses develop pituitary dysfunction (PPID), which is associated with haircoat changes, muscle loss, and a higher risk of developing an infection or laminitis. Elevated plasma adrenocorticotropic hormone (ACTH) is used to diagnose PPID; however, ACTH is not stable in blood samples. Therefore, samples should be kept at 4 °C until analysis. In ambulatory veterinary practice, blood samples can be left at room temperature (20 or 30 °C) or inadvertently left in a vehicle without refrigeration where they might be exposed to temperatures of up to 70 °C in hot climates. To evaluate the effects of temperature on ACTH concentrations, we experimentally subjected blood samples from horses with and without pituitary dysfunction to temperatures of 4 (reference), 20, 30, and 70 °C for 1 h prior to laboratory measurement. The stability of ACTH was affected by short-term exposure to high temperatures in horses with and without pituitary dysfunction with both higher and lower ACTH concentrations measured unpredictably. Our results suggest that samples should be kept at 4 °C to reflect the true ACTH concentration. Exposure to temperatures of up to 40 °C for 1 h can still provide an appropriate assessment of pituitary function in most cases, but the ACTH concentration changed by 12% in healthy horses and 5% in horses with PPID. Abstract Pituitary pars intermedia dysfunction (PPID) is diagnosed by increased basal or post thyrotropin-releasing hormone (TRH) stimulation ACTH concentrations. ACTH is known to be unstable; however, the effect of different temperatures and TRH stimulation on equine ACTH stability is poorly described. In total, 15 horses, including 8 PPID positive (ACTH > 35 pg/mL at baseline or >65 pg/mL 30 min after TRH stimulation), were divided into 2 groups: 9, including 5 PPID positive, with basal ACTH concentrations and 6, including 3 PPID positive, with post TRH stimulation ACTH concentrations. Whole blood was stored for 1 h at 4, 20, 30, 40, or 70 °C. After centrifugation, immunoreactive ACTH concentrations were determined using a chemiluminescent assay. Linear mixed effect models were used to detect the effects of temperature, PPID status, and TRH stimulation on the immunoreactive ACTH concentration. Temperature had a significant effect (p = 0.003) on immunoreactive ACTH concentrations, and this effect was greater in PPID-negative horses (p = 0.01), with the changes in immunoreactive ACTH concentrations being slightly unpredictably higher or lower than samples stored at 4 °C. Even at 20 °C, mean immunoreactive ACTH concentrations minimally changed by 5% in PPID horses and 12% in non-PPID horses after 1 h. No significant effect of TRH stimulation was identified. Although ACTH concentrations should ideally be determined from samples kept at 4 °C, samples inadvertently left at temperatures of up to 40 °C can provide valid results if analyzed within 1 h; however, this increases the risks of altered ACTH concentrations, occasionally influencing the diagnosis of PPID.
Dynamics of Microbial Communities during the Removal of Copper and Zinc in a Sulfate-Reducing Bioreactor with a Limestone Pre-Column System

Biological treatment using sulfate-reducing bacteria (SRB) is a promising approach to remediate acid rock drainage (ARD). Our purpose was to assess the performance of a sequential system consisting of a limestone bed filter followed by a sulfate-reducing bioreactor treating synthetic ARD for 375 days and to evaluate changes in microbial composition. The treatment system was effective in increasing the pH of the ARD from 2.7 to 7.5 and removed total Cu(II) and Zn(II) concentrations by up to 99.8% and 99.9%, respectively. The presence of sulfate in ARD promoted sulfidogenesis and changed the diversity and structure of the microbial communities. Methansarcina spp. was the most abundant amplicon sequence variant (ASV); however, methane production was not detected. Biodiversity indexes decreased over time with the bioreactor operation, whereas SRB abundance remained stable. Desulfobacteraceae, Desulfocurvus, Desulfobulbaceae and Desulfovibrio became more abundant, while Desulfuromonadales, Desulfotomaculum and Desulfobacca decreased. Geobacter and Syntrophobacter were enriched with bioreactor operation time. At the beginning, ASVs with relative abundance <2% represented 65% of the microbial community and 21% at the end of the study period. Thus, the results show that the microbial community gradually lost diversity while the treatment system was highly efficient in remediating ARD.
Enhancing Robot Perception Using Human Teammates ∗ (Extended Abstract)

In robotics research, perception is one of the most challenging tasks. In contrast to existing approaches that rely only on computer vi- sion, we propose an alternative method for improving perception by learning from human teammates. To evaluate, we apply this idea to a door detection problem. A set of preliminary experiments has been completed using software agents with real vision data. Our results demonstrate that information inferred from teammate observations significantly improves the perception precis ion. 1. BACKGROUND Robot perception is generally formulated as a problem of ana- lyzing and interpreting various sensory inputs, e.g., camera feeds. In this paper, we approach robot perception from a completely dif- ferent direction. Our approach utilizes a team setting where a robot collaborates with human teammates. Motivated by the fact that humans possess superior perception skills relative to thei r robotic counterparts, we investigate how a robot can take advantage of its teammate's perfect vision. In general, an agent acquires new information through percep- tion, and in turn, the agent chooses actions based on the informa- tion acquired. Let us suppose that a robot has a mental model of its human teammate such that a causal relationship is specifi ed be- tween information and actions. Then, by understanding the human mental model of such decision making (or planning), the robot can infer what the human teammate has seen based on the human's be- havior. In other words, an observation of a human teammate can be ∗ This work was conducted (in part) through collaborative partic- ipation in the Robotics Consortium sponsored by the U.S Army
Defining Characteristics of an Integrated STEM Curriculum in K--12 Education

The purpose of the study was to obtain consensus concerning the defining characteristics of integrated STEM (Science, Technology, Engineering, and Mathematics) curriculum. This study utilized a three round modified Delphi study to solicit recommendations from experts of STEM education in order to: 1) create a set of categorical and defining curricular components needed to develop and implement appropriate integrated STEM curriculum; 2) identify the characteristics that set integrated STEM education curriculum apart from single-discipline curricula; 3) discuss the components necessary to gauge whether an initiative, project, or curriculum should be referred to as integrated STEM education; and 4) examine whether significant differences exist from the defining characteristics based on the disciplinary grounding of panelists in science, mathematics, or technology and engineering. Results indicate that it is essential that STEM education be problemor project-based, although other considerations are essential in providing students with the most authentic learning experiences. The panel agreed that the majority of STEM curricula are not integrated, but discipline-specific curricula and that many STEM programs have a narrow educational focus that includes a collection of activities and specific products that may not be developed using sound pedagogical practices. The results from the study add to the literature on the definitive attributes of STEM education. Table of
Four-Port Cylindrical Pattern- and Polarization-Diversity Dielectric Resonator Antenna for MIMO Application

In this communication, a four-port cylindrical pattern-diversity and polarization-diversity dielectric resonator antenna (DRA) for multiple-input multiple-output (MIMO) applications is presented for the first time. The design utilizes two degenerate HEM12δ+1 modes and two degenerate HEM21δ modes of the cylindrical DRA, with unidirectional radiation and quasi-omnidirectional radiation, respectively. The resonant frequencies of four modes can be predicted by the radar cross section characteristic of an isolated DRA. Through optimizing the dimension of DRA and loading technology, the HEM12δ+1 and HEM21δ modes can operate in the same band. The HEM12δ+1 modes are effectively excited by two polarization orthogonal slot pairs while two coaxial probes are utilized for exciting the HEM21δ modes. The power divider with tapered end is presented to expand bandwidth of HEM21δ modes. In addition, the method based on mode orthogonal to utilize two degenerate HEM21δ modes with high isolation is proposed. To verify design, a four-port diversity DRA operating at 2.4 GHz band (2.4–2.48 GHz) was simulated, fabricated and measured. The S parameters and radiation characteristics were measured and discussed. Moreover, the calculated indoor communication performance including the envelop correlation coefficient, mean effective gain and channel capacity as the proposed four-port DRA used for MIMO element are given and discussed.
Heterogeneous Clutter Suppression via Affine Transformation on Riemannian Manifold of HPD Matrices

Due to a serious shortage of training data, the performance of adaptive clutter suppression suffers remarkable degradation in heterogeneous environments. To address this problem, a novel clutter suppression method via affine transformation on manifolds is proposed. First, training samples in heterogeneous environments are characterized on an established manifold in which the distribution properties are analyzed. Then, a clutter classification scheme is proposed, whereby the KL divergence decision rule is derived to identify the training data as either homogenous or heterogeneous samples. Afterward, based on the distribution properties of samples and the clutter classification scheme, an affine transformation on manifolds is proposed for sample augmentation by transporting heterogeneous samples into the region of homogeneous samples. Finally, the clutter in the area of interest is suppressed on the manifold, which combines the transformed samples with the homogeneous samples, such that superior performance is obtained. Experiments on both simulated and real data validate the superiority of the proposed method in highly heterogeneous environments.
Analyzing Differences between Online Learner Groups during the COVID-19 Pandemic through K-Prototype Clustering

Online learning is a very important means of study, and has been adopted in many countries worldwide. However, only recently are researchers able to collect and analyze massive online learning datasets due to the COVID-19 epidemic. In this article, we analyze the difference between online learner groups by using an unsupervised machine learning technique, i.e., k-prototypes clustering. Specifically, we use a questionnaire designed by domain experts to collect various online learning data, and investigate students’ online learning behavior and learning outcomes through analyzing the collected questionnaire data. Our analysis results suggest that students with better learning media generally have better online learning behavior and learning results than those with poor online learning media. In addition, both in economically developed or undeveloped regions, the number of students with better learning media is less than the number of students with poor learning media. Finally, the results presented here show that whether in an economically developed or an economically undeveloped region, the number of students who are enriched with learning media available is an important factor that affects online learning behavior and learning outcomes.
A min-max theorem for clean tangled clutters

A clutter is clean if it has no delta or the blocker of an extended odd hole minor. There are combinatorial and geometric classes of clean clutters, namely ideal clutters, clutters without an intersecting minor, and binary clutters. A clutter is tangled if it has covering number two and every element is in a minimum cover. Clean tangled clutters arise, for example, when studying the packing property in Clutter Theory. We define two parameters on clean tangled clutters, one is the optimum of a combinatorial minimization problem called the monochromatic covering number, extending notions such as matroid girth and clutter covering number, while the other is the optimum of a geometric maximization problem called the depth, intimately linked to another parameter defined recently called the notch of a set system. We prove a min-max relation between the two parameters, exposing an intriguing interplay between the combinatorics and the geometry of such clutters. As a consequence of our results, we also prove that the core of an ideal tangled clutter is an ideal clutter.
Performance evaluation of portable milking machine on machine economy, milk yield, milking time, and milk constituents of Nepalese Cattle

Hand milking, a most common practice for majority of the farm households is a labor and time intensive process in Nepal. Effect of milking machine on milk yield, milking time, milking rate and milk composition, and economical aspects of machine use was investigated on cow milking applying portable two cluster bucket type milking machine. Three treatments were investigated as follows: hand milking, machine milking (M1) @330 mmHg vacuum pressure and machine milking (M2) @290 mmHg vacuum pressure. The obtained daily milk yield for hand milking (7.58 ± 1.28 kg) was 7.3% and 2.4% higher than machine milking M1 (7.02 ± 1.89 kg), and M2 (7.40 ± 1.69 kg), respectively. The milk yield did not differ statistically between hand and machine milking methods (p > 0.05). Milking machine significantly shortened the cow milking time from 11.91 minutes (hand milking) to 5.38 minutes (M1) and 4.98 minutes (M2) respectively. Similarly, milk flow rate for hand milking (0.32 kg min) was 52.9% (0.68 kg min) and 57.3% (0.75 kg min) lower than M1 and M2, respectively. There were significant differences in milking time and milk flow rate between machine milking and hand milking (p<0.05). Results indicated that there was no any difference between milking methods in the incidence of milk composition (p>0.05). The use of a milking machine saves more than one half the labor required for milking a herd of 17 cows. Cost saving achieved by our result were 39.47%-58.98% for machine milking depending on the number of cluster. Therefore, we concluded that greater saving in labor and cost can be occurred in larger and higher producing herds by the use of two or more cluster milking machine. Importantly, an economical aspect of the milking machine use is basically proportional to the size of the herd.