Miracle-dz/UniFAR-FTUs huggingface dataset:
Few-layer hexagonal boron nitride synthesized by chemical vapor deposition and its insulating properties

Hexagonal boron nitride (h-BN), which is one of two-dimensional (2D) materials, is expected to be used as supporting and passivation layers for graphene-based devices. However, it is difficult to obtain large-area h-BN by the conventional exfoliation techniques. Here, we performed chemical vapor deposition (CVD) by employing epitaxial metal films as a catalyst to grow few-layer h-BN with a large grain size. The grain sizes of h-BN obtained were found to be a few micrometers or larger. Furthermore, we evaluated insulating properties of few-layer h-BN with conductive atomic force microscopy. Assuming a parallel plate model, a breakdown strength was estimated to be at least 7.5–45.5 MV cm−1, considering variations in h-BN thickness. These values are comparable with that obtained for exfoliated h-BN in a previous study. Considering the scalability and insulating properties, our epitaxially-synthesized h-BN is expected to be used for future graphene devices.
Inter-Rater Reliability of Grid Localization Test of Tactile Spatial Localization for the Low Back

Tactile acuity is a key component of a normal functioning somatosensory system. Tactile acuity allows an individual to discern the sense of touch or stimuli and localize the site of the sensory stimuli. Evidence has demonstrated that individuals with persistent pain often have impaired tactile acuity abilities [1,2]. This impairment in tactile acuity may be due to a shift in the individual’s central nervous system structure and function [3-6]. These cortical changes alter the brain representation of the body for these individuals and could be a potential source for symptoms [7,8].
Current status of putative animal sources of SAS-CoV-2

SARS-CoV-2 is currently considered to have emerged from a bat coronavirus reservoir. 20 However, the real natural cycle of this virus remains to be elucidated. Moreover, the COVID-19 21 pandemic has led to novel opportunities for SARS-CoV-2 transmission between humans and 22 susceptible animal species. In silico and in vitro evaluation of the interactions between the SARS23 CoV-2 spike protein and eucaryotic angiotensin-converting enzyme 2 (ACE2) receptor have 24 tentatively predicted susceptibility to SARS-CoV-2 infection of several animal species. Although 25 useful, these data do not always correlate with in vivo data obtained in experimental models or 26 during natural infections. Other host biological properties may intervene such as the body 27 temperature, level of receptor expression, co-receptor, restriction factors, and genetic background. 28 The spread of the SARS-CoV-2 also depends on the extent and duration of viral shedding in the 29 infected host as well as population density and behaviour (group living and grooming). Overall, 30 current data indicate that the most at-risk interactions between humans and animals for COVID-19 31 infection are those involving certain mustelids (such as minks and ferrets), rodents (such as 32 hamsters), lagomorphs (especially rabbits), and felines (including cats). Therefore, special attention 33 should be paid to the risk of SARS-CoV-2 infection associated with pets. 34
International Journal of Instruction

Citation: Mardianto. , Hanurawan, F. Chusniyah, T. , Rahmawati, H. , & Hutagalung, F. D. (2021). Cyber Aggression between Intentions and Cyber Wellness of Students: An application of TPB Models. International Journal of Instruction, 14(2), 67-82. https://doi.org/10.29333/iji.2021. 1425a Article submission code: 20200127084403 Received: 27/01/2020 Revision: 25/08/2020 Accepted: 19/09/2020 OnlineFirst: 11/01/2021
This paper is included in the Proceedings of the 31st USENIX Security Symposium. Private Signaling

We introduce the problem of private signaling . In this problem, a sender posts a message on a certain location of a public bulletin board, and then posts a signal that allows only the intended recipient (and no one else) to learn that it is the recipient of the message posted at that location. Besides privacy, two efficiency requirements must be met. First, the sender and recipient do not participate in any out-of-band communication. Second, the overhead of the recipient must be (much) better than scanning the entire board. Existing techniques, such as server-aided fuzzy message detection (Beck et al., CCS’21), could be employed to solve the private signaling problem. However, this solution leads to a trade-off between privacy and efficiency, where the complexity of the recipient grows with the required privacy. Specifi-cally, this would require a scan of the entire board to obtain full privacy for the recipient. In this work, we present a server-aided solution to the private signaling problem that guarantees full privacy for all recipients while requiring only constant amount of work for both the recipient and the sender. Specifically, we provide three contributions: First, we provide a formal definition of private signaling in the Universal Composability (UC) framework and show that it captures several real-world settings where recipient anonymity is de-sired. Second, we present two server-aided protocols that UC-realize our definitions: one using a single server equipped with a trusted execution environment, and one based on two servers that employ garbled circuits. Third, we provide an open-source implementation of both of our protocols, evaluate their performance, and identify for which sets of parameters they can be practical.
The Potential Applications of Nanotechnology in Medicine

Background:Non-communicable diseases management such as cancers often represent a difficult situation. Discoveries of nanotechnology in physics and chemistry were extensively introduced for application in the biomedical field. Nanoparticles imply multimodal uses in bio-detection, drug delivery and diagnostic imaging due to their surfaces ability to interact and interfere effectively with biological environment and targeting cell-surface receptors. Objectives: To identify the nanotechnology applications in medical fields and illustrate their efficacy and efficiency in diagnosis and management of diseases. Review of Literature: Nanoparticle applications in management and control of serious diseases such as cancers are promising. Nanoparticles target the drugs delivery system specifically to malignant cells. They are able to penetrate the stratum corneum barrier of the skin and thus have been used widely as a treatment tool in skin cancer imaging, vaccine delivery via the skin, antimicrobials and wound healing. Recently, nanoparticles were used in lung diseases through their ability to accumulation the drugs in the diseased lung areas by providing a local inhalation delivery of active components. Nanotechnology possess as well useful anti-inflammatory effects and can improve wound healing process through acting as antimicrobial agents. Silver nanoparticles have potential effect against gram negative and gram positive pathogens. Conclusion: Nanoparticles have the ability to potent the diagnosis and treatment in various diseases such as: cancers, lung disease, dermatology and coronary artery diseases via targeting the diseased cells specifically and thus reducing the adverse effects and general toxicity associated with conventional treatments.
International Journal of Instruction

Citation: Phoeun, M. , & Sengsri, S. (2021). The Effect of a Flipped Classroom with Communicative Language Teaching Approach on Undergraduate Students’ English Speaking Ability. International Journal of Instruction, 14(3), 1025-1042. https://doi.org/10.29333/iji.2021. 14360a Article submission code: 20201110093143 Received: 10/11/2020 Revision: 13/02/2021 Accepted: 09/03/2021 OnlineFirst: 24/06/2021
U.S. Treasury Auctions: A High Frequency Identification of Supply Shocks∗

We present a novel identification strategy of U.S. Treasury supply shocks based on auction data. We interpret changes in Treasury futures prices around public announcements by the Treasury as shocks to the expected supply of debt securities by the U.S. government. After describing the theoretical mechanism between futures prices and expected debt supply, we isolate the component of price variation in futures pertaining to Treasury announcements between 1998 and 2020. We then study how Treasury supply affects financial markets by means of local projections, using our series of shocks as instrumental variables. We show that surprise increases in Treasury supply have sizable and significant dynamic causal effects on financial markets, as they cause an upward shift of the yield curve, fuelled in part by an increase in the term premium. While stock prices go up and volatility goes down, corporate bond yields increase. As a result, the equity premium rises, the risk premium falls, inflation expectations soar and the liquidity premium decreases. JEL-Classification: E44, E62, H63
Review on the applications of machine learning models for stock market predictions: A literature survey

Financial stocks values are non-linear, volatile, and chaotic, making them one of the most challenging financial time series to predict. The incentive of financial gain has led many researchers and academia to devise methods to predict the stock market, despite copious uncertainty. Because of their ability to recognize complex patterns in several applications, machine learning models are extensively researched among the most recent methods. In this paper, Support Vector Machine, Artificial Neural Networks and Case-based Reasoning for stock market prediction is surveyed. This paper also reviews sentiment analysis to highlight the behavioral trends of the stock market and its investors with the advent of technology.A generalised modelling methodology for applying machine learning techniques to the stock market is proposed in this paper
Investigating the Multimodal Nature of Human Communication

The multimodal nature of human communication has been well established. Yet few empirical studies have systematically examined the widely held belief that this form of perception is facilitated in comparison to unimodal or bimodal perception. In the current experiment we first explored the processing of unimodally presented facial expressions. Furthermore, auditory (prosodic and/or lexicalsemantic) information was presented together with the visual information to investigate the processing of bimodal (facial and prosodic cues) and multimodal (facial, lexic, and prosodic cues) human communication. Participants engaged in an identity identification task, while event-related potentials (ERPs) were being recorded to examine early processing mechanisms as reflected in the P200 and N300 component. While the former component has repeatedly been linked to physical property stimulus processing, the latter has been linked to more evaluative “meaning-related” processing. A direct relationship between P200 and N300 amplitude and the number of information channels present was found. The multimodal-channel condition elicited the smallest amplitude in the P200 and N300 components, followed by an increased amplitude in each component for the bimodal-channel condition. The largest amplitude was observed for the unimodal condition. These data suggest that multimodal information induces clear facilitation in comparison to unimodal or bimodal information. The advantage of multimodal perception as reflected in the P200 and N300 components may thus reflect one of the mechanisms allowing for fast and accurate information processing in human communication.
Response of hot pepper (Capsicum annuum L.) to major fungal diseases under field and greenhouse conditions in Horo Guduru Wollega, Oromia, Ethiopia.

Hot pepper (Capsicum annuum L.) is a national spice and vegetable of Ethiopia, produced as a cash crop. Biotic and abiotic stresses are very common throughout the pepper producing area of the country. Diseases are the major constraint to hot pepper production. An experimental trial was conducted at Harato Research site, Wollega University, Ethiopia to evaluate the reaction of five hot pepper varieties (Mareko Fana, Bako Local, Melka Shote, Melka Awaze and Oda Haro) and one local variety has control against the major fungal diseases. In vitro and in vivo, test was conducted during 2018/2019 main growing season. The result showed that Phytophthora blight (Phytophthora capsici) followed by, Frogeye leaf spot (Cercospora capsici) and Fusarium wilt (Fusarium oxysporum) were the most predominant and severe fungal pathogens for hot pepper at the specified growing area. There was high significant (P<0.001) difference between varieties for all diseases scored, yield and yield components. Even though, the degree of infection varied between the varieties, the local checks were highly attacked by Phytophthora blight and Fusarium wilt whereas, Melka Shote and Melka Awaze varieties were devastated by Frogeye leaf spot in both fields and greenhouse conditions. The tested varieties including traditional and improved varieties were affected by fungal pathogens and it is recommended to intensify research programs aimed at disease resistance and genetic improvement of cultivated hot pepper varieties through breeding procedures towards the interest of resource poor farmers.
International Journal of Instruction

Ubiquitous learning has recently gained increasing popularity in the education sector, which significantly increased the efficiency of individual and collaborative learning. The aim of this study is to develop an Android version of science education-adaptive learning system (ScEd-ALS) as a science learning medium to accommodate various learning styles. The method used in this research is a mixedmethod consisting of a qualitative method, which is a developmental method that provides illustrations concerning the process of creating the developed media, and a quantitative method, which utilizes quasi-experiments to determine the effectiveness of the developed media application. The study comprised 114 eighthgrade junior high school students and three integrated science teachers in South Tangerang. The final product of the study is an Android-based science learning medium that conforms to the visual, aural, reading/writing, and kinesthetic student learning styles. Hence, this Android-based ScEd-ALS was found to be feasible and useful, as assessed by five experts (two media experts and three science education material experts). Nonetheless, there were significant differences in the learning outcomes between the experimental class using the Android version of ScEd-ALS compared to the control class. The effectiveness of using ScEd-ALS in this study was measured based on the percentage of students' mastery level. ScEd-ALS Android based on visual and kinesthetic learning styles are the most effective media compared to aural and read/write.
Mastectomy with Sentinel Lymph Node Biopsy and Prosthetic Breast Reconstruction under Hypnosis Analgesia: A Multistep Approach

The incidence of breast cancer worldwide is increasing as is the survival rate after breast cancer. This is essentially due to therapeutic progress. However, anticancer treatment is associated with nonnegligible side effects related to the different treatment modalities. One of the greatest challenges for the coming years will be to promote the participation of patients in their therapeutic plan and to encourage them to not give up their adjuvant treatment for alternative, inefficient and dangerous therapies. In this context, the use of hypnosis is a very good option among highly motivated patients. Hypnosis is able to decrease side effects induced by surgery, general anesthesia and anticancer treatments and generates an important feeling of satisfaction among patients. Herein, we report the case of a breast cancer patient undergoing a modified radical mastectomy and sentinel lymph node biopsy for an extensive intraductal carcinoma, while under hypnosis analgesia and interpectoral block. The different steps of the prosthetic breast reconstruction and breast symetrisation were also performed with the same modalities of anesthesia.
TESTING SEMI-STRONG FORM OF MARKET EFFICIENCY: A STUDY OF NSE

In the major stock markets of the world, it is the forces of demand and supply that set prices. There are hundreds of analysts and thousands of traders, receiving new information on a company through electronic and paper media. The Efficient Market Hypothesis (EMH) implies that if new information is revealed about a firm it will be incorporated into the share price rapidly and rationally, with respect to the direction of the share price movement and the size of that movement. Market efficiency is directly or implicitly tested in the study, which is performed to identify stock price reaction to certain events such as budget announcement and credit policy announcement. It can be studied under weak form, semi strong form and strong form of Efficient Market Hypothesis. This paper is an attempt to study the weak and semi strong form of hypothesis that the prices or movements in the share prices are affected by past and publicly available information. The present study examined the behavior of daily stock returns for 10 prominent stocks listed on National Stock Exchange (NSE) from January 1, 2005 to December 31, 2005. Five major events were taken into consideration to evaluate the effect of publicly available information on the stock prices. The study revealed that the market instantaneously absorbs all relevant information as it becomes publicly available which indicates that the weak and semi strong forms are inefficient during the study period. The study depicted that the NSE is weak form efficient during the selected period. Finally, it concluded that stock market efficiency does not mean that investors have perfect powers of prediction; all it means is that the current level is an unbiased estimate of its true economic value based on the information revealed.
Correlating Size and Composition-Dependent Effects with Magnetic, Mössbauer, and PDF Measurements in a Family of Catalytically Active Ferrite Nanoparticles

The magnetic spinel ferrites, MFe2O4 (wherein ‘M’ = a divalent metal ion such as but not limited to Mn, Co, Zn, and Ni), represent a unique class of magnetic materials in which the rational introduction of different ‘M’s can yield correspondingly unique and interesting magnetic behaviors. Herein we present a generalized hydrothermal method for the synthesis of single-crystalline ferrite nanoparticles with ‘M’ = Mg, Fe, Co, Ni, Cu, and Zn), which can be systematically and efficaciously produced simply by changing the metal precursor. Our protocol can moreover lead to reproducible size control by judicious selection of various surfactants. As such, we have probed the effects of both (i) size and (ii) chemical composition upon the magnetic properties of these nanomaterials using complementary magnetometry and Mössbauer spectroscopy techniques. The structure of the samples was confirmed by atomic PDF analysis of X-ray and electron powder diffraction data as a function of particle size. These materials retain the bulk spinel structure to the smallest size (i.e. 3 nm). In addition, we have explored the catalytic potential of our ferrites as both (a) magnetically recoverable photocatalysts and (b) biological catalysts, and noted that many of our asprepared ferrite systems evinced intrinsically higher activities as compared with their iron oxide counterparts.
Dating Violence: A Review

Dating violence, which is considered as a type of interpersonal violence, is defined as the use of physical, verbal or emotional violence to each other in the relationship and imposing social restrictions on their behavior. The aim of this article is to determine the risk factors that increase the severity of dating violence, which is a common problem nowadays, to investigate its effects and the effectiveness of the protection programs. For this purpose, Google Scholar, PsycArticles and PsycInfo databases were searched. Research shows that dating violence is affected by many different risk factors such as alcohol use, past domestic violence and peer interactions. Although dating violence is seen in both sexes, it is seen that women are more victims than men. This may have negative physical, psychological and social effects such as anxiety, depression, suicide risk, substance and alcohol use, and low self-esteem. When the effectiveness of the programs developed to prevent dating violence and protect the victims were examined, significant differences were found between the intervention groups and the control groups.
A New Definition of Hip Geometry Measures to Evaluate Hip Fracture Risk

Background: Our goal was to test the influence of the anatomical position of the head in relation to the femoral neck on the quality of Hip Geometry (HG) for a better diagnosis of people running risk of femoral neck and trochanter fractures. The previously used measures of HG are defined by the position of the neck in relation to the femoral diaphisis. Methods: We tested HG measures with an anatomical (CN axis) and non-anatomical relation of the femoral neck and head (NN ́axis). The test we have performed on a clearly defined sample of 171 white females. Results: Femoral neck fracture: CNAL ≥ 78.88 mm, AUC 0.67, 95% CI 0.64-0.84, sensitivity 0.76 and specificity 0.58, p<0.001; CNTMA ≥ 47.33 mm, AUC 0.70; 95% CI 0.56-0.82, 0.69 and 0.67, p=0.001; CNS angle ≥ 127.5°, AUC 0,66, 95% CI 0.55-0.77, 0.57 and 0.69, p=0.01. NN ́AL ≥ 79.12 mm, AUC 0.66; 95% CI 0.55-0.78, 0.55 and 0.69, p= 0.008; NN ́TMA ≥ 44.20 mm, AUC 0.53; 95% CI 0.41-0.65, 0.43 and 0.67 p=0.668. NS angle ≥ 123.50°, AUC 0.59; 95% CI 0.47-0.72, 0.57 and 0.58, p= 0.149. Neither the measures CN axis nor NN ́ axis don’t diagnose the risk of a trochanter fracture. Conclusion: The measures of HG defined by an anatomical relation between the neck and head are better at diagnosing people running risk of femoral neck fractures than previously used measures. Hip Geometry doesn’t influence the biomechanics of trochanter fractures. Anatomical measures better evaluate the risk of femoral neck fractures than the previous. These measures are usable in lowering the amount and severity of femoral neck fractures.
Crystal structure of (E)-4-(2-(4-(diethylamino)phenyl)diazen-1-ium-1-yl)benzenesulfonate monohydrate

Abstract C16H21N3O4S, triclinic, P1̅ (no. 2), a = 8.402(2) Å, b = 9.035(2) Å, c = 11.692(3) Å, α = 102.382(4)°, β = 109.303(4)°, γ = 97.122(4)°, V = 799.7(3) Å3, Z = 2, Rgt(F) = 0.0412, wRref(F2) = 0.1080, T = 173(2)K.
A WEIGHT-SHARED CNN FOR UNSUPERVISED DENSE DEPTH PREDICTION AND CAMERA MOTION ESTIMATION

In most of the CNN-based methods, the predicted depth map usually can’t be clearly recognized. In this paper, an end-to-end CNN is proposed to predict depth and estimate camera pose from pairs of consecutive frames. There are two branches in the network, which share weights to increase the connection between dense map and camera motion. The network is designed and trained in an unsupervised manner with a newly proposed feature error to improve the depth accuracy of the environment structure. The feature error is computed by the intermediate feature maps to reduce the impact of the photometric noise. Experimental results on the KITTI datasets demonstrate that the proposed method can achieve better performance of dense map prediction and camera pose estimation compared with the state-of-the-art approaches.