Miracle-dz/UniFAR-FTUs huggingface dataset:
Implementation of embedded real-time monitoring temperature and humidity system

Temperature and humidity are among the parameters that significant to the industrial and agricultural. Traditionally, these elements are monitored inefficiently through wired monitoring system that caused higher implementation and maintenance cost. In addition, the device to detect the temperature such thermometer is not suitable for real-time monitoring since it need a longer response time to measure. With the advent of wireless technology, the temperature and humidity are monitored remotely and effectively. This paper aims to describe the implementation of an embedded real-time temperature and humidity monitoring system, using Arduino for Internet of Things (IoT) application. The system integrates the Arduino node with a dashboard system call Node-FRED, which interfaced to the LoRa radio through the Things Network gateway. This IoT application is deployed on both indoor and outdoor environment, to investigate the relation between the temperature and humidity level in order to manage the environment at more comfort level.
Impact of Summative Assessment on First Year Medical Students' Mental Health

Objective: Studies have revealed that the prevalence of distress among medical student is higher compared to normal population and the main stressor was academic especially examinations. This study is interested in gathering data objectively on the impact of summative examination on the USM medical students’ mental health. Methods: This is a comparative pre and post cross-sectional study. A total of 260 first year medical students were selected as respondents for the first data collection whereas only 100 medical students were randomly selected for the second data collection. The 12 items General Health Questionnaire (GHQ-12) and Medical Student Stressor Questionnaire (MSSQ) were administered to measure stress level and stressor of the medical students. Stress levels of medical students were measured at two occasions; eight months prior to the examination as the baseline stress level and just after the last paper of the examination as the examination stress level. Result: A total of 213 students responded in the first session and 99 students in the second session. This study showed that the percentage of distressed medical students was significantly increased during summative examination; the baseline percentage of distressed medical students was 26.29% and the percentage of distressed medical students during the examination was 58.59% (X 2 = 30.2, p < 0.001). The mean stress level was found to be significantly increased during the examination; the baseline mean stress level was 2.41 and the mean stress level during examination was 4.39 (t = -5.72, p < 0.001). Binary logistic regression showed that medical students were at 3.97 time more risk to develop distressed compared to before the examination (Wald = 28.82, OR (CI 95%) = 3.97 (2.40, 6.56), p < 0.001). Conclusion: The percentage of distressed medical students during the examination was significantly higher compared to before the examination. The mean stress level was significantly high during the examination. Medical students were at high risk to develop distress during summative examination period.
Learning ship width and direction by convolutional neural networks without manual labelling

ABSTRACT Direction and width prediction have become hot topics in accurate ship location, while the resolution of remote sensing data has been increasing. In the current machine learning, demand for extensive manual labelling has become one of the biggest challenges to further improve tasks such as ship attribute prediction. To cope with this problem, in this paper, we propose a method to predict ship direction and width without manual labelling. To this end, pseudo-label generation approaches have been proposed for transfer learning with convolutional neural network (CNN). Experiments demonstrated that the pre-trained classification CNN features could preserve variational information for such attribute prediction. And the proposed pseudo-labels, which are even with limited qualities, could be efficient to train an accurate ship direction and width prediction model through fault-tolerant training by neural networks.
Distributed Blockchain-Based Trusted Multidomain Collaboration for Mobile Edge Computing in 5G and Beyond

Mobile edge computing (MEC) sinks computing power to the edge of networks and integrates mobile access networks and Internet services in 5G and beyond. With the continuous development of services, privacy protection is extremely important in a heterogeneous MEC system for multiserver collaboration. However, most of the existing schemes only consider the privacy of users or services other than the privacy of network topology. For the purpose of topology privacy protection, this article employs blockchain to construct heterogeneous MEC systems and adopts accommodative bloom filter as a carrier for multidomain collaborative routing consensus without exposing topology privacy. Blockchain is used to implement multiplex mutual trust networking and collaborative routing verification through the membership service and consensus mechanism. Experiments are conducted to evaluate the feasibility and performances of our scheme. The results indicate that the proposed scheme can highly improve the credibility and efficiency of MEC collaboration.
Soil microbial attributes and function across multiple scales in Neotropical Savanna

Savannas are the most sensitive ecosystems to future changes in land use and climate. Therefore, understanding of the factors underpinning savanna ecosystem function is urgently required for ecologically-relevant conservation and management. This thesis aims to address this knowledge gap, investigating how local conditions and landscape features influence soil microbial attributes, and the resistance and resilience of soil functioning within the three distinct vegetation types of the Brazillian Cerrado biome: Gallery forest, Veredas and Cerrado sensu stricto. Firstly, I evaluated how local vegetation characteristics and soil physico-chemical properties interact and influence soil microbial attributes (Chapter 2). Secondly, I investigated how landscape-scale anthropogenic disturbance and topography affect soil microbial community structure and enzyme activity (Chapter 3). I also assessed how soil CO2 emissions are related to microbial attributes and topography, and the resistance and resilience of soil functioning (respiration) of the vegetation types in response to drought and drying-rewetting (Chapter 4). Lastly, I conducted an experiment to investigate the mechanisms underpinning C mineralisation in rewetted soils from the different Cerrado vegetation types (Chapter 5). At the local scale, I found different patterns in above- and below-ground interactions within the three vegetation types. Soil physico-chemical properties strongly affected soil microbial attributes in Gallery forests and Veredas, whereas vegetation characteristics were the main determinant in Cerrado sensu stricto. At the landscape scale, I found topography to be the major predictor of microbial attributes in all vegetation types, and that anthropogenic disturbance influences soil microbial communities both positively and negatively. Veredas soils were the most resistant to drought, while Gallery forests soils were the most resilient in their reponse to rewetting after drought. I also discovered that soil organic matter quality combined with nutrient availability influenced different mechanisms underpinning soil C stock and release to the atmosphere across the different Cerrado types. Based on these findings, I discuss the importance of flooding regimes in the wetland vegetation types (Gallery forest and Veredas) for ecosystem functioning, and implications for future land-use and climate change in the Cerrado biome (Chapter 5). I emphasize the need for Brazilian environmental legislation to prioritize the integral conservation of periodically flooded areas.
A General Approach to Fairness with Optimal Transport

We propose a general approach to fairness based on transporting distributions corresponding to different sensitive attributes to a common distribution. We use optimal transport theory to derive target distributions and methods that allow us to achieve fairness with minimal changes to the unfair model. Our approach is applicable to both classification and regression problems, can enforce different notions of fairness, and enable us to achieve a Pareto-optimal trade-off between accuracy and fairness. We demonstrate that it outperforms previous approaches in several benchmark fairness datasets.
Drivers of underlying inflation in the euro area over time: a Phillips curve perspective

In this article we review the evolution of euro area HICP inflation excluding energy and food since the Great Financial Crisis through the lens of the Phillips curve. This period is particularly interesting, as the euro area experienced two recessions (in 2008-2009 and 2011-2014) and a protracted episode of low inflation from 2013 onwards. We estimate a large set of Phillips curve models for the euro area and review the interpretation of inflation developments that they provide over time. We highlight both the advantages and some of the limitations of this type of analysis. We find that our models can account for much of the weakness in underlying inflation between 2013 and mid-2017, but that they cannot account for the most recent weakness in underlying inflation. JEL Classification: E31, E58
ANALISIS PENERAPAN METODE ACTIVITY BASED COSTING TERHADAP TARIF RAWAT INAP PADA RUMAH SAKIT UMUM KASIH BUNDA

ABSTRACT - Use of the estimated cost of hospitalization rates were based on General Hospital competitor rates imposed by Mother Love General Hospital, causing the gap between the cost of the facilities provided, and therefore to reduce this gap required a method to calculate the rates can provide cost information accurately. Overcome this method of activity-based costing can be used because the charge in accordance with the selection of activities undertaken appropriate cost driver. The method used is descriptive quantitative method, with the presentation of the data in the form of the costs in the form of numbers processing using mathematical formulas. The results showed that rates calculated using activity based costing method is greater than the rate that had been used by Mother Love General Hospital of Rp 454,226, while the rates in effect at the General Hospital Mother Love Rp 125,000. This is because rates Kasih Bunda Hospital is not a standard cost estimate for the result obtained from another hospital rates, while the rates based on activity based costing methods derived from calculations based on the activities performed in the inpatient activities. Keywords: activity based costing method, hospitalization rates
Deep Learning Methods On Neutron Scattering Data

Recently, by using deep learning methods, a computer is able to surpass or come close to matching human performance on image analysis and recognition. This advanced methods could also help extracting features from neutron scattering experimental data. Those data contain rich scientific information about structure and dynamics of materials under investigation. Deep learning could help researchers better understand the link between experimental data and materials properties. Moreover,it could also help to optimize neutron scattering experiment by predicting the best possible instrument configuration. Among all possible experimental methods, we begin our study on the small-angle neutron scattering (SANS) data and by predicting the structure geometry of the sample material at an early stage. This step is a keystone to predict the experimental parameters to properly setup the instrument as well as the best measurement strategy. In this paper, we propose to use transfer learning to retrain a convolutional neural networks (CNNs) based pre rained model to adapt the scattering images classification, which could predict the structure of the materials at an early stage in the SANS experiment. This deep neural network is trained and validated on simulated database, and tested on real scattering images.
Display Transmitter Link Controller Design Technology for Linux OS

The main purpose of the paper is to develop a driver architecture for a display transmitter link controller when the controller has its own registers and memory. The developed architecture should reduce update changes in the implementation code and should not require any special tools or methods to develop its implementations. The paper analyzes publicly accessible DRM subsystem-based drivers and identifies two main architecture types, which serve as a basis for the majority of open source drivers. It also analyzes the strengths and weaknesses of the architecture types to achieve the above purpose. The identified architecture types were used to build a new architecture that has the strengths of both types, which allows achieving the purpose. The paper also describes the developed driver debugging methods, which are based on the architecture under analysis and take into account the possibility of errors in the hardware, absence or insufficiency of controller documentation and incomplete emulation of the devices being developed. The results were evaluated during development of the DisplayPort driver for a perspective controller, and the driver was tested together with a prototype device and a monitor supporting the DisplayPort 1.1 standard. The results of this paper can be used to create new transmitter link controller drivers for Unix-like systems both when a production state controller exists and when doing parallel development of a new controller and a driver for it.
Emotions and Affective Polarization: How Enthusiasm and Anxiety About Presidential Candidates Affect Interparty Attitudes

In the context of an increasingly divided populace, this article considered how the emotions (enthusiasm and anxiety) partisans feel toward U.S. presidential candidates may heighten or diminish affective polarization. In Study 1 (American National Election Studies [ANES] 2008–2009 panel data), we found that enthusiasm for the in-group candidate and anxiety about the out-group candidate were related to higher levels of affective polarization, whereas enthusiasm for the out-group candidate was related to lower levels of affective polarization. In Study 2 (2016 panel data), we found that in-group enthusiasm was related to higher levels of affective polarization and out-group enthusiasm was related to lower levels of affective polarization, but neither in-group nor out-group anxiety was significantly related to affective polarization. These findings highlight that enthusiasm about out-group candidates may have a unique ability to disrupt affective polarization and that it is important to consider the source of an emotion response, not just the type of emotion.
Neoplastic Brain, Glioblastoma, and Immunotherapy

IGF-I, insulin-like growth factor 1, is present in normal fetal/neonatal brain development and reappears in the mature brain participating in the development of malignant tumor, glioblastoma multiforme. Targeting the IGF-I system has emerged as a useful method to reduce glial malignant development. Downregulation in the expression of IGF-I using antigene anti-IGF-I technology (antisense, AS, and triple helix, TH) applied in glioma cell culture established from glioblastoma biopsies induces the expression of B7 and MHC-I antigens in transfected cells (immuno-genicity). The transfected cancer cells, “vaccines,” after subcutaneous injection, initiated an immune response mediated by T CD8+ lymphocytes, followed by tumor regression (immunotherapy). The median survival of patients treated by surgery followed by radiotherapy and immunotherapy was 21–24 months. On the other side, the experimental work has demonstrated that IGF-I AS or TH transfected tumor cells fused with activated dendritic cells, DC, showing more striking immunogenic character. Using IGF-I TH/DC “vaccination,” the efficiency in suppressing rat glioma tumors is not only relatively higher than that obtained using IGF-I TH cells but is also more rapid.
STUDIES ON THE EFFECT OF QUERCETIN ON DIABETIC WOUND AND HYPERTENSION IN RATS

Title of the Thesis : Studies on the effect of quercetin on diabetic wound and hypertension in rats Name of the Student & Registration No. : Mahrukh Ahmad (J-12-D-42-V) Major Subject : Veterinary Pharmacology and Toxicology Name and Designation of Major Advisor : Dr. Mudasir Sultana Professor and Head, Division of Veterinary Pharmacology and Toxicology, F.V. Sc & A.H, R.S. Pura, Jammu. Degree to be awarded : Ph.D (Veterinary Pharmacology and Toxicology) Year of award of Degree : 2016 Name of the University : Sher-e-Kashmir University of Agricultural Sciences & Technology of Jammu (J&K) The present study was designed to evaluate the ameliorative effect of quercetin on streptozotocin-induced-diabetes, diabetic wound and DOCA salt induced hypertension in Wistar rats. Rats of 150-200g body weight were divided into six groups of six animals each and were subjected to various daily oral treatment regimes for 21 days to determine the effect of quercetin on diabetic wound healing. For evaluating the effect of quercetin on hypertension male Wistar rats were divided into four groups of six animals each and were subjected to various daily oral treatment regimes for six weeks. Oral administration of quercetin @100mg/kg B.W for 21 days in diabetic rats normalized the altered blood glucose, TC, HDL, triglycerides, LDL, protein profile, plasma urea nitrogen, creatinine and antioxidant biomarkers (MDA, SOD, CAT, GST, GPx). Topical application of quercetin ointment (15%) on the excised wound in diabetic wistar rats was sufficient enough to heal the wound area. Hypertension was induced in uninephrectomized wistar rats by weekly twice subcutaneous injection of DOCA @25mg/kg B.W for six consecutive weeks. Treating the hypertensive rats with quercetin @20 mg/kg B.W for six weeks significantly reduced (P<0.05) the mean arterial pressure. Furthermore, the lipid profile was improved along with other biochemical (plasma urea nitrogen, plasma creatinine, SGOT, SGPT) and oxidative stress parameters (MDA, CAT, SOD, GST, GPx). Therefore, it is concluded that quercetin @ 100mg/kg B.W has antidiabetic potential. Wound healing property has been excellently produced by 15% topical application alone and 15% topical application + 100mg/kg B.W orally. Quercetin @ 20mg/kg B.W for six weeks in rats was sufficient enough to reduce DOCA-salt induced hypertension.
Yesterday's Monsters: The Manson Family Cases and the Illusion of Parole

Seo writes, “The contradiction of the automobile as both the preeminent symbol of American values and an object of extensive policing threw into sharp relief the vexing conundrum of discretionary policing in a society based on the rule of law” (159). Since Prof. Seo’s book was released, that conundrum has become, if anything, even more vexing. When I finished Policing the Open Road, I was left contemplating the role the automobile will play in the next evolution of American society, the changes that will occur against the backdrop of board public skepticism of policing as a mode of governance and the increasingly availability of ever-more sophisticated autonomous vehicles. Policing the Open Road does not attempt to answer those questions, but it gives readers a firm historical foundation for thinking about the answers.
3D breast surface reconstructions from consumer-grade RGB-D cameras

Breast cancer is one of the most prevalent yet increasingly treatable cancer types. Clinical studies are suggesting a significant impact of breast cancer treatment on female patients’ wellbeing and quality of life. With the oncological prognosis for mastectomy being on par with breast-conserving surgery, the latter still does lead to poor or suboptimal results in nearly a third of cases. Geometric 3D models of the breast have the potential to aid planning, assessment and prediction of treatment but require sustaining costly infrastructure-heavy commercial scanning solutions. This cross-disciplinary work within the scope of a European project investigates recently marketed depth consumer cameras as low-cost easy-to-operate imaging devices for dense 3D breast surface reconstruction. Clinical data acquisition software in accordance with a predefined protocol is implemented and deployed. Preliminary breast surface models from extending a state-of-the-art static-scene reconstruction method are validated on synthetic, phantom and clinical data. Contemporary publicly available reconstruction frameworks from the computer vision and robotics community are subsequently evaluated. Their shortcomings with respect to the characteristics of the captured breast data are addressed in a new tailored non-rigid reconstruction pipeline. Favourable accuracy and precision are underpinned by an extensive clinical data validation including a breast volume comparison study against the gold standard.
Dosimetric comparison between 10MV-FFF and 6MV-FFF for lung SBRT

Plans were prepared by using same non-coplanar fields and physical parameters in 6MV-FFF and 10MV-FFF energies for fourteen lung Stereotactic Body Radio Therapy (SBRT) patients. In two plans which have different energies, critic organ doses, PTV doses, quality of plans (Gradient Index (GI), Homogeneity Index (HI), Conformity Index (CI)) and Monitor Unit (MU) values were compared. Quality controls were performed with 2D-Array Iba MatriXX Evolution® dosimetry system for each plans. As a results, plan with 6MV-FFF energy give better results in terms of CI and GI values. In this way, when more conformal dose distributions were provided, there was a rapid dose decrease at out of target volume. Lower MU values were obtained in plans which was prepared with 10MV-FFF energy. In plan with 10MV-FFF energy lower MU values are obtained. Lower values in heart and spinal cord doses are founded and better results are obtained in Body and Ipsa-Lung V5, V10, V20 values with 6MV-FFF energies. When differences were very small in volume which were taken low dose (V5), these differences increased in volume which were taken high dose (V20). High dose rates can be reached by both two unfiltered energies and can be used in lung SBRT.Plans were prepared by using same non-coplanar fields and physical parameters in 6MV-FFF and 10MV-FFF energies for fourteen lung Stereotactic Body Radio Therapy (SBRT) patients. In two plans which have different energies, critic organ doses, PTV doses, quality of plans (Gradient Index (GI), Homogeneity Index (HI), Conformity Index (CI)) and Monitor Unit (MU) values were compared. Quality controls were performed with 2D-Array Iba MatriXX Evolution® dosimetry system for each plans. As a results, plan with 6MV-FFF energy give better results in terms of CI and GI values. In this way, when more conformal dose distributions were provided, there was a rapid dose decrease at out of target volume. Lower MU values were obtained in plans which was prepared with 10MV-FFF energy. In plan with 10MV-FFF energy lower MU values are obtained. Lower values in heart and spinal cord doses are founded and better results are obtained in Body and Ipsa-Lung V5, V10, V20 values with 6MV-FFF energies. When differences were very sma.