Miracle-dz/UniFAR-FTUs huggingface dataset:
Aviation environmental policy and issues of timescale

Every operational, technological, and policy decision affecting aviation represents a potential tradeoff among economic efficiency and impacts to climate, air quality, and community noise. Furthermore, effects in these domains occur over different temporal and spatial scales and with different aleatoric and epistemic uncertainty. Thus, robust, fast, and flexible tools that value these impacts on a common scale such as monetized changes in net welfare are needed along with methodologically sound and appropriate analysis frameworks to inform decisionmaking. The objectives of this thesis are threefold: 1) to advance the modeling tools used to calculate and value aviation's impact on the environment; 2) to analyze realworld aviation environmental policies and advance policy decision-making support; and 3) to explore the underlying issues of timescales in policy modeling, to develop and make explicit the treatment of these timescales, and thereby to improve policy support best-practices. In support of the first objective, a model is presented for calculating the health impacts of aviation noise, particularly hypertension, myocardial infarction, and stroke to complement current modeling approaches of the willingness-to-pay for noise abatement. Also, advances are made to an existing simplified climate model for aviation by improving the representation of uncertainty, updating modeling components for both longand short-lived forcing agents, and developing a module to consistently model the life-cycle impacts of alternative fuels. Finally, a method for modeling the social costs of aviation lead emissions is developed. In support of the second thesis objective, three policy case studies are presented: aircraft noise certification, residential soundproofing and land acquisition, and general aviation lead emissions. The costs and benefits of different policies are evaluated for each case. Results are calculated with explicit accounting for scientific, modeling, and economic uncertainty and are presented considering a
Aberrant cortical development is driven by impaired cell cycle and translational control in a DDX3X syndrome model

Mutations in the RNA helicase, DDX3X, are a leading cause of Intellectual Disability and present as DDX3X syndrome, a neurodevelopmental disorder associated with cortical malformations and autism. Yet the cellular and molecular mechanisms by which DDX3X controls cortical development are largely unknown. Here, using a mouse model of Ddx3x loss-of-function we demonstrate that DDX3X directs translational and cell cycle control of neural progenitors, which underlies precise corticogenesis. First, we show brain development is highly sensitive to Ddx3x dosage; Complete Ddx3x loss from neural progenitors causes microcephaly in females, whereas hemizygous males and heterozygous females show reduced neurogenesis without marked microcephaly. In addition, Ddx3x loss is sexually dimorphic, as its paralog, Ddx3y, compensates for Ddx3x in the developing male neocortex. Using live imaging of progenitors, we show that DDX3X promotes neuronal generation by regulating both cell cycle duration and neurogenic divisions. Finally, we use ribosome profiling in vivo to discover the repertoire of translated transcripts in neural progenitors, including those which are DDX3X-dependent and essential for neurogenesis. Our study reveals invaluable new insights into the etiology of DDX3X syndrome, implicating dysregulated progenitor cell cycle dynamics and translation as pathogenic mechanisms.
Aplikasi Jago (Baca Dan Tulis Pego) Dengan Voice Recognition Berbasis Android

Pego adalah huruf Arab yang dimodifikasi untuk menuliskan bahasa Jawa, bahasa Indonesia, dan Bahasa Sunda. Sekilas tulisan pego memang mirip dengan tulisan arab hijaiyah seperti biasanya. Tetapi masih ada tambahan huruf dan kaidah penulisannya yang membuat peserta didik kesulitan dalam menyesuaikan kosa kata dalam bentuk bahasa Indonesia atau bahasa selainnya. Sekolah MI Darul Ulum II merupakan salah satu sekolah yang memiliki materi “Arab pego” sebagai muatan lokal. Pembelajarannya berupa metode pengajaran menulis di papan dalam mengenal huruf pego dan cara penulisan pego. Sayangnya, metode ini membuat peserta didik mengalami kesulitan dalam mengenal huruf pego dan fungsi bacaan huruf pego untuk penulisan bahasa Indonesia atau bahasa Jawa. Oleh karena itu dibutuhkan sebuah aplikasi yang dapat membantu peserta didik dalam proses belajar huruf pego. Penelitian ini bertujuan untuk membuat sebuah aplikasi media pembelajaran yang berbasis android dalam pembelajaran pego. Aplikasi dalam penelitian ini dikembangkan dengan menggunakan model pengembangan sistem waterfall. Aplikasi ini didesain dengan unfield modelling language (UML). Hasil dari penelitian ini adalah telah dibangun aplikasi pembelajaran jago (belajar menulis dan membaca pego) dengan voice recognition berbasis android menggunakan Adobe Flash Professional CS6. Aplikasi pembelajaran pego berbasis android ini dibangun dengan beracuan pada panduan baca tulis Arab-Melayu dan dengan suatu pengajaran menarik.
Mood Beta, Sentiment and Stock Returns in China

We examine the cross-sectional seasonality of stock excess returns in China. We find that stocks’ historical excess returns are positively related to their future excess returns under a congruent-mood period and negatively associated with their future excess returns under a noncongruent-mood period. Besides, stocks with larger mood beta tend to outperform during mood periods, and this impact is still significant after differentiating companies. Moreover, consistent with our hypotheses, mood beta has stronger explanatory power after China’s unique Split-Share Structure Reform and RMB Exchange Rate Reform. Finally, mood beta has stronger explanatory power compared to sentiment beta during ascending and descending mood months.
Hole-drilling method eccentricity error correction using a convolutional neural network

Hole eccentricity is an important error source when residual stress is measured via the hole-drilling method. The conventional ways to correct eccentricity error for hole-drilling residual stress measurement rely on complicated mathematical processes and are difficult to use. To overcome this shortcoming, this paper proposes a method that uses a convolutional neural network to correct for the hole-drilling method eccentricity error. First, the hole-drilling method measurement process in uniform biaxial stress field is simulated via the finite element method. The influence of the eccentric distance, eccentric angle, and stress ratio on the strain measurement error is discussed. Then, a convolutional neural network is trained using simulated data and the hole-drilling method strain measurement error is predicted for arbitrary eccentricity conditions. Finally, the residual stress is corrected by introducing the strain error into its equation. The simulated residual stresses of ten eccentric measurement points in predefined stress fields are corrected using this procedure to conducted numerical tests. The maximum error of simulated stresses decreased from 30.46% to −4.67% after correction. Therefore, the hole eccentricity has a significant influence on the residual stress measurement accuracy of hole-drilling method. The proposed correction method can effectively eliminate this error.
Cues that Work: Designing the Optimal Restaurant Crowdfunding Campaign in the US

ABSTRACT This study explores how restaurant entrepreneurs incorporate various intrinsic and extrinsic cues into the design of reward-based crowdfunding campaigns to maximize their probability of success. This study aims to identify the optimal levels of each of these cues to guide entrepreneurs’ strategic behavior. Based on the cue utilization theory and the concept of optimal arousal, this study collected restaurant project data from Kickstarter. Linguistic Inquiry and Word Count (LIWC) was also used to quantify linguistic cues in the project title. Linear and quadratic terms of cues were included in the logistic regression model. An optimal campaign should have 13 pictures, 2 videos, a detailed but succinct description, and many rewards. The project title should have a neutral and conservative style instead of being extremely positive.
Development and Application of Liquid Crystals as Stimuli-Responsive Sensors

This focused review presents various approaches or formats in which liquid crystals (LCs) have been used as stimuli-responsive sensors. In these sensors, the LC molecules adopt some well-defined arrangement based on the sensor composition and the chemistry of the system. The sensor usually consists of a molecule or functionality in the system that engages in some form of specific interaction with the analyte of interest. The presence of analyte brings about the specific interaction, which then triggers an orientational transition of the LC molecules, which is optically discernible via a polarized optical image that shows up as dark or bright, depending on the orientation of the LC molecules in the system (usually a homeotropic or planar arrangement). The various applications of LCs as biosensors for glucose, protein and peptide detection, biomarkers, drug molecules and metabolites are extensively reviewed. The review also presents applications of LC-based sensors in the detection of heavy metals, anionic species, gases, volatile organic compounds (VOCs), toxic substances and in pH monitoring. Additionally discussed are the various ways in which LCs have been used in the field of material science. Specific attention has been given to the sensing mechanism of each sensor and it is important to note that in all cases, LC-based sensing involves some form of orientational transition of the LC molecules in the presence of a given analyte. Finally, the review concludes by giving future perspectives on LC-based sensors.
Mechanical competition promotes selective listening to receptor inputs to resolve directional dilemmas in neutrophil migration

As neutrophils navigate complex environments to reach sites of infection, they may encounter obstacles that force them to split their front into multiple leading edges, raising the question of how the cell selects which front to maintain and which front(s) to abandon. Here we challenge chemotaxing HL60 neutrophil-like cells with symmetric bifurcating microfluidic channels, enabling us to probe the cell-intrinsic properties of their decision-making process. Using supervised statistical learning, we demonstrate that cells commit to one leading edge late in the decision- making process, rather than amplifying early pre-existing asymmetries. Furthermore, we use optogenetic tools to show that receptor inputs only bias the decision similarly late, once mechanical stretching begins to weaken each front. Finally, optogenetic attempts to reverse cell decisions reveal that, once an edge begins retracting, it commits to this fate, with the kinase ROCK limiting its sensitivity to inputs until the retraction is complete. Collectively our results suggest a “selective listening” model in which both actively protruding cell fronts and actively retracting cell rears have strong commitment to their current migratory program.
Towards Adaptive Fault Tolerance: From a Component-Based Approach to ROS

A system that remains dependable when facing changes (new threats, failures, updates) is resilient. In this paper, we report on an approach taking advantage of Component Based Software Engineering technologies for tackling a crucial aspect of resilient computing, namely the on-line adaptation of fault tolerance mechanisms. The second part of this paper shows how this approach can be implemented on ROS that is presently used for implementing automotive applications, e.g. ADAS. We illustrate the mapping of ideal components to ROS components and give implementation details of a fault tolerance design pattern that is adaptive at runtime. We finally draw the lessons learnt from our first experiments.
A refactoring approach to improve energy consumption of parallel software systems

Empowering application programmers to make energy-aware decisions is a critical dimension in improving energy efficiency of computer systems. Despite the growing interest in designing software development processes, frameworks, and programming models to facilitate application-level energy management, little is known on how to design application-level energy-efficient solutions for concurrent software running on parallel architectures. This is unfortunate for at least two reasons: (1) thanks to the proliferation of multicore CPUs, concurrent programming is a standard practice in modern software engineering; (2) a CPU with more cores (say 32) often consumes more power than one with fewer cores (say 1 or 2). However, application developers still do not understand how their code modifications impact energy consumption in a parallel system. Analyzing STACKOVERFLOW showed evidence that this is a real problem; Even though the interest in energy consumption issues is increasing over the years, developers still hold misconceptions and assumptions that are not always true. This lack of knowledge is primarily due to a lack of appropriate tools to measure/identify/refactor energy consumption hotspots. This thesis begins to bridge the chasm of the first problem — the lack of knowledge — by presenting an extensive experimental space exploration over two concurrent programming building blocks: (1) thread-safe collections and (2) thread management constructs. Through a list of findings that are not always obvious, we illuminate the relationship between the choices and settings of design decisions and energy consumption of parallel systems. This thesis then starts to bridge the gap of the second problem — the lack of tools. Lessons learned in our previous studies showed that ForkJoin tasks often operate on an indexable data structure, with subtasks operating only on part of this data structure. One naive solution is to copy part of the data structure and use it in the next computation. In a recursive framework such as ForkJoin, given an array-based representation, each recursive call will create n new arrays, where n is the width of forking. To address this, we derive a refactoring that, instead of copy part of the data structure, it shares it, allowing subtasks to operate on contiguous partitions of the data structure. We manually applied this refactoring into 15 open source projects. Our refactoring succeed in saving energy for each one of them (12% average saving). We sent the refactored versions to the project owner and, during a timeframe of 40 days, 7 out of 9 projects that replied to our patches have already accepted and merged them. Discussions during the merge process revealed that developers were not aware of this optimization. We then implemented this refactoring as an Eclipse plug-in so that other developers can (1) detect uses of copy where it would be beneficial to use sharing and (2) refactor the code in an automated way.
Discharge‐Modulated Soil Organic Carbon Export From Temperate Mountainous Headwater Streams

Erosion and riverine transport of organic carbon is an important component of the global carbon cycle, but the significance of this process for Earth's surface carbon budgets depends on the sources of carbon being mobilized. In this study, we aim to constrain how runoff‐driven erosion modulates the contribution of different carbon source endmembers, that is, bedrock, soil and vegetation, in three forested headwater catchments in the Swiss Prealps. The sources of organic carbon are determined using an inverse model based on bulk carbon isotope signatures and the abundances and distributions of long‐chain n‐alkane plant wax biomarkers in suspended sediments collected over a range of discharges. Despite landcover differences and contrasting bulk particulate organic carbon (POC) signatures, the increase of soil‐sourced organic carbon with runoff is similar in all three studied catchments. This apparent existence of common processes implies that export fluxes of soil organic carbon may be extrapolated to similar catchments. Overall, our analysis shows that runoff‐driven soil erosion in these alpine headwater streams is responsible for the export of at least 0.3 to 0.8 gC m−2 yr−1 as POC. Our study also shows that despite a significant variability in isotopic and molecular POC signatures at low runoff, all three catchments show a convergence of these signatures at higher discharges. Suspended sediment samples collected at above‐average runoff are hence most representative of overall endmember contributions.
Oral Submucous Fibrosis Patients Expressed Hypoxia Inducible Factor-1α (HIF-1α) in Saliva: A Biomarker for Detection of Malignant Transformation

Objective: Aim of this current study was to determine the malignant transformation associated with hypoxia inducible factor-1α among patients of oral submucous fibrosis (OSF). Study Design: This Retrospective study was carried from 1st January, 2021 to 31st December, 2021 at the Department of Dental Materials, Sardar Begum Dental College, Gandhara University, Peshawar Methods: There were forty five diagnosed patients of oral submucous fibrosis with ages 18-50 years were included in the current study. After taking informed consent for baseline details were recorded which includes age, gender, causes and symptoms of OSF. Inter Incisal Opening (IIO) of mouth among all the patients were measured. Hypoxia inducible factor-1α was observed among all the cases. Staining intensity of fibroblast and correlation of different grades of staining intensity with blood vessels were assessed in terms of mild, moderate and severe. SPSS 26.0 version was used to analyze complete data. Results: There were 32 (71.1%) males and 13 (28.9%) females in this study. 22.13±5.29 kg/m2 was the mean body mass index of patients with mean age 31.02±3.45 years. Most common cause was tobacco found in 20 (44.4%) cases, followed by smoking in 15 (33.3%) patients and areca nut found in 10 (22.2%) cases. Most common symptom was burning sensation, pain, ulceration and dry mouth. Twenty four (53.3%) patients had IIO level <27mm and >27mm level was in 21 (46.7%) patients. Mean blood vessels were 11.1±2.34 with majority of the cases had mild staining intensity in 23 (51.1%) cases. Mean fibroblasts were 42.23±5.64 and had mild staining intensity in majority cases 21 (46.7%). Conclusion: According to our study HIF-1α was an effective factor in the malignant transformation of oral submucous fibrosis. Aside from that, our findings revealed that OSF malignancy can be detected by the use of HIF-1 as a biomarker. Keywords: OSF, Hypoxia Inducible Factor-1α, Fibroblast, Staining Intensity, Blood Vessels
Accessibility challenges of e-commerce websites

Today, there are many e-commerce websites, but not all of them are accessible. Accessibility is a crucial element that can make a difference and determine the success or failure of a digital business. The study was applied to 50 e-commerce sites in the top rankings according to the classification proposed by ecommerceDB. In evaluating the web accessibility of e-commerce sites, we applied an automatic review method based on a modification of Website Accessibility Conformance Evaluation Methodology (WCAG-EM) 1.0. To evaluate accessibility, we used Web Accessibility Evaluation Tool (WAVE) with the extension for Google Chrome, which helps verify password-protected, locally stored, or highly dynamic pages. The study found that the correlation between the ranking of e-commerce websites and accessibility barriers is 0.329, indicating that the correlation is low positive according to Spearman’s Rho. According to the WAVE analysis, the research results reveal that the top 10 most accessible websites are Sainsbury’s Supermarkets, Walmart, Target Corporation, Macy’s, IKEA, H&M Hennes, Chewy, Kroger, QVC, and Nike. The most significant number of accessibility barriers relate to contrast errors that must be corrected for e-commerce websites to reach an acceptable level of accessibility. The most neglected accessibility principle is perceivable, representing 83.1%, followed by operable with 13.7%, in third place is robust with 1.7% and finally understandable with 1.5%. Future work suggests constructing a software tool that includes artificial intelligence algorithms that help the software identify accessibility barriers.
METHODOLOGY ENHANCEMENTS OF THE EDUCATIONAL PROCESS IN DSP PROGRAMMING COURSE

This paper presents a practical solution for intera ction between students and software/hardware system s in education. The development of science and the techn ology allowed significant enhancements to the metho ds in presentation of new materials to students. The main purpose of this research was for the students to g ain some basic insight into elementary techniques needed for design, implementation and merging of hardware and software components used in testing of the algorith ms for digital signal processing in real time. Main goal was to develop Digital Signal Blocks (DSP) which would be used as intuitive bridge between students and DS P systems by eliminating obscure software interface. Over the years it was established that students was te the majority of their time in classes on adopting softw are interface which leaves them with very little ti me to master the key principles in the curriculum. This i s especially true in the case of the embedded syste ms because there students must learn to work with seve ral software packets. The developed software system allows students to concentrate on just one graphica l interface which is intended to handle every aspec t of embedded system design – from algorithm simulation to the hardware implementation. Through the work wi th the students it was concluded that the developed DS P blocks presented very good assistance in educatio nal process. Since real hardware systems were used in t his case noise was introduced in the system which d oes not exist in simulation software and therefore this opt ion produced much larger capabilities for developme nt of the robust algorithms. The advantage of this approach l ies in the fact that the anchor point in education was transferred from the mere observation of the lectur e presentation to the active participation in the a ggregation of the new material.
The value of FDG PET/CT in the management of malignant melanoma: a retrospective study

Objectives: Positron Emission Tomography with Computed Tomography (PET/CT) is a valuable imaging method for the restaging of malignant diseases as well as the evaluation of treatment outcomes. As melanoma lesions are mostly FDG-avid, whole-body 18F-fluorodeoxyglucose (18F-FDG) PET/CT imaging modality can be used to determine the spread of the tumor. In the present study, we intended to share our clinical experience with FDG PET/CT in malignant melanoma patients under different kinds of treatment. Methods: In this retrospective study, the data sets of 122 patients who had surgical resection of known primary tumors, all of which were histopathology-proven malignant melanoma, were analyzed. All patients underwent baseline 18F-FDG PET/CT scan no sooner than 45 days and at least once after surgery. Clinical information, radiological imaging, histopathology, and treatment modalities were noted for all patients, and 18F-FDG PET/CT findings were examined. Results: All patients were histopathology-proven and 47 of them had acral lentiginous, 37 nodular, 23 amelanotic, and 15 atypical malignant melanoma. Local recurrence was detected by 18F-FDG PET/CT in 13 (10.6%; 3 male, 10 female) of the 122 patients, and the mean recurrence time after diagnosis was 3 ± 1.4 years. 10 patients with brain and bone metastases underwent radiotherapy. 19 patients with lung, bone, and hepatic metastases received chemotherapy and 22 patients immunotherapy. Conclusions: Malignant melanoma is a type of skin cancer that may involve any organ. In localized cases, complete surgical resection may be adequate for a cure. If diagnosed with the latter type, the whole body of the patient must be examined.