Miracle-dz/UniFAR-FTUs huggingface dataset:
Are Older Adults’ Leisure Patterns Consistent with the Active Ageing Model? The Influence of the Ageist Stereotypes

More and more studies indicate that leisure plays a fundamental role in active ageing. Our study describes the current leisure patterns of older adults, comparing them with other age groups. Consequently, 445 adults, stratified by age (young, middle-aged and older adults), were selected and subsequently administered a set of tests. The results indicate that older people claim having more time for their leisure activities; however, the diversity of activities performed is lower, showing a negative gradient based on age. The leisure patterns of older people reflect a predominance of passive leisure, little cultural leisure time and moderate levels of social and physical leisure activities. Older people’s leisure seems to be influenced by ageist stereotypes and attribution biases. Our findings imply that these results could be used to design and implement programs aimed at promoting leisure styles that contribute to increase active ageing.
T.U.E.S.D.A.Y (Translation Using machine learning from English Speech to Devanagari Automated for You)

In today ' s globalized world, one thing that acts as a barrier to healthy information exchange is language. On top of that, with the onset of technologies such as YouTube and Facebook making it easy to share knowledge with people all around the world, language can impede that flow of information. If someone in India wants to access a piece of content in written form from another country, they can make use of services such as Google translate. However, the same cannot be extended for any piece of content which is rendered in an audio-visual medium since no such apparatus has been developed which can help people comprehend the content of that specific type. Specifically, students have experienced this first-hand when they try to access content from other universities but the medium of language is something that they are not well-versed in. With these issues in mind, this group is trying to build an automatic voice dubbing system: a speech-to-speech translation pipeline which can help users easily understand other users without the worry of language barrier. The model is called T.U. E.S. D.A. Y. (Translation Using machine learning for English Speech to Devana-gari Automated for You) and is divided into three conversion modules: English speech to English text, English text to Devanagari text, and finally Devanagari text to Hindi speech. These modules work together in tandem to ensure an integrated model as a whole.
“It’s Never Too Late”: High School Counselors’ Support of Underrepresented Students’ Interest in STEM

The purpose of this study was to contribute to the literature surrounding school counselors and their support of underrepresented high school students who are interested in science, technology, engineering, and math (STEM). The influence of context on school counseling was also explored, in particular practicing during the COVID-19 pandemic. Through this phenomenological study, nine high school counselors were individually interviewed, and four themes emerged. These themes were: (a) professional knowledge surrounding issues of diversity in STEM, (b) training related to the needs of underrepresented students in STEM, (c) active engagement in supporting underrepresented students’ STEM career interests, and (d) barriers related to supporting underrepresented students’ STEM interests. This article includes implications for (a) how school counselors can support underrepresented students’ STEM interests, particularly during the COVID-19 pandemic; (b) how counselor educators can contribute to STEM-related research and training; and (c) how school administrators can support school counselors’ STEM initiatives.
Using Machine Learning To Understand Suicide: A New Approach To Classifying Australian Coroner’s Court Decisions

We aimed to demonstrate how a large collection of publicly accessible Australian Coroner’s Court case files (n=4459) (2009-2019) can be automatically classified for determination of death by suicide, presence of mental health disorder and sex of deceased via Natural Language Processing (NLP) methods - supervised machine learning and unsupervised dictionary-based and string search based approaches. We achieved superior levels of accuracy in the machine learning classification (Gradient Boosting vs. Random Forest baseline) of deaths by suicide of 83.3% (sensitivity = 85.1%, Specificity = 79.1%) and an accuracy of 98.3% for the dictionary-based classification of mental health disorder, as defined by the OCD-10 (sensitivity = 99.0%, specificity = 97.9%). Our machine learning approach automatically classified 24.2% (1078/4459) of the case files as referring to deaths by suicide while 63.7% (2940/4459) where classified as exhibiting a mental health disorder1. We employed a two-stage machine learning approach involving feature engineering, followed by predictive modelling in the second. Feature engineering involved several steps including removal of low value text, parts of speech analysis, term document weighting and topic clustering. Predictive classification involved extensive hyperparameter tuning to yield the most accurate model. We validated our models against a manually pre-coded subsample of case files, and also via binary logistic regression to test the contribution of each classified mental health disorder against determinations of deaths by suicide according to extant literature. This validation step confirmed elevated odds of suicide attributed to diagnoses of Depression, Schizophrenia and Obsessive Compulsive Disorder. Finally, we offer a short case study to demonstrate the efficacy of our approach in investigating a subset of case findings referring to suicides resulting from family violence. We offer a proof of concept model that demonstrates an objective and scalable approach to the analysis of legal texts. The use of NLP methods in analysing Coroner's Court case findings has important implications for the ongoing development of a real-time surveillance of suicide system in Australia.
Personality And Criminal Trajectories In Young Adults Held In Chilean Prisons

Aim: The study is framed in evolutionary criminology, analyzing the role of personality, risk and criminal history in the development of persistent criminal trajectories observed in young adulthood. Personality variables observed with the Millon Clinical Multiaxial Inventory (MCMI-III), criminal risk levels according to the Risk-Need-Responsivity model (RNR), and criminal trajectory according to the Multidimensional Model of Differentiated Intervention with Adolescents (MMIDA) are identified. Method: 200 young men (18 to 26 years old) held in two Chilean prisons took part. All voluntarily responded to two instruments (MCMI-III and EDA-A) in individual applications and penitentiary professionals assessed the risk instrument (IGI). Results: A cluster analysis was performed with the scores obtained on the MCMI-III, establishing 5 groupings that define and describe risk levels and criminal history, comparing them conceptually with the typology of the MMIDA. Discussion: It was concluded in 4 clusters that central characteristics of the types defined by the MMIDA in adolescents are preserved, whereas in the fifth differences attributable to neuropsychological maturation processes inherent to the age are observed. The results are discussed, demonstrating the need to recognize the period of youth, beyond 18 years, as a phase that requires specialized interventions from the youth penal system, given their greater neuropsychological plasticity and receptivity to interventions.
Determination of Suitable Nursery Growth Media for Cardamom (Eletteria cardamomum Maton.) Seedlings at Teppi, Southwestern Ethiopia

Cardamom is mainly growing for its dry capsule used as a flavoring agent for food, beverages, medicinal, and source of income for the smallholder farmers in southwestern Ethiopia. Despite its advantages, the production and productivity of the crop hindered by several factors, for instance, poor agronomic practices, poor crop breeding, and management, from nursery to the main field of production. Therefore, a nursey-based experiment was conducted to identify the appropriate growth media ratios for cardamom seed germination, seedling uniformity, and vigor at Tepi, Southwestern Ethiopia. Gene cardamom variety was evaluated in six different growth media types namely; Fine Sandy Soil (FS), Forest Soil (ForS), FS: ForS (1:1), FS: DCH (Decomposed Coffee Husk) (1:1), ForS: DCH(1:1), and FS:ForS: DCH(1:1:1) and laid out in randomized complete block design with three replications. The result revealed that better cardamom seedling growth performance and vigor were obtained from a 1:1 ratio of decomposed coffee husk + forest soil growth media. Therefore, from the result, we concluded that the mixture of decomposed coffee husk + forest soil (1:1) can be used for better cardamom seedling establishment at Tepi and similar agroecology of Ethiopia. Future, studies should focus on the seedling obtained from this soil media mixture performance in the field for yield and yield components.
Quality Enhancement of Tapioca Starch Gel using Sucrose and Xanthan Gum

Abstract The quality of starch gel could be enhanced by sugar and hydrocolloid. Sucrose (0, 10 % and 20 %) and xanthan gum (Xan) (0.3125 %) were added in the tapioca starch (TS) gels (25 %w/w TS and TS/Xan gels) for quality investigation. Sucrose increased gelatinization temperatures of starch mixtures. Moisture content and water activity decreased with increasing sucrose content and Xan addition. Freeze–thaw stability of TS and TS/Xan gels with and without sucrose was evaluated. Sucrose and Xan decreased water separation from repeated freeze–thaw cycles. A regression model for predicting water separation from Xan, sucrose and selected freeze–thaw cycle was developed and showed a good predictability. After keeping the TS and TS/Xan gels at 5 °C for 7 and 14 days, the hardness of TS and TS/Xan gels increased with increasing sucrose content but was retarded by adding Xan (p<0.05), suggesting Xan impeded the structure formation contributed from amylose molecule association during cold storage.
Utilizing pre-determined beam orientation information in dose prediction by 3D fully-connected network for intensity modulated radiotherapy.

Background Although the effect of pre-determined beam orientation on dose distribution of intensity modulated radiotherapy (IMRT) has been well-documented, its impacts on dose prediction are less investigated. In this study, the direction map of beam orientation was incorporated into our proposed deep-learning network and utilized in dose prediction of IMRT plans consisting of multiple static fields. Methods The direction map was used to characterize the radiation path through region of interest along a beam orientation. Besides, the distance map was used to characterize the spatial distribution between organs at risk (OARs) and planning target volume (PTV). The input of prediction model consisted of CT image, mask image (for PTV and OARs), distance map, and direction map. The output of prediction model was the estimated dose distribution in three dimensions. A 3D fully-connected network composed of a down-sampling encoder and an up-sampling pyramid decoder was trained based on the calculated 3D dose distributions obtained from a treatment planning system. The voxel-level mean absolute error (MAE), dosimetric metrics, and dose-volume histogram were employed to assess the quality of the estimated dose distribution. Performance of the prediction model was evaluated in two aspects. First, the effectiveness of the new features, direction map, distance maps, and pyramid decoder on prediction accuracy of model were assessed. Second, the proposed model was compared with the other three published prediction models, 3D UNet, ResNet-anti-ResNet, U-ResNet-D for inter-model evaluation. Results The improvement of prediction accuracy was 0.38 with the input of direction map and 0.43 with the input of distance map. Our proposed model achieved the least MAE (3.97±1.42) compared with the other three models: (5.37±1.51) for ResNet-anti-ResNet, (4.45±1.52) for U-ResNet-D, and (4.53±1.72) for Unet-3D. Conclusions The preliminary result demonstrated that the prediction accuracy of the proposed model was higher than those of the other three state-of-the-art prediction models. The introduction of direction maps, distance map, and pyramid decoder can effectively improve the performance of the current deep-learning network-based prediction models.
Digital Twin for Supply Chain Coordination in Modular Construction

Over the past decades, the construction industry has been attracted to modular construction because of its benefits for reduced project scheduling and costs. However, schedule deviation risks in the logistics process of modular construction can derail its benefits and thus interfere with its widespread application. To address this issue, we aim to develop a digital twin framework for real-time logistics simulation, which can predict potential logistics risks and accurate module arrival time. The digital twin, a virtual replica of the physical module, updates its virtual asset based on building information modeling (BIM) in near real-time using internet of thing (IoT) sensors. Then, the virtual asset is transferred and exploited for logistics simulation in a geographic information system (GIS)-based routing application. We tested this framework in a case project where modules are manufactured at a factory, delivered to the site via a truck, and assembled onsite. The results show that potential logistical risks and accurate module arrival time can be detected via the suggested digital twin framework. This paper’s primary contribution is the development of a framework that mediates IoT, BIM, and GIS for reliable simulation which predicts potential logistics risks and accurate module delivery time. Such reliable risk prediction enables effective supply chain coordination, which can improve project performance and the widespread application of modular construction.
Executive Functions of BoP Consumers: Research Propositions, Conceptual Framework and Implications for Marketing Strategies for BoP Markets

Abstract Although extant literature has studied consumers at the bottom of the pyramid (BoP) extensively, there seem to be some lacunae in terms of a deeper understanding of the cognitive peculiarities of low-income consumers owing to their resource-lean environments and childhood uncertainties. In this paper, we attempt to address this gap by focusing on poverty-induced idiosyncrasies in a set of vital cognitive processes called executive functions (EFs). Specifically, we exlore the possible impact of such anomalies in EFs on a BoP consumer’s information processing abilities, decision-making processes, and consumption behaviors, through a series of propositions and a conceptual framework. The focus is on two core EFs, inhibition and working memory, which tend to make BoP consumers susceptible to persuasive messages, while lacking sufficient self-control, goal-directed behavior, analogy-processing and comparative evaluation abilities. We then present several managerial, policy and research implications of the study.
Multi-Band Transceiver for Tracking Application

Conventional Transceivers are designed using particular wireless technology and thus works in a specified range. This paper presents data transmission over Encrypted Multiband Transceivers which makes use of different wireless communication technologies, Encryption and GPS is used to securely communicate an image or other kinds of digital information with efficiency. It uses dynamic switching which is depending upon the distance, network, receiver sensitivity etc. Transceiver communication protocols are discussed with the help of software implementation and their algorithms.
Herméneutique et joueur modèle : Interpréter le mythe et le fait religieux dans la série Soulsborne de From Software

Affronter le probleme de la presence des mythes et du religieux au sein de la serie Soulsborne – designation commune aux derniers jeux du developpeur From Software – dans laquelle les motifs et renvois hypertextuels s’y referant abondent, presuppose de s’etre livre a un examen psycho-cognitif du joueur modele souhaite pour ces jeux. Une telle analyse nous permet de mettre en perspective l’importance fondamentale de la capacite hermeneutique d’un tel joueur, confronte a l’absence de referent narratif. Nous soutenons en cela que les dimensions religieuses et mythologiques demeurent les leviers fictionnels centraux a disposition du joueur, et dont il convient de dessiner les contours afin d’apprehender et d’interpreter ces univers diegetiques.
Race to the Door - A Goldfinger Attack on Proof of Work Cryptocurrencies

Goldfinger attacks aim to crash the value of a target cryptocurrency by undermining the underlying consensus protocol, utilizing the majority of the voting power in the system. In a Proof of Stake (PoS) context, where voting power is based on the amount of cryptocurrency held, this can be achieved in the form of a buy-out attack, where a majority of the target currency is purchased. In this context, the Race to the Door (RTTD) effect was described, which leads to more and more holders exiting the target currency before it becomes worthless. This effect reduces the price of further voting stake, rendering the attack cheaper the more it progresses. This thesis aims to show that a Race to the Door style attack is also technically possible in a Proof of Work (PoW) context without acquiring a majority of the voting power (i.e., hash rate). For this purpose, the technical feasibility and cost of such an attack are investigated on the example of Ethereum. First, a system model for RTTD attacks on PoW cryptocurrencies is presented to provide an overview. The attack is thereby divided into the phases preparation, race and attack. To demonstrate the technical feasibility, these phases are implemented in the form of smart contracts on Ethereum. For the attack phase, three variants are presented, each realizing a different denial of service attack. For this purpose, in-band payments are used to incentivize either the triggering of additional transactions or the creation of empty blocks by miners. To estimate the costs of the proposed attack variants, an empirical analysis is performed, where transaction data of historical congestion phases of the Ethereum blockchain are examined. Based on the results, the estimated costs of the attack variants are calculated and compared. The hourly costs of Blocking transactions using transaction triggering are around 870 Ether. Incentivizing miners to leave one-third of the blocks empty costs about 790 Ether per hour. The thesis shows that Race to the Door attacks are also technically feasible in the context of PoW cryptocurrencies. The cost of the attack hereby depends on its intensity and duration. The intensity can be configured at the attack phase, and the duration depends on the amount of currency available for the attack.
Memory Loss induced by Aspartame in Albino Rats: Study on neurobehavioral changes

Objective : Aspartame (ASP) consumption in various food and beverage products has generated a lot of controversy on safety. Many reports, ASP caused deterioration of health condition likes diabetes, psychiatric disorders, memory loss, etc. This study aimed to investigate the optimization duration of ASP to induce memory loss in Sprague Dawley rats. Methods : The ASP was administered 40 mg/kg BW orally for 28 days in rats. Analysis of memory loss by neurobehavioural changes including latency time, length of track, per cent time and frequency target quadrant using Morris Water Maze (MWM) at day 14, 21, 28, and 24 hours after the last treatment. Results: The administration of ASP showed the time-dependent changes for each indicator of neurobehavioural. The results demonstrated during 28 days of induction showed a significant decrease in latency time, length of track, per cent time and frequency target quadrant. Conclusion : From the results, it can be concluded administration of ASP during 28 days induce neurobehavioural changes related to memory loss in rats. Abstrak: Objektif: Penggunaan aspartame (ASP) sebagai pemanis buatan yang banyak terdapat pada makanan, dan minuman menimbulkan berbagai kontroversi dalam hal keamanan. Berbagai data menunjukkan ASP dapat menyebabkan gangguan kesehatan seperti diabetes, gangguan psikiatrik, penurunan fungsi memori, dll. Penelitian ini bertujuan untuk menentukan waktu durasi penggunaan ASP yang dapat menyebabkan gangguan fungsi memori pada tikus Sprague Dawley. Metode:ASP diberikan secara oral pada tikus dengan dosis 40 mg/kg BB selama 28 hari. Analisis terhadap fungsi memori dilakukan dengan adanya perubahan perilaku pada hewan, meliputi waktu latensi, Panjang lintasan, persentase waktu dan frekuensi kuadran menggunakan Morris Water Maze (MWM) setelah 24 jam setelah pemberian pada hari ke 14,21, 28. Hasil: Pemberian ASP menunjukkan adanya perbedaan waktu pada setiap indicator perilaku. Pemberian selama 28 hari menujukkan adanya perbedaan signifikan pada penurunan waktu latensi, Panjang lintasan, persentase waktu dan frekuensi kuadran. Kesimpulan: Berdasarkan hasil, pemberian ASP selama 28 hari dapat menyebabkan adanya perubahan perilaku yang berkaitan dengan fungsi memori pada tikus.
Outcomes of Lymph Node Dissection in Nephroureterectomy in the Treatment of Upper Tract Urothelial Carcinoma: Analysis of the ROBUUST Registry

Purpose: We sought to evaluate outcomes of lymph node dissection (LND) in patients with upper tract urothelial carcinoma. Materials and Methods: We performed a multicenter retrospective analysis utilizing the ROBUUST (for RObotic surgery for Upper Tract Urothelial Cancer Study) registry for patients who did not undergo LND (pNx), LND with negative lymph nodes (pN0) and LND with positive nodes (pN+). Primary and secondary outcomes were overall survival (OS) and recurrence-free survival (RFS). Multivariable analyses evaluated predictors of outcomes and pathological node positivity. Kaplan-Meier analyses (KMAs) compared survival outcomes. Results: A total of 877 patients were analyzed (LND performed in 358 [40.8%]/pN+ in 73 [8.3%]). Median nodes obtained were 10.2 for pN+ and 9.8 for pN0. Multivariable analyses noted increasing age (OR 1.1, p <0.001), pN+ (OR 3.1, p <0.001) and pathological stage pTis/3/4 (OR 3.4, p <0.001) as predictors for all-cause mortality. Clinical high-grade tumors (OR 11.74, p=0.015) and increasing tumor size (OR 1.14, p=0.001) were predictive for lymph node positivity. KMAs for pNx, pN0 and pN+ demonstrated 2-year OS of 80%, 86% and 42% (p <0.001) and 2-year RFS of 53%, 61% and 35% (p <0.001), respectively. KMAs comparing pNx, pN0 ≥10 nodes and pN0 <10 nodes showed no significant difference in 2-year OS (82% vs 85% vs 84%, p=0.6) but elicited significantly higher 2-year RFS in the pN0 ≥10 group (60% vs 74% vs 54%, p=0.043). Conclusions: LND during nephroureterectomy in patients with positive lymph nodes provides prognostic data, but is not associated with improved OS. LND yields ≥10 in patients with clinical node negative disease were associated with improved RFS. In high-grade and large tumors, lymphadenectomy should be considered.