Miracle-dz/UniFAR-FTUs huggingface dataset:
Identifikasi Source Image Menggunakan Pendekatan Forensic Similarity pada Image Forensik

Dengan perkembangan teknologi digital, gambar digital bisa didapat kapan dan dimana saja melalui kamera dan telepon genggam. Orang dapat memperoleh gambar dengan mudah dan dapat juga memanipulasi sumber informasi pada konten dan bahkan dapat melakukan manipulasi gambar. Sehingga perlu melakukan verifikasi sumber gambar yang merupakan pekerjaan utama di bidang image forensik. Identifikasi sumber kamera adalah proses menentukan perangkat kamera mana yang telah digunakan untuk mengambil gambar. Pendekatan Forensic Similarity yang berbasis Convolutional Neural Network menentukan jika dua patch gambar diambil oleh kamera yang berbeda atau dari kamera yang sama. Pendekatan ini berbeda dari identifikasi kamera pada umumnya karena tidak menentukan kamera yang tepat yang digunakan untuk menangkap salah satu patch. Kekuatan pendekatan ini adalah kemampuan untuk membandingkan kamera yang tidak digunakan untuk melatih sistem. Ini memungkinkan penyidik mempelajari informasi penting tentang gambar yang diambil dengan kamera apa pun, dan tidak dibatasi oleh kumpulan model kamera di database penyidik. Meskipun informasi model kamera, tanggal dan waktu, dan informasi lainnya dapat ditemukan di EXIF atau di header JPEG, secara umum tidak mungkin untuk menganggap informasi tersebut benar karena metadata gambar dapat dengan mudah dimodifikasi. Proses identifikasi kamera sumber menggunakan identifikasi pada gambar untuk mengetahui sumber kamera yang diperoleh dari gambar tersebut. Dengan menggunakan pendekatan forensic similarity dapat mendukung informasi pada metadata sehingga dapat menjamin keaslian dari informasi yang diperoleh.
Measuring the self-interaction cross-section of dark matter with astronomical particle colliders

The dark matter paradigm has been a great source of speculation in both the 20th and 21st Centuries. Since its proposed existence in 1933, the mounting evidence has led to this theoretical particle becoming one of the greatest mysteries of modern physics. However, despite its dominant presence in the Universe, little is known about its nature and how it behaves. In this thesis I critically analyse one particular property of dark matter: the self-coupling. The self-interacting dark matter paradigm hypothesises that dark matter is not collisionless as assumed in most cosmological simulations, and in-fact has some probability that it will scatter off itself. Such a self-coupling will resolve many discrepancies that exist between observations and theory, particularly on small, non-linear scales. Moreover, any detection of a self-interaction cross-section will place considerable limitations on the acceptable particle physics models of dark matter and hence has grown to become an important question. In this thesis I develop and implement a method to constrain the selfinteraction cross-section of dark matter that exploits continually accreting and merging groups of galaxies as they fall into galaxy clusters. Utilising the ubiquitous nature of accreting substructure, I measure the offsets between dark matter and baryonic gas as they become separated due to their differing interaction properties. Studying this effect over a sample of events, I will be able to make the first ever statistical estimate of the cross-section of dark matter, while averaging over many different unknown merging scenarios. I begin my thesis by deriving an analytical description of sub-halo infall, allowing me to constrain dark matter self-interaction models directly from observations. In this study, I find that current archival data should be able to detect a difference in the dynamical behaviour of dark matter and standard model particles at 6σ, and measure the total interaction cross-section σDM/m with 68%
Use of Nods Less Synchronized with Turn-Taking and Prosody During Conversations in Adults with Autism

Autism spectral disorder (ASD) is a highly prevalent neurodevelopmental disorder characterized by deficits in communication and social interaction. Head-nodding, a kind of visual backchannels, is used to co-construct the conversation and is crucial to smooth social interaction. In the present study, we quantitively analyze how head-nodding relates to speech turn-taking and prosodic change in Japanese conversation. The results showed that nodding was less frequently observed in ASD participants, especially around speakers’ turn transitions, whereas it was notable just before and after turn-taking in individuals with typical development (TD). Analysis using 16 sec of long-time sliding segments revealed that synchronization between nod frequency and mean vocal intensity was higher in the TD group than in the ASD group. Classification by a support vector machine (SVM) using these proposed features achieved high performance with an accuracy of 91.1% and an F-measure of 0.942. In addition, the results indicated an optimal way of nodding according to turn-ending and emphasis, which could provide standard responses for reference or feedback in social skill training for people with ASD. Furthermore, the natural timing of nodding implied by the results can also be applied to developing interactive responses in humanoid robots or computer graphic (CG) agents.
Applying the Transtheoretical Model of Behavioral Change to Establish Physical Activity Habits

The Transtheoretical Model is an integrative model of behavior change developed in response to increasing theoretical diversity within psychotherapy. Since its conception, the model has been applied to a variety of behavior change contexts such as substance abuse, diet, and exercise. PURPOSE: to review and summarize the literature relative to applications of the Transtheoretical Model in exercise interventions, and to provide considerations for health professionals while using the Transtheoretical Model in their practice. METHODS: The components of the Transtheoretical Model of behavior change are parsed and analyzed to review their function and role in the model. In addition, the model is reviewed to determine the effectiveness of applying the Transtheoretical Model in conjunction to interventions aimed at increasing physical activity behavior. RESULTS: In general, results support the application of Transtheoretical Model for physical activity behavioral change, but not unconditionally. Beyond highlighting results of studies applying the Transtheoretical Model, implications and considerations for interventions using the models are also detailed. CONCLUSION: When acknowledging the multidimensional nature of the model, it is important to demonstrate a good understanding of how the various dimensions relate to one another and recognize how these relationships will influence intervention development.
The Effects of Navigation Cues and Involvement of Highly Innovative Consumers on Attitudes Toward Mobile Application Stores

In the e-commerce area, navigation cues play an important role that guides consumers while they are browsing products in online stores. Best-seller lists and product categories are typically used as navigation cues. With the rapid growth of smartphone penetration around the world, the role of navigation cues has become more critical to consumers who enjoy buying products and applications via mobile application stores. The purpose of this study is to investigate the relationships among navigation cues, attitudes, and involvement of users in mobile stores based on the elaboration likelihood model. A laboratory experiment was conducted, and the experiment results indicate that consumers with high involvement have better attitudes toward the product categories approach compared to the best-seller list approach. The fits of navigation cues and mobile consumer characteristics may contribute to the mobile application store design strategy.
YAP/Smad3 promotes pathological extracellular matrix microenviroment‐induced bladder smooth muscle proliferation in bladder fibrosis progression

Abstract Fibrosis is a chronic inflammation process with excess extracellular matrix (ECM) deposition that cannot be reversed. Patients suffer from bladder dysfunction caused by bladder fibrosis. Moreover, the interactive mechanisms between ECM and bladder fibrosis are still obscure. Hence, we assessed the pivotal effect of Yes‐associated protein (YAP) on the proliferation of bladder smooth muscle in fibrosis process. We identified that stiff ECM increased the expression and translocation of YAP in the nucleus of human bladder smooth muscle cell (hBdSMC). Sequencings and proteomics revealed that YAP bound to Smad3 and promoted the proliferation of hBdSMC via MAPK/ERK signaling pathway in stiff ECM. Moreover, CUT and TAG sequencing and dual‐luciferase assays demonstrated that Smad3 inhibited the transcription of JUN. The YAP inhibitor CA3 was used in a partial bladder outlet obstruction (pBOO) rat model. The results showed that CA3 attenuated bladder smooth muscle proliferation. Collectively, YAP binding with Smad3 in the nucleus inhibited the transcription of JUN, and promoted the proliferation of bladder smooth muscle through the MAPK/ERK signaling pathway. The current study identified a novel mechanism of mechanical force induced bladder fibrosis that provided insights in YAP‐associated organ fibrosis.
Artemisinin-based combination therapy amongst medical students in the University of Benin, South-South Nigeria: A cross-sectional study

Since 2005, the recommended first-line therapy for uncomplicated malaria in Nigeria has been Artemisinin-based Combination Therapy (ACT). Previous research indicates that these therapies are widely accepted by health care providers and other end users. Nonetheless, few studies have examined the preferences of clinical students who will be future prescribers of these medications. This was a descriptive cross-sectional survey of medical students undergoing clinical placements at the University of Benin Teaching Hospital in Benin City, Edo State, South-South Nigeria, to assess ACT preferences, tolerability, and cost considerations. Consenting clinical medical students who were recruited sequentially were given a semi-structured questionnaire. The questionnaire collected information about the students’ demographics, previous episodes of malaria symptoms, diagnosis, and treatment. Their preferred antimalarial, tolerability to ACTs, and ACT cost. The information was presented descriptively. There were 475 registered clinical students, but only 416 agreed to participate in the survey, yielding an 87.6% response rate. The students’ mean (standard deviation) age was 24.3 (3.8) years, with a male preponderance of 250 (60.1%). The majority, 154 (37.0%), were in the 600 level, while the 500 and 400 levels were 130 (31.3%) and 132 (31.7%), respectively. The majority of students, 272 (65.5%), treated malaria presumptively, and the majority of students, 344 (82.7%), had treated one to five episodes of malaria in the previous 12 months. The ACTs were known to nearly all of the final year clinical students (97.4%). The majority, 289 (69.5%), had no adverse drug reactions with the ACTs. Among those who experienced adverse drug reactions, 23 (39.7%) discontinued their medication, while 2 (3.4%) required hospitalization. The mean cost of the ACT was ₦1263.4 (SD ± 529.6) (₦=Naira) (3.0 USD), with a range of ₦ 300- ₦3000 (0.72- 7.2 USD). This study demonstrates a high level of acceptance for ACTs, particularly artemether-lumefantrine. However, the adverse effects of ACTs, particularly other recommended ACTs, must be evaluated on a regular basis because they may have an impact on their continued use.
Optimal Robust Control for Rigid Serial Manipulators: A Fuzzy Approach

We first investigate the fundamental properties of rigid serial manipulators as related to the control design. Then, a new optimal robust control is proposed for serial‐link mechanical manipulators with fuzzy uncertainty. Fuzzy set theory is used to describe the uncertainty. The desirable system performance is deterministic (assuring the bottom line) and also fuzzy (enhancing the cost consideration). The proposed control is deterministic and is not the usual if‐then rules‐based control. The resulting controlled system is uniformly bounded and uniformly ultimately bounded proved via the Lyapunov minimax approach. A performance index (the combined cost, which includes average fuzzy system performance and control effort) is proposed based on the fuzzy information. The optimal design problem associated with the control can then be solved by minimizing the performance index. The resulting control design is systematic and is able to guarantee the deterministic performance as well as minimizing the cost. In the end, a cylindrical robot manipulator is chosen for demonstration.
Global RNN Transducer Models For Multi-dialect Speech Recognition

Constructing single, uniﬁed automatic speech recognition (ASR) models that work effectively across various dialects of a language is a challenging problem. Although many recently proposed approaches are effective, they are computationally more expensive compared to the conventional approach of us-ing ASR models designed separately for each dialect. In this paper, we propose a novel modeling technique for constructing accurate, multi-dialect, speech recognition systems with a single uniﬁed model, based on recurrent neural network transducers (RNN-T), which does not incur any extra computational costs at decoding time. Once a model has been created, the same decoding settings can also be used across all dialects. In our proposed approach, an RNN-T model with a shared encoder, common joint network and multi-branch prediction networks is ﬁrst constructed. After training each prediction network on an ASR task corresponding to various dialects, an effective interpolation step combines the multi-branch prediction networks back into a computationally-efﬁcient single branch. The effectiveness of the proposed technique is shown on ASR tasks on major English dialects. The proposed method approaches oracle performance and improves by 15-30% relative over dialect-speciﬁc models in dialect agnostic conditions.
Aerodynamics of the curve-ball : an investigation of the effects of angular velocity on baseball trajectories

In this dissertation the aerodynamic force and initial conditions of pitched baseballs are estimated from high-speed video data. Fifteen parameters are estimated including the lift coefficient, drag coefficient and the angular velocity vector using a parameter estimation technique that minimizes the residual error between measured and estimated trajectories of markers on the ball’s surface and the center of mass of pitched baseballs. Studies are carried out using trajectory data acquired from human pitchers and, in a more controlled environment, with a pitching machine. In all 58 pitch trajectories from human pitchers and 20 pitching machine pitches with spin information are analyzed. In the pitching machine trials four markers on the ball are tracked over the first 4 ft (1.22 m) and the center of mass of the ball is tracked over the last 13 ft (3.96 m) of flight. The estimated lift coefficients are compared to previous measured lift coefficients of Sikorsky (Alaways & Lightfoot, 1998) and Watts & Ferrer (1987) and show that significant differences exists in the lift coefficients of twoand four-seam curve balls at lower values of spin parameter, S . As S increased the twoand four-seam lift coefficients merge becoming statistically insignificant. The estimated drag coefficients are compared to drag coefficients of smooth spheres and golf-balls and show that these data sets bound the drag-coefficient of the baseball. Finally, it is shown that asymmetries of the ball associated with the knuckleball can influence the trajectory of the more common curve and fastball.
An Immersive Human-Robot Interactive Game Framework Based on Deep Learning for Children’s Concentration Training

In order to alleviate bottlenecks such as the lack of professional teachers, inattention during training processes, and low effectiveness in concentration training, we have proposed an immersive human–robot interactive (HRI) game framework based on deep learning for children’s concentration training and demonstrated its use through human–robot interactive games based on gesture recognition. The HRI game framework includes four functional modules: video data acquisition, image recognition modeling, a deep learning algorithm (YOLOv5), and information feedback. First, we built a gesture recognition model containing 10,000 pictures of children’s gestures, using the YOLOv5 algorithm. The average accuracy in recognition trainingwas 98.7%. Second, we recruited 120 children with attention deficits (aged from 9 to 12 years) to play the HRI games, including 60 girls and 60 boys. In the HRI game experiment, we obtained 8640 sample data, which were normalized and processed.According to the results, we found that the girls had better visual short-term memory and a shorter response time than boys. The research results showed that HRI games had a high efficacy, convenience, and full freedom, making them appropriate for children’s concentration training.
Pseudophilothrips perseae Damaging Hass Avocado Fruits in México

Abstract. During 2020, producers of Hass avocado (Persea americana Mill.) in the central region of Veracruz State detected atypical damage associated with infestation by thrips. Larvae and adults were feeding on developing fruits, causing wounds in the epidermis, producing necrotic spots, and reducing commercial value. Insects were collected from affected fruits, mounted, and identified using specialized keys. Images of damage were obtained, and numbers of affected trees and fruits were quantified. Thrips specimens were identified as Pseudophilothrips perseae (Thysanoptera: Phlaeothripidae) with an incidence of 1.6% in the orchard examined. Damage by P. perseae in this work differed from that usually caused by other thrips species that feed and oviposit on tender tissues of avocado trees. We reported for the first time, damage caused by P. perseae in developing avocado fruits. More study is necessary to determine distribution and potential to increase in abundance and affect crop production.
Masculinities under construction, bodies under (re)construction: trans men’s desires, contradictions, and ambiguities in the transexualizing process

Abstract This paper presents the research results on the strategies, expectations, and desires of 28 transsexual men in building their masculinities and reconstructing their bodies through cross-hormonization. The qualitative research was carried out in an outpatient clinic of the transsexualization process in a city in the metropolitan region of Rio de Janeiro. We employed semi-structured interviews and participant observation from November 2019 to January 2020 to collect data. Content analysis guided the analysis of the statements from which the discussed categories emerged. The categories were discussed in the light of the concepts of gender, transsexuality, and masculinity, besides references from studies on ethnicity/skin color in their articulations with health. The data revealed desires, contradictions, and ambiguities regarding the construction of masculinity and the (re)construction of bodies more suited to it. They also evidenced the desire for the male bodily standard achieved through hormonization and surgeries, and black skin color emerged as a critical inequality mark. We concluded that, while refuting many male model features, these men want to enter this world and blend in with the crowd as men, thus experiencing fuller masculinity.
Automatic Mean Opinion Score Estimation with Temporal Modulation Features on Gammatone Filterbank for Speech Assessment

The mean opinion score (MOS) obtained by listening tests is a key component of speech quality evaluation. However, as subjective tests are too costly to conduct on a large scale, it is necessary to estimate the MOS objectively. Thus far, the features used in existing methods for automatic MOS prediction are not based on human perception of speech. In this paper, we propose an automatic MOS estimation method using temporal modulation features on the gammatone filterbank to improve the correlation of the predicted MOS with human perception. We evaluated our method using utterance-level and system-level mean squared errors (MSEs) and Spearman rank correlation co-efficients (SRCCs). Compared with the baseline method of the VoiceMOS challenge, the proposed method had a better performance in both utterance-level metrics and system-level SRCC. It also exhibited a significant improvement for utterances with low MOS values.
A post-exercise infrared sauna session improves recovery of neuromuscular performance and muscle soreness after resistance exercise training

The aim of this study was to investigate effects of a single infrared sauna (IRS) session on post-exercise recovery of neuromuscular performance, autonomic nervous system function, subjective sleep quality, and muscle soreness. Male basketball players (n = 16) performed two trials consisting of a complex resistance exercise protocol (maximal strength with plyometrics), followed by either 20 min passive recovery (PAS) or IRS (temperature 43 ± 5°C), in a randomized crossover design, with trials separated by one week. Recovery of neuromuscular performance was assessed using 20 m maximal sprint, maximal countermovement-jump (CMJ), and isometric leg press tests, performed 14 hours after exercise. Heart rate (HR), heart rate variability (HRV), sleep diary, muscle soreness, and indirect muscle damage markers were measured pre and post exercise. The decrease in CMJ performance from pre- to post-exercise was attenuated after IRS compared to PAS (p < 0.01). The IRS session resulted in higher HR and lower root mean square of successive differences between normal heartbeats (RMSSD), and high and low frequency power, compared to PAS (p < 0.002). Post-exercise night-time HR and HRV did not differ following IRS vs. PAS. Muscle soreness was less severe, and perceived recovery was higher after IRS compared to PAS (p < 0.01). Post-exercise IRS attenuated the drop in explosive performance and decreased subjective muscle soreness after resistance training, which may enhance mood, readiness, and physical performance of an athlete. A single IRS session had no detrimental effects on recovery of the autonomic nervous system.
A hierarchical visuo-motor organization for computational models of the mirror system

Typical patterns in the space of motor configurations, frequently referred as motor synergies, enable one to provide a simplified action representation. The computational model of the mirror system introduced in this thesis hypothesizes that a synergy representation of actions could be actually developed in motor cortex and strongly involved in the process of elaboration of observed actions. In particular the action representation and the mirror system model were developed in order to reproduce two important biological findings about motor cortex, namely: 1) the action is represented according to different levels of detail; 2) the visual representation of an observed action is represented according to different levels of detail. In particular in this thesis, focusing on hand grasping actions, we investigate a synergy repersentation of actions where the synergies would be forced to be hierarchically organized. We show that this representation results to be accurate and, biologically plausible, being able to describe action at multiple level of detail. Successively we present an architecture where the previous hierarchical synergy representation is used in the process of elaboration of an observed action. We show how using this motor information can actually improve the process of action recognition and repreoduce one of the principal characteriscms of the mirror neurons, namely thier distinction in stricktly and broadly neurons.