Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimizing the Finite Length Performance of Sparse Superposition Codes

Sparse superposition codes are a recent class of codes introduced by Barron and Joseph for efficient communication over the AWGN channel. With an appropriate power allocation, these codes have been shown to be asymptotically capacity-achieving with computationally feasible decoding. However, a direct implementation of the capacity-achieving construction does not give good finite length error performance, and has unnecessarily high computational complexity. In this paper, we consider sparse superposition codes with approximate message passing (AMP) decoding, and describe a variety of techniques to improve their finite length performance and decrease computational complexity. These include using implicit Walsh-Hadamard design matrices, optimizing SPARC power allocations and codebook parameters, and estimating a critical decoding parameter online instead of pre-computation. Finally we compare the error performance of AMP-decoded sparse superposition codes with coded modulation using LDPC codes from the WiMAX standard.
Optimal Nonergodic $O(1/K)$ Convergence Rate: When Linearized ADM Meets Nesterov's Extrapolation

The Alternating Direction Method (ADM) is widely used for linearly constrained convex problems. Recently, ADM is proven to have an $o(1/\sqrt{K})$ convergence rate in a nonergodic sense, where $K$ is the number of iterations. Moreover, this rate is tight. In this paper, we accelerate ADM with Nesterov's first acceleration scheme to improve the nonergodic convergence rate of ADM from $o(1/\sqrt{K})$ to $O(1/K)$. A Linearized ADM with Nesterov's Extrapolation (LADM-NE) is proposed and satisfies $|F(x^K)-F(x^*)|\leq O(1/K)$ and $\| Ax^K-b\|\leq O(1/K)$. As far as we know, this is the first nonergodic $O(1/K)$ convergent ADM type method for general linearly constrained convex problems. We then propose an LADM-NE with restart (LADM-NER) to further speed up the convergence in practice, which can also achieve the improved $O(1/K)$ nonergodic convergence rate. We also show that the lower complexity bound of ADM type methods for the separable linearly constrained nonsmooth convex problems is $O(1/K)$, which means that LADM-NE and LADM-NER are optimal. Numerical results testify to the advantage of our methods in speed and accuracy.
Development and In Vitro–In Vivo Correlation Evaluation of IMM-H014 Extended-Release Tablets for the Treatment of Fatty Liver Disease

This study aimed to develop extended-release tablets containing 25 mg IMM-H014, an original drug formulated by a direct powder pressing method based on pharmaceutical-grade hydrophilic matrix polymers such as hydroxypropyl methylcellulose, to establish an in vitro–in vivo correlation (IVIVC) to predict bioavailability. The tablets’ mechanical properties and in vitro and in vivo performance were studied. The formulation was optimized using a single-factor experiment and the reproducibility was confirmed. The in vitro dissolution profiles of the tablet were determined in five dissolution media, in which the drug released from the hydrophilic tablets followed the Ritger–Peppas model kinetics in 0.01 N HCl medium for the first 2 h, and in phosphate-buffered saline medium (pH 7.5) for a further 24 h. Accelerated stability studies (40 °C, 75% relative humidity) proved that the optimal formulation was stable for 6 months. The in vivo pharmacokinetics study in beagle dogs showed that compared to the IMM-H014 immediate release preparation, the maximum plasma concentration of the extended-release (ER) preparation was significantly decreased, while the maximum time to peak and mean residence time were significantly prolonged. The relative bioavailability was 97.9% based on the area under curve, indicating that the optimal formulation has an obvious ER profile, and a good IVIVC was established, which could be used to predict in vivo pharmacokinetics based on the formulation composition.
Reliability and Validity of the Geriatric Depression Scale in a Sample of Portuguese Older Adults with Mild-to-Moderate Cognitive Impairment

Although the Geriatric Depression Scale (GDS) is a well-established instrument for the assessment of depressive symptoms in older adults, this has not been validated specifically for Portuguese older adults with cognitive impairment. The objective of this study was to analyze the psychometric properties of two Portuguese versions of the GDS (GDS-27 and GDS-15) in a sample of Portuguese older adults with mild-to-moderate cognitive impairment. Clinicians assessed for major depressive disorder and cognitive functioning in 117 participants with mild-to-moderate cognitive decline (76.9% female, Mage = 83.66 years). The internal consistency of GDS-27 and GDS-15 were 0.874 and 0.812, respectively. There was a significant correlation between GDS-27 and GDS-15 with the Beck Depression Inventory-II (GDS-27: rho = 0.738, p < 0.001; GDS-15: rho = 0.760, p < 0.001), suggesting good validity. A cutoff point of 15/16 in GDS-27 and 8/9 in GDS-15 resulted in the identification of persons with depression (GDS-27: sensitivity 100%, specificity 63%; GDS-15: sensitivity 90%, specificity 62%). Overall, the GDS-27 and GDS-15 are reliable and valid instruments for the assessment of depression in Portuguese-speaking older adults with cognitive impairment.
On the asymptotic equidistribution of sums of independent identically distributed random variables

For a sum Sn of n I. I. D. random variables the idea of approximate equidistribution is made precise by introducing a notion of asymptotic translation invariance. The distribution of Sn is shown to be asymptotically translation invariant in this sense iff Si is nonlattice. Some ramifications of this result are given.
Mantle Wavespeed and Discontinuity Structure Below East Africa: Implications for Cenozoic Hotspot Tectonism and the Development of the Turkana Depression

Ethiopia's Cenozoic flood basalt magmatism, uplift, and rifting have been attributed to one or more mantle plumes. The Nubian plate, however, has drifted 500–1,000 km north since initial magmatism at ∼45 Ma, having developed above mantle that now underlies the northern Tanzania craton and the low‐lying Turkana Depression. Unfortunately, our knowledge of mantle wavespeed structure and mantle transition zone (MTZ) topography below these regions is poorest, due to a historical lack of seismograph stations. The same data gap means we lack constraints on lithospheric structure in and around the NW–SE trending Mesozoic Anza rift. We exploit data from new seismograph networks in the Turkana Depression and neighboring northern Uganda to develop AFRP22, a new African absolute P‐wavespeed tomographic model that resolves whole mantle structure along the entire East African rift system. We also map MTZ thickness using Ps receiver functions. East Africa's thinnest MTZ (∼25 km thinning) underlies the northwest Turkana Depression. AFRP22 reveals a co‐located, previously unrecognized, slow wavespeed plume tail, extending from the MTZ, deep into the lower mantle. This plume may thus have contributed, along with the African Superplume, to the development of the 45–30 Ma flood basalt province that preceded extension. Pervasive sub‐lithospheric slow wavespeeds imply that Turkana's present‐day low elevation is explained best by Mesozoic and Cenozoic‐age crustal thinning. At ∼100 km depth, AFRP22 illuminates a fast wavespeed SE Ethiopian plateau. In addition to governing the northernmost limit of Mesozoic Anza rifting, the refractory nature of this lithospheric block likely minimized Cenozoic flood basalt magmatism there.
SKRINING DAN EDUKASI PENCEGAHAN HIPERTENSI PADA MASYARAKAT PESISIR KAMPUNG SALO, KOTA KENDARI

Hypertension is a condition characterized by elevated systolic blood pressure above 140 mmHg and diastolic blood pressure above 90 mmHg. Persistent high blood pressure can lead to symptoms such as nausea, vomiting, headaches, nosebleeds, shortness of breath, and others. It can also increase the risk of stroke, heart failure, and kidney failure. Nearly 95% of hypertension cases are influenced by environmental risk factors and genetic predisposition. The prevalence of hypertension in Indonesia is quite high, warranting special attention and management. The Asian Medical Student's Association (AMSA) Unit of Halu Oleo University conducted the "Berjuang untuk Solidaritas, Peduli Hipertensi" event as part of the AMSA-UHO 2023 program. The objective was to raise awareness about nutrition management and dietary therapy for hypertension patients through lectures, discussions, demonstrations, and health screenings. The event showed an improvement in knowledge among the participants. A pre-test was conducted with a questionnaire consisting of 10 questions, involving 35 individuals. The results indicated that prior to the event, 17% had good knowledge, 25% had moderate knowledge, and 58% had poor knowledge about hypertension. After the educational activities and knowledge demonstrations, 83% had good knowledge and 16% had moderate knowledge. Furthermore, out of the 35 participants, 20 were found to have hypertension, 5 had prediabetes, and 7 had hyperuricemia. The coastal community of Kampung Salo in Kendari City demonstrated a relatively good level of knowledge regarding nutrition management to prevent the occurrence of non-communicable diseases, particularly hypertension. Additionally, they actively participated in health screenings for early detection of hypertension and other related conditions. It is hoped that the community of Kampung Salo will continue to actively engage in early prevention efforts, both at an individual and community level.
Pixelated GaSb solar cells on silicon by membrane bonding

We demonstrate thin-film GaSb solar cells which are isolated from a GaSb substrate and transferred to a Si substrate. We epitaxially grow ∼3.3 μm thick GaSb P on N diode structures on a GaSb substrate. Upon patterning in 2D arrays of pixels, the GaSb films are released via epitaxial lift-off and they are transferred to Si substrates. Encapsulation of each pixel preserves the structural integrity of the GaSb film during lift-off. Using this technique, we consistently transfer ∼4 × 4 mm2 array of pixelated GaSb membranes to a Si substrate with a ∼ 80%–100% yield. The area of individual pixels ranges from ∼90 × 90 μm2 to ∼340 × 340 μm2. Further processing to fabricate photovoltaic devices is performed after the transfer. GaSb solar cells with lateral sizes of ∼340 × 340 μm2 under illumination exhibit efficiencies of ∼3%, which compares favorably with extracted values for large-area (i.e., 5 × 5 mm2) homoepitaxial GaSb solar cells on GaSb substrates.We demonstrate thin-film GaSb solar cells which are isolated from a GaSb substrate and transferred to a Si substrate. We epitaxially grow ∼3.3 μm thick GaSb P on N diode structures on a GaSb substrate. Upon patterning in 2D arrays of pixels, the GaSb films are released via epitaxial lift-off and they are transferred to Si substrates. Encapsulation of each pixel preserves the structural integrity of the GaSb film during lift-off. Using this technique, we consistently transfer ∼4 × 4 mm2 array of pixelated GaSb membranes to a Si substrate with a ∼ 80%–100% yield. The area of individual pixels ranges from ∼90 × 90 μm2 to ∼340 × 340 μm2. Further processing to fabricate photovoltaic devices is performed after the transfer. GaSb solar cells with lateral sizes of ∼340 × 340 μm2 under illumination exhibit efficiencies of ∼3%, which compares favorably with extracted values for large-area (i.e., 5 × 5 mm2) homoepitaxial GaSb solar cells on GaSb substrates.
An Interval Prediction Method for Day-Ahead Electricity Price in Wholesale Market Considering Weather Factors

Accurate prediction of electricity prices under uncertainties is an important and challenging problem for all electricity market participants. This article proposes a novel generative model-based prediction interval construction method for day-ahead electricity prices. A conditional time series generative adversarial network is proposed to generate realistic and diverse electricity price scenarios. With these generated price scenarios, prediction intervals can be combined. After that, a threshold select machine is proposed to truncate the threshold of random noise input to adjust the quality of prediction intervals, balancing the reliability and sharpness. Finally, shortwave irradiance, wind speed, and temperature are taken into account in the threshold select machine, further improving the reliability and the sharpness of the prediction intervals. Case studies verify the effectiveness and superiority of the proposed method.
Accuracy Comparison of Data Mining Methods for Internet Gaming Disorder Classification

Excessive access to online games by players can lead to addiction. Online game addiction can be detected through various ways including self-report questionnaires. Based on the value of the answers in the questionnaire a person can be categorized into groups, mild addiction, moderate addiction and severe addiction. Generally, this assessment calculation is done manually or through procedural programming languages. This is not efficient for processing more and more data, for that the mechine learning classification model is applied to solve the problem of program code repetition. This study compared the performance of three mechine learning methods against two different types of questionnaires, namely questionnaires with Likert scale and questionnaires with yes no type. The case study used in this study is online game addiction among high school students in Banda Aceh City, Indonesia. This research successfully proved that the algorithm . It is better to use questionnaires with data types. , while algorithms.are better to use for questionnaires with types.with the accuracy of the three algorithms are as follows. This study reveals the emergence of online game addiction, especially among high school students within Banda Aceh city. The results depicted that as many as 6% of high school students in the city of Banda Aceh indicated experiencing online game addiction based on their reports. Another objective of this research is to find the best accuracy between Naive Bayes and Support vector machine (SVM) in classifying the severity of the online game. It found that SVM accuracy was higher than Naive Bayes for the case of online game addiction level classification in high school students in Banda Aceh. This study provided baseline data for further research.
Graphene field effect transistor for generating on-chip thermoelectric power

Graphene is a promising material for thermoelectric application due to its large surface-to-volume ratio, high electrical conductivity, and high mechanical strength. In this paper, the thermoelectric properties of a series of narrow armchair graphene nanoribbons (GNR) in semiconducting family GNR(3p+1,0) are evaluated by using the semi-classical Boltzmann theory. It is found that the narrow GNR(7,0) exhibits small thermal conductivity and large TEP of 1170μV / K at small chemical potential μ = 0.1 eV . However, the small electrical conductivity of narrow GNR(7,0) suppresses the thermoelectric figure-of-merit ZT, such that better thermoelectric performance of ZT > 0.01 is achieved only for large chemical potentials, μ > 0.5eV . Our result shows that tuning the chemical potential with respect to ribbon chirality and orientation can enhance the thermoelectric performance of GNRs, however, further increase in thermoelectric power requires phonon engineering to reduce the thermal conductivity of graphene without significant reduction in its thermoelectric power and electrical conductivity.
Two consistent estimators for the skew Brownian motion

The skew Brownian motion (SBm) is of primary importance in modeling diffusion in media with interfaces which arise in many domains ranging from population ecology to geophysics and finance. We show that the maximum likelihood procedure estimates consistently the parameter of an SBm observed at discrete times. The difficulties arise because the observed process is only null recurrent and has a singular distribution with respect to the one of the Brownian motion. Finally, using the idea of the expectation–maximization algorithm, we show that the maximum likelihood estimator can be naturally interpreted as the expected total number of positive excursions divided by the expected number of excursions given the observations. The theoretical results are illustrated by numerical simulations.
Incremental Learning for End-to-End Automatic Speech Recognition

We propose an incremental learning for end-to-end Automatic Speech Recognition (ASR) to extend the model's capacity on a new task while retaining the performance on existing ones. The proposed method is effective without accessing to the old dataset to address the issues of high training cost and old dataset unavailability. To achieve this, knowledge distillation is applied as a guidance to retain the recognition ability from the previous model, which is then combined with the new ASR task for model optimization. With an ASR model pre-trained on 12,000h Mandarin speech, we test our proposed method on 300h new scenario task and 1h new named entities task. Experiments show that our method yields 3.25% and 0.88% absolute Character Error Rate (CER) reduction on the new scenario, when compared with the pre-trained model and the full-data retraining baseline, respectively. It even yields a surprising 0.37% absolute CER reduction on the new scenario than the fine-tuning. For the new named entities task, our method significantly improves the accuracy compared with the pre-trained model, i.e. 16.95% absolute CER reduction. For both of the new task adaptions, the new models still maintain a same accuracy with the baseline on the old tasks.
CUSUM tests for change points in AR(P) models

This paper analyzes the problem of testing for change points in processes by CUSUM test using asymptotic theory. The limiting distribution of test statistic is derived and Monte Carlo simulation is provided. It shown that the empirical power not only depends on the sample size, but is sensitive to the magnitude of location of structural breaks.
Facility location under matroid constraints: fixed-parameter algorithms and applications

We study an NP-hard uncapacitated discrete facility location problem: The task is to decide which facilities to open and which clients to serve for maximum profit so that the facilities form an independent set in given facility-side matroids and the clients form an independent set in given client-side matroids. Combining the color coding technique with representative sets of matroid intersections, we show that the problem is fixed-parameter tractable parameterized by the number of matroids and the minimum rank among the client-side matroids. We apply this algorithm to obtain fixed-parameter algorithms for social network analysis, line planning in public transport, and team management. We complement our tractability results by lower bounds.
Dynamic optimization of two methods of the long jump

In this thesis, I analyzed, modelled, and optimized two different techniques of the long jump: the hitchkick and hang. Using video data, I made a dynamic model of both techniques, then created a cost function that took torques and angles into consideration to simulate physical limitations. Using a function minimizing optimizer, trajectories were simulated over a range of torque limits and angle penalties. Over the course of 292 simulations, we found that the hitchkick technique improved jump distances more than the hang technique, improving by up to 34.65% with an average of 7.7% while the hang technique increased jump distance by a maximum of 30.21%, with an average of -15.89%. Thesis Supervisor: Sangbae Kim Title: Associate Professor
Human Fatigue Estimate: Usage of Systems from Traffic in Buildings

Sledovani unavy clověka je dnes hlavně domenou dopravy (systemy pro sledovani řidice v modernich automobilech, systemy pro strojvedouci, atd.). U lidi pracujicich v kancelařich se unava prakticky nesleduje, přestože jeji vliv může mit negativni dopad nejen na kvalitu a produktivitu prace, ale v připadě osob na velinech v průmyslu take možna bezpecnosti rizika. Tato resersni prace se zabýva možnostmi aplikace systemů pro monitoring unavy řidice automobilu (např. z pohybu oci, aktivit při řizeni) na osoby pracujici v kancelařských prostorach. To se vzhledem k možnostem pohybu po kancelaři jevi jako nedostatecne. Protože clověk travi v kancelaři typicky vice casu než v automobilu, ovlivňuje jej výrazněji vnitřni prostředi budov, ktere je vhodne do odhadu unavy take zahrnout. Výsledkem tak může být system kvantifikujici miru unavy zohledněnim jak vnitřniho prostředi, tak vybraných biologických signalů clověka snimaných na pracovnim mistě.
Blind identification using channel order estimation: subspace approach based on CGM

Subspace methods (SSM) are an effective approach for blind identification. However, these methods have two major disadvantages: i) they require a large amount of computation for the eigen-value decomposition (EVD) and the singular-value decomposition (SVD), what is more, ii) they require the prior knowledge of accurate channel order. In this paper, we discuss a new algorithm for blind identification using the property of conjugate gradient method (CGM) and using the conception of principal component analysis (PCA), which is based on the orthogonality between the subspaces spanned by the column vectors of the impulse response matrix (the impulse response subspace) and the noise subspace. The new algorithm does not need calculation of both EVD and SVD, and still more the prior knowledge of accurate channel order is unnecessary. Furthermore, the new algorithm has computations O(m/sup 2/) where m is the data vector length. We show the effectiveness of the proposed method by numerical example.
Insights into the genetic influences of the microbiota on the life span of a host

Escherichia coli (E. coli) mutant strains have been reported to extend the life span of Caenorhabditis elegans (C. elegans). However, the specific mechanisms through which the genes and pathways affect aging are not yet clear. In this study, we fed Drosophila melanogaster (fruit fly) various E. coli single-gene knockout strains to screen mutant strains with an extended lifespan. The results showed that D. melanogaster fed with E. coli purE had the longest mean lifespan, which was verified by C. elegans. We conducted RNA-sequencing and analysis of C. elegans fed with E. coli purE (a single-gene knockout mutant) to further explore the underlying molecular mechanism. We used differential gene expression (DGE) analysis, enrichment analysis, and gene set enrichment analysis (GSEA) to screen vital genes and modules with significant changes in overall expression. Our results suggest that E. coli mutant strains may affect the host lifespan by regulating the protein synthesis rate (cfz-2) and ATP level (catp-4). To conclude, our study could provide new insights into the genetic influences of the microbiota on the life span of a host and a basis for developing anti-aging probiotics and drugs.
A Metric Analogue of Stone Duality for Markov Processes

The Stone representation [Sto36] theorem is one of the recognized landmarks of mathematics. The Stone representatio theorem [Sto36] states that every (abstract) boolean algebra is isomorphic to a boolean algebra of sets; in modern terminology one has an equivalence of categories between the category of boolean algebras and the (opposite of) the category of compact Hausdor ff zero-dimensional spaces, or Stone spaces.