Miracle-dz/UniFAR-FTUs huggingface dataset:
The error-in-variables problem in the logistic regression model

RHONDA ROBINSON CLARK. The Error-in-Variables Problem in the Logistic Regression Model. (Under the direction of Clarence E. Davis.) It is well known that when the independent variable in simple linear regression is measured with error that least squaresestimates are not unbiased. This is also true for logistic regression and the magnitude of the bias is demonstrated through simulation studies. Estimators are presented as possible solutions to the 'errorin-variables' problem; that is, the problem of obtaining consistent estimators of model parameters when measurement error is present in the independent variable. Two solutions require an external estimate of the variance of the measurement error, two require multiple measures on the independent variable, while two others are extensions of the method of grouping, and the instrumental variable approach. Simulation studies show that the use of an external estimate of the error variance or multiple measures on the independent variable leads to estimators with substantially lower mean square error than the least squares estimate. For the grouping and instrumental variable approaches, the proposed estimators have lower mean square error under some but not all conditions. The methods discussed are applied to data from the Lipid Research Clinics Program Prevalence Study.
What Nutraceuticals Can Do for Duchenne Muscular Dystrophy: Lessons Learned from Amino Acid Supplementation in Mouse Models

Duchenne muscular dystrophy (DMD), the severest form of muscular dystrophy, is characterized by progressive muscle weakness with fatal outcomes most often before the fourth decade of life. Despite the recent addition of molecular treatments, DMD remains a disease without a cure, and the need persists for the development of supportive therapies aiming to help improve patients’ quality of life. This review focuses on the therapeutical potential of amino acid and derivative supplements, summarizing results obtained in preclinical studies in murine disease models. Several promising compounds have emerged, with L-arginine, N-acetylcysteine, and taurine featuring among the most intensively investigated. Their beneficial effects include reduced inflammatory, oxidative, fibrotic, and necrotic damage to skeletal muscle tissues. Improvement of muscle strength and endurance have been reported; however, mild side effects have also surfaced. More explorative, placebo-controlled and long-term clinical trials would need to be conducted in order to identify amino acid formulae that are safe and of true benefit to DMD patients.
On the sequential benchmarking of subannual series to annual totals

Temporal benchmarking according to the least squares methods of Denton is widely used for official statistics. The purpose of Denton methods is to achieve consistency between high‐ and low‐frequency data, for example, quarterly and annual data. The high‐frequency data are adjusted to align with low‐frequency data, while preserving as much as possible the short‐term movements of the preliminary high‐frequency data. Theoretically, it is best to benchmark all available data for all periods at once. Practically, such a simultaneous approach is often not feasible, due to the impossibility of changing results that have already been published. Therefore, benchmarking is often applied according to a sequential approach. This paper demonstrates that a popular Denton method is not always appropriate for sequential benchmarking. Undesirable abrupt changes of benchmarking corrections can occur. This paper proposes solutions that better preserve the short‐term movements between sequentially benchmarked series.
Measuring the electric charge of antihydrogen by stochastic acceleration

Assuming hydrogen is charge neutral, CPT invariance demands that antihydrogen also be charge neutral. Quantum anomaly cancellation also demands that antihydrogen be charge neutral. Standard techniques based on measurements of macroscopic quantities of atoms cannot be used to measure the charge of antihydrogen. In this paper, we describe how the application of randomly oscillating electric elds to a sample of trapped antihydrogen atoms, a form of stochastic acceleration, can be used to place experimental limits on this charge.
The Preferences of Shared Micro-Mobility Users in Urban Areas

This research focuses on the preferences of micro-mobility users in urban areas, specifically shared electric bikes (e-bikes), shared conventional bikes (bike), and shared electric scooters (e-scooters). It is found that previous scholars study traveler preferences of traditional transport modes while limited attention has been given to preferences of travelers toward micro-mobility considering electric scooters and bikes over conventional bikes. In order to address this gap, a discrete choice modeling approach is used to study the preferences of people through developing a transport choice model. A discrete choice experiment (DCE) is designed where choice sets that combine the shared micro transport modes where three associated attributes and four levels are included in the DCE for each alternative. A stated preference (SP) survey is designed and distributed in Budapest, Hungary. This research focuses on urban areas where travel time is relatively short. Multinomial Logit (MNL) model is applied where a transport choice model is developed. The effect of several factors on the preferences of people toward the three micro transport modes are evaluated. The developed transport choice model includes trip time, trip cost, walking distance, parking characteristics, and socio-demographic factors. The results indicate that travelers prefer using bikes more than e-bikes and e-scooters. Furthermore, it is found that e-scooter is the least favored by travelers. It is noteworthy that car drivers, individuals with access to or frequent usage of micro-mobility, graduate students, full-time workers, males, and young people are more willing to use shared electric micro-mobility services. The probability of choosing a transport mode based on the changes on parking type attribute is estimated in this research. The results show that travelers prefer free floating parking when they use shared electric micro-mobility services. This research underscores the significance of parking type (docks or dockless) and socio-demographic variables when it comes to micro-mobility modes in urban areas. It is evident that shared electric micro-mobility options require more effort and policy support to be effectively implemented, as shared conventional bikes appear more appealing to users. Overall, these findings contribute to the understanding of micro-mobility preferences and highlight areas for further exploration and potential policy interventions.
Electronic properties of and carrier dynamics in self-organized quantum dots for memories

This work investigates the electronic properties of and carrier dynamics in self-assembled semiconductor quantum dots (QDs) by means of static capacitance-voltage (C-V) spectroscopy, Deep-Level Transient Spectroscopy (DLTS), and time-resolved current measurements. The background and motivation is to further increase the storage time in a memory device based on self-assembled QDs, and to study the read-out process in such a memory. Hence, the work consists of two parts. In the first part, the electronic properties, such as the hole localization energy and the apparent capture cross section, are studied for various material systems. GaSb/GaAs QDs with and without AlxGa1−xAs barriers are studied by DLTS. The localization energies found for the GaSb/GaAs QDs are between 460(±20) meV and 760(±20) meV. The maximum localization energy of 800(±50) meV is reached with additional Al0.3Ga0. 7As barriers. The apparent capture cross sections are between 1 ·10−12 cm and 5 ·10−11 cm. Based on the theory of thermal emission, a storage time at room temperature between 100 ns and 80 ms is extrapolated for these values. Compared to previous work, the localization energy in QDs was increased, but due to a smaller apparent capture cross section, the storage time is still smaller than previously achieved values. For the first time, GaSb/GaAs quantum rings (QRs) are studied by DLTS. As a result of their smaller size compared to QDs, a localization energy of just 380(±10) meV is found, while the apparent capture cross section is comparable to the one of QDs. Also for the first time, a sample based on QDs in a GaP matrix is investigated. A mean activation energy of 450(±20) meV with an apparent capture cross section of 2 · 10−13 cm is found for In0.25Ga0. 75As/GaAs/GaP QDs, resulting in a room temperature storage time of 3 μs. In the second part, the coupling of a layer of InAs QDs to an adjacent two-dimensional hole gas (2DHG) is studied for a series of samples with different tunneling barriers. C-V measurements and time-resolved current measurements reveal the level-splittings of the many-particle hole levels in the InAs QDs. The values are found in good agreement with predictions from 8-band k·p theory. For the first time, these measurements are also performed at temperatures above 4 K. The emission and capture processes between the QDs and the 2DHG are studied and give insight into the type of the emission and capture processes, which change from pure tunneling to thermal-assisted tunneling when the temperature is increased. Based on the results of this work, recommendations for novel heterostructures are given: GaSb/AlxGa1−xAs with an Al-content beyond 30%, GaSbxP1−x/AlyGa1−yP QDs, and nitridebased QDs. These materials further increase the localization energy and the storage time in a QD-based memory, possibly to more than ten years at 300 K. An enhanced device design optimizes the device for fast operation at room temperature.
Complete Genome Sequence of Floricoccus penangensis ML061-4 Isolated from Assam Tea Leaf [Camellia sinensis var. assamica (J.W.Mast.) Kitam.]

Floricoccus penangensis is a Gram-positive coccoid organism that is a member of the lactic acid bacteria. F. penangensis ML061-4 was originally isolated from the surface of an Assam tea leaf, and its genome is herein shown to contain gene clusters predicted to be involved in complex carbohydrate metabolism and biosynthesis of secondary metabolites.
Wideband Asymmetric Single-Pole Double-Throw Switch Based on Back-to-Back Coupler Structure

In this letter, a wideband asymmetric single-pole double-throw (AS-SPDT) switch equipped with a back-to-back coupler structure is presented for fifth generation millimeter-wave band applications. By employing a back-to-back connection from two couplers, a balanced structure in the Rx mode and a reflection-type structure in the Tx mode are combined into a single circuit; a control signal is used to switch between the Rx and Tx modes. These two structures extend the 3-dB bandwidth (BW) and improve the isolation. The on-state transistor of the reflection-type structure can be controlled to improve <inline-formula> <tex-math notation="LaTeX">$P_{\mathrm{ 1dB}}$ </tex-math></inline-formula> in the Tx mode. The proposed AS-SPDT switch supports 28 and 38 GHz operation; the measured 3-dB BWs are 48 and 53 GHz in the Rx and Tx modes, respectively. In the Rx mode, the measured <inline-formula> <tex-math notation="LaTeX">${\mathrm{ IP}}_{\mathrm{ 1dB}}$ </tex-math></inline-formula> values are 12 and 13 dBm at 28 and 38 GHz, respectively. In the Tx mode, the measured <inline-formula> <tex-math notation="LaTeX">${\mathrm{ IP}}_{\mathrm{ 1dB}}$ </tex-math></inline-formula> values are 29 and 27 dBm at 28 and 38 GHz, respectively. In the available 3-dB BW, the proposed AS-SPDT switch has a wider 20-dB isolation BW than the other works. These results indicate that the proposed switch has wider 3-dB BW, better linearity, and high isolation than the other works.
An image understanding system based on the geometrized histograms method: finding the sky in road scenes

In this paper, the technique provided by the geometrized histogram method for segmentation and description of color images is developed and improved in order to analyze the adjacency relation of left and right germs of contrast objects (left and right contrast curves) on the STG. This adjacency relation involves and generalizes the adjacency relation for regions in classical segmentation methods (the so-called RAG). Using this order relation, the adjacency relation for left and right germs of contrast objects is established. This order relation is also employed for finding relations between left and right germs with prescribed geometric and color-intensity characteristic that are not adjacent and lay apart at a distance. In addition, the concept of contours that are close to vertical on STG is introduced. Based on the adjacency relation proposed, a technique for constructing complex contrast objects with a prescribed geometric shape and color-intensity description is proposed. The developed technique is applied to analyzing road scenes in order to find the sky in video sequences. The results of finding the object in video sequences by a program complex, implementing these ideas, are presented and discussed.
Effect of soil texture and hydraulic parameters on WRF simulations in summer in east China

This article investigated the effect of soil texture, i.e. 5‐min Food and Agriculture Organization soil texture (STFAO) and 30' Harmonized World Soil Database soil texture (STHWSD), and hydraulic parameters, i.e. US Department of Agriculture soil hydraulic parameters (SPUS) and China soil hydraulic parameters (SPCH), on the Weather Research and Forecasting (WRF) model simulation in summer in eastern China. Near‐surface meteorological fields from 365 automatic weather stations were used to evaluate the performance of WRF. Obvious differences between the two soil texture datasets and the two soil hydraulic parameter datasets were found. The simulated 2‐m temperature, 2‐m specific humidity, and 10‐m wind speed were improved significantly at a 95% confidence interval via bootstrap test when STHWSD was used. The agreement is weaker as SPUS was replaced by SPCH. Soil texture and hydraulic parameters affect surface energy partitioning and the distribution of precipitation. The influence of wilting point on WRF's performance is more significant than other soil hydraulic parameters.
Perception of Midwifery Students towards Characteristics of Clinical Teachers at Public Universities, Tigray, Ethiopia, 2016

Background: Clinical teaching lies at the heart of medical education. Clinical education is used in midwifery profession as a way to practice didactic information in hands on environment. The quality of learning in the clinical setting is greatly affected by clinical teachers. Objective: The aim of this study was to assess clinical teachers’ characteristics and their influence on learning perceived by Midwifery students. Methodology: This study was conducted at midwifery department of public universities in Tigray regional state, Ethiopia. Institution based cross sectional study design was utilized. A total of 286 participants using census method were included in the study that took at least one clinical course and were present during data collection. The nursing clinical teacher effectiveness inventory tool was used to collect data. Result: The frequently used characteristics were as the following in descending order: is self-confident, answers carefully and precisely questions and listens attentively but the clinical teachers were least at recognizing their own limitations, demonstrating clinical skill and judgment and offering special help when difficulties arise. Clinical teachers were best at their personality but least at their midwifery competence. The frequency use of characteristics had a moderate to high relationship with perceived facilitation of clinical learning. The items with high positive correlation were: gears instruction to students’ level of readiness, answers carefully and precisely questions raised by students, makes specific suggestions for improvement, questions students to elicit underlying reasoning, and provides specific practice opportunity. Conclusion and Recommendation: The clinical teachers were self-confident, answered questions carefully and precisely, listened attentively, encouraged active participation in discussion. When clinical teachers increase frequency of characteristics, so does learning in the clinical area too. To have better clinical learning, there should be orientation for new clinical teachers, work shop, evaluation and self-assessment of clinical teachers.
Oxidative damage from repeated tissue isolation for subculturing causes degeneration in Volvariella volvacea

The fungal fruiting body is the organized mycelium. Tissue isolation and mycelium succession are common methods of fungal species purification and rejuvenation in the production of edible mushrooms. However, repeated succession increases strain degeneration. In this study, we examined the effect of repeated tissue isolation from Volvariella volvacea fruitbodies on the occurrence of degeneration. The results showed that less than four times in succession improved production capacity, however, after 12 successions, the traits indicating strain degeneration were apparent. For instance, the density of aerophytic hyphae, hyphal growth rate and hyphal biomass were gradually reduced, while the hyphae branching was increased. Also, other degenerative traits such as prolonged production cycles and decreased biological efficiency became evident. In particular, after 19 successions, the strain degeneration became so severe no fruiting bodies were produces anymore. Meanwhile, with the increase in successions, the antioxidant enzyme activity decreased, reactive oxygen species (ROS) increased, the number of nuclei decreased, and the mitochondrial membrane potential decreased along with morphological changes in the mitochondria. This study showed that repeated tissue isolation increased oxidative damage in the succession strain due to the accumulation of ROS, causing cellular senescence, in turn, degeneration in V. volvacea strain.
Involving humans to learn attributes

However, unlike object categories, attributes are not well-defined. To see why, consider the following thought experiment. If a person is asked to draw a “boot”, the drawings of different people will likely not differ very much. But if a person is asked to draw what the attributes “formal” or “feminine” mean, drawings will vary. Drawings of a “forest” will likely all include a number of trees, but drawings of a “natural”, “open-area”, or “cluttered” scene will differ greatly among artists. Finally, if humans are asked to draw or even pick from a set of male actors an “attractive” or “masculine” person, responses will differ more than if they were asked to draw or select a “man”.
Decoding Quasi-Cyclic codes is NP-complete

We prove that the problem of decoding a Quasi-Cyclic (QC) code is NP-hard, and the corresponding decision problem is NP-complete. Our proof is based on a new characterization of quasi-cyclic codes closely related to linear random codes. We also discuss the cryptographic signiﬁcance of this result
Latency Matters: Real-Time Action Forecasting Transformer

We present RAFTformer, a realtime action forecasting transformer for latency-aware realworld action forecasting. RAFTformer is a two-stage fully transformer based architecture comprising of a video transformer backbone that operates on high resolution, short-range clips, and a head transformer encoder that temporally aggregates information from multiple short-range clips to span a long-term horizon. Additionally, we propose a novel self-supervised shuffled causal masking scheme as a model level augmentation to improve forecasting fidelity. Finally, we also propose a novel realtime evaluation setting for action fore-casting that directly couples model inference latency to overall forecasting performance and brings forth a hith-erto overlooked trade-off between latency and action fore-casting performance. Our parsimonious network design fa-cilitates RAFTformer inference latency to be 9x smaller than prior works at the same forecasting accuracy. Owing to its two-staged design, RAFTformer uses 94% less training compute and 90% lesser training parameters to outperform prior state-of-the-art baselines by 4.9 points on EGTEA Gaze+ and by 1.4 points on EPIC-Kitchens-100 validation set, as measured by Top-5 recall (T5R) in the offline setting. In the realtime setting, RAFTformer outperforms prior works by an even greater margin of upto 4.4 T5R points on the EPIC-Kitchens-100 dataset. Project Webpage: https://karttikeya.github. io/publication/RAFTformer/.
ALGEBRAICALLY EXTENDED 2D IMAGE REPRESENTATION

We present an algebraically extended 2D image representation in this paper. In order to obtain more degrees of freedom, a 2D image is embedded into a certain geometric algebra. Combining methods of differential geometry, tensor algebra, monogenic signal and quadrature filter, the novel 2D image representation can be derived as the monogenic extension of a curvature tensor. The 2D spherical harmonics are employed as basis functions to construct the algebraically extended 2D image representation. From this representation, the monogenic signal and the monogenic curvature signal for modeling intrinsically one and two dimensional (i1D/i2D) structures are obtained as special cases. Local features of amplitude, phase and orientation can be extracted at the same time in this unique framework. Compared with the related work, our approach has the advantage of simultaneous estimation of local phase and orientation. The main contribution is the rotationally invariant phase estimation, which enables phase-based processing in many computer vision tasks.
BETTER MONITORIZATION AND PREDICTABILITY FOR COMPUTATION INFRASTRUCTURES THROUGH DATA FUSION

Cloud computing provides a wide variety of services that allow its users to develop and maintain applications at a relatively low cost. The services o ﬀ ered by a cloud system also provide the ability to ﬂexibly scale the resources of any application. Because of these beneﬁts, cloud data centers are extremely popular. However, although generally considered secure, for circumstances involving the management of sensitive data some companies opt for a hybrid solution that involves storing some or all of their resources in a private data center, and occasionally, when system utilization reaches higher levels, the execution of some components is assigned to a public cloud data center, ensuring the integrity and security of that data without a ﬀ ecting service performance. Its however essential that such a migration services happens before the system is overloaded, as to avoid further negative impact to system performance, while avoiding services running in the cloud needlessly due to its increased costs. To mitigate this problem it is possible to apply methods that aim to predict periods of high system utilization. The prediction results can later be utilized to migrate resources before usage spikes occur, in a time window where it is possible to deal e ﬀ ectively with them. In this work we intend to explore new strategies to monitor and extract metrics from di ﬀ erent components of a private data center, and combine this information in order to characterize the level of utilization of the system. It is also intended, based on the information extracted, to investigate solutions that predict future system utilization and to develop a scaling mechanism that allows certain resources to be sent to and removed from a the private data center to a public cloud provider. The results of each solution will be compared for their accuracy, execution speed, and the improvement in response time that can be achieved in the managed system. This thesis is conducted in collaboration with NOVO BANCO.