Miracle-dz/UniFAR-FTUs huggingface dataset:
Likelihood analysis of a first‐order autoregressive model with exponential innovations

Abstract. This paper derives the exact distribution of the maximum likelihood estimator of a first‐order linear autoregression with an exponential disturbance term. We also show that, even if the process is stationary, the estimator is T‐consistent, where T is the sample size. In the unit root case, the estimator is T2‐consistent, while, in the explosive case, the estimator is ρT‐consistent. Further, the likelihood ratio test statistic for a simple hypothesis on the autoregressive parameter is asymptotically uniform for all values of the parameter.
Modeling the Effects of Printed-Circuit-Board Parasitics on the Switching Performance of Wide-Bandgap Applications

Wide-bandgap (WBG) devices, like devices based on Silicon-Carbide (SiC) and Gallium-Nitride (GaN), incorporate smaller capacitances and thus faster switching dynamics than traditional semiconductor devices. The size of these capacitances reaches the same order of magnitude than the parasitic elements of the printed circuit board (PCB). This has to be addressed effectively, in order to achieve the full potential of WBG devices. A novel methodology is introduced in this work, which helps to predict the effects of parasitic components of the PCB layout on the dynamic behavior of a power switch. The proposed methodology provides a detailed model, which incorporates the parasitic elements of the PCB design. This model is translated into a simple metamodel, using a design-of-experiment (DoE) methodology. With this metamodel, a design-space which utilizes single and multiple parasitic and discrete parameters to predict the impact on the switching behavior is generated. The parasitic parameters are estimated with simple geometry approximations of the PCB design. The obtained metamodel enables PCB designers to map performance objectives of the switching dynamics, such as voltage/current overshoot, to layout parameters before manufacturing. The methodology is validated with simulation and experimental results in the context of the gate-source voltage overshoot of a GaN-prototype, showing high accuracy.
Chenodeoxycholic Acid Ameliorates AlCl3-Induced Alzheimer’s Disease Neurotoxicity and Cognitive Deterioration via Enhanced Insulin Signaling in Rats

Insulin resistance is a major risk factor for Alzheimer’s disease (AD). Chenodeoxycholic acid (CDCA) and synthetic Farnesoid X receptor (FXR) ligands have shown promising outcomes in ameliorating insulin resistance associated with various medical conditions. This study aimed to investigate whether CDCA treatment has any potential in AD management through improving insulin signaling. Adult male Wistar rats were randomly allocated into three groups and treated for six consecutive weeks; control (vehicle), AD-model (AlCl3 50 mg/kg/day i.p) and CDCA-treated group (AlCl3 + CDCA 90 mg/kg/day p.o from day 15). CDCA improved cognition as assessed by Morris Water Maze and Y-maze tests and preserved normal histological features. Moreover, CDCA lowered hippocampal beta-site amyloid precursor protein cleaving enzyme 1 (BACE1) and amyloid-beta 42 (Aβ42). Although no significant difference was observed in hippocampal insulin level, CDCA reduced insulin receptor substrate-1 phosphorylation at serine-307 (pSer307-IRS1), while increased protein kinase B (Akt) activation, glucose transporter type 4 (GLUT4), peroxisome proliferator-activated receptor gamma (PPARγ) and glucagon-like peptide-1 (GLP-1). Additionally, CDCA activated cAMP response element-binding protein (CREB) and enhanced brain-derived neurotrophic factor (BDNF). Ultimately, CDCA was able to improve insulin sensitivity in the hippocampi of AlCl3-treated rats, which highlights its potential in AD management.
Generalized Delta Mechanisms from Soft Actuators

Soft robots, and more specifically soft actuators, have the promise to create high degree of freedom actuation. However, designing these actuators to achieve complex motions is difficult. Here we propose the design of a soft mechanism class that can be additively manufactured and easily and intuitively designed. The actuators use parallel structures of simple soft linear-extension actuators to create higher degree of freedom movements without additional joints or mechanical components. We show that depending on configuration, the actuators can be designed to create pure planer motion, motion in 3-space, and rotation. We also analyze the position and force workspaces for a set of designs, comparing outputs across linear scaling and number of simple actuators. Lastly, we show a demonstration in distributed locomotion that highlights the ease of manufacturing and the use of the large number of controllable degrees of freedom.
Structural evidence for an in trans base selection mechanism involving Loop1 in polymerase μ at an NHEJ double-strand break junction

Eukaryotic DNA polymerase (Pol) X family members such as Pol μ and terminal deoxynucleotidyl transferase (TdT) are important components for the nonhomologous DNA end-joining (NHEJ) pathway. TdT participates in a specialized version of NHEJ, V(D)J recombination. It has primarily nontemplated polymerase activity but can take instructions across strands from the downstream dsDNA, and both activities are highly dependent on a structural element called Loop1. However, it is unclear whether Pol μ follows the same mechanism, because the structure of its Loop1 is disordered in available structures. Here, we used a chimeric TdT harboring Loop1 of Pol μ that recapitulated the functional properties of Pol μ in ligation experiments. We solved three crystal structures of this TdT chimera bound to several DNA substrates at 1.96–2.55 Å resolutions, including a full DNA double-strand break (DSB) synapsis. We then modeled the full Pol μ sequence in the context of one these complexes. The atomic structure of an NHEJ junction with a Pol X construct that mimics Pol μ in a reconstituted system explained the distinctive properties of Pol μ compared with TdT. The structure suggested a mechanism of base selection relying on Loop1 and taking instructions via the in trans templating base independently of the primer strand. We conclude that our atomic-level structural observations represent a paradigm shift for the mechanism of base selection in the Pol X family of DNA polymerases.
The melREDCA Operon Encodes a Utilization System for the Raffinose Family of Oligosaccharides in Bacillus subtilis

Bacillus subtilis utilizes different polysaccharides produced by plants. These carbohydrates are primarily degraded by extracellular hydrolases, and the resulting oligo-, di-, and monosaccharides are transported into the cytosol via phosphoenolpyruvate-dependent phosphotransferase systems (PTS), major facilitator superfamily, and ATP-binding cassette (ABC) transporters. In this study, a new carbohydrate utilization system of B. subtilis responsible for the utilization of α-galactosides of the raffinose family of oligosaccharides (RFOs) was investigated. RFOs are synthesized from sucrose in plants and are mainly found in the storage organs of plant leaves. Our results revealed the modus operandi of a new carbohydrate utilization system in B. subtilis. ABSTRACT Bacillus subtilis is a heterotrophic soil bacterium that hydrolyzes different polysaccharides mainly found in the decomposed plants. These carbohydrates are mainly cellulose, hemicellulose, and the raffinose family of oligosaccharides (RFOs). RFOs are soluble α-galactosides, such as raffinose, stachyose, and verbascose, that rank second only after sucrose in abundance. Genome sequencing and transcriptome analysis of B. subtilis indicated the presence of a putative α-galactosidase-encoding gene (melA) located in the msmRE-amyDC-melA operon. Characterization of the MelA protein showed that it is a strictly Mn2+- and NAD+-dependent α-galactosidase able to hydrolyze melibiose, raffinose, and stachyose. Transcription of the msmER-amyDC-melA operon is under control of a σA-type promoter located upstream of msmR (PmsmR), which is negatively regulated by MsmR. The activity of PmsmR was induced in the presence of melibiose and raffinose. MsmR is a transcriptional repressor that binds to two binding sites at PmsmR located upstream of the −35 box and downstream of the transcriptional start site. MsmEX-AmyCD forms an ATP-binding cassette (ABC) transporter that probably transports melibiose into the cell. Since msmRE-amyDC-melA is a melibiose utilization system, we renamed the operon melREDCA. IMPORTANCE Bacillus subtilis utilizes different polysaccharides produced by plants. These carbohydrates are primarily degraded by extracellular hydrolases, and the resulting oligo-, di-, and monosaccharides are transported into the cytosol via phosphoenolpyruvate-dependent phosphotransferase systems (PTS), major facilitator superfamily, and ATP-binding cassette (ABC) transporters. In this study, a new carbohydrate utilization system of B. subtilis responsible for the utilization of α-galactosides of the raffinose family of oligosaccharides (RFOs) was investigated. RFOs are synthesized from sucrose in plants and are mainly found in the storage organs of plant leaves. Our results revealed the modus operandi of a new carbohydrate utilization system in B. subtilis.
Scene Matching in GPS Denied Environments: A Comparison of Methods for Orthophoto Registration

Unmaned Aerial Systems (UAS) is a subject with great appeal, nowadays. Suitable applications for this kind of vehicles are countless. This work presents a study on scene matching (navigation with global positioning using image registration) in GPS denied environments. Usually, the problem is solved by fusing inertial data with other sources of displacement measurements like simultaneous localization and mapping or visual odometry. Although helpful, those methods establish a navigation system based on relative positioning, since they are limited to foreseeing displacements from previous states. Image registration can refresh the UAS position with georeferenced data, i.e., an absolute global position. This work reaches that goal through a detailed analysis of methods capable of extracting image information (e.g, edges or other invariant key points), enabling the registration process and consequently the estimation of position. Our results were quantified in terms of error estimation and time cost for computation. They have shown that good performance is achieved with a Convolutional Neural Network complemented with SURF approach.
A Deep Convolutional Neural Network for Interrelationship Identification between Humans from Images

The paper proposes a deep convolutional neural network for visual categorization of different interrelationships between humans from digital images. To achieve this goal, we first generated a dataset of interrelationships containing two interrelationship classes i.e. handshaking and hugging. Our proposed network having around 2 lakh neurons is trained with 8 lakh parameters. The network contains a total of seven layers i.e. two convolution layers each followed by max pooling layers and fully connected layers. Output layer contains a sigmoid function providing binary outputs i.e. 0 for one class and 1 for another class. To maintain the nonlinearity of images, Rectified Linear Units (ReLUs) have been used in each convolution and fully connected layers. The model generates an average accuracy of approximately 81%. Data augmentation technique has also been applied to reduce over-fitting.
Constant On-Time Multi-Mode Digital Control with Superior Performance and Programmable Frequency

The need for smaller size and extended battery life in portable devices poses a tough challenge to design multi-mode digital control in DC-DC converters while operating over a wide range of load current and input voltage. This paper presents a multi-mode digital controller which shares a common constant on-time modulator and achieves high efficiency, fast transient response, smooth transitions, and programmable switching frequency by dynamically adjusting the on-time with the input voltage during light load conditions to keep the voltage ripple within the desired band. The digital modulator uses the event-based sampling for voltage-loop which achieves inherent current-loop stability. The proposed scheme offers a natural transition to DCM. Further, the stability analysis using discrete-time model and design of the proposed scheme are discussed. Both the buck and boost converter prototypes are made, and the proposed scheme is implemented using an FPGA device.
Hypermongone C Accelerates Wound Healing through the Modulation of Inflammatory Factors and Promotion of Fibroblast Migration

The physiology of wound healing is dependent on the crosstalk between inflammatory mediators and cellular components of skin regeneration including fibroblasts and endothelial cells. Therefore, strategies to promote healing must regulate this crosstalk to achieve maximum efficacy. In light of the remarkable potential of natural compounds to target multiple signaling mechanisms, this study aims to demonstrate the potential of hypermongone C, a polycyclic polyprenylated acylphloroglucinol (PPAP), to accelerate wound closure by concurrently enhancing fibroblast proliferation and migration, promoting angiogenesis, and suppressing pro-inflammatory cytokines. This compound belongs to a family of plants (Hypericum) that traditionally have been used to treat injuries. Nevertheless, the exact biological evidence to support the claims is still missing. The results were obtained using a traditional model of cell scratch assay and endothelial cell tube formation, combined with the analysis of protein and gene expression by macrophages. In summary, the data suggest that hypermongone C is a multi-targeting therapeutic natural compound for the promotion of tissue repair and the regulation of inflammation.
Multijoint Musculoarticular Stiffness Derived From a Perturbation Is Highly Variable

Abstract Schofield, M, Tinwala, F, Cronin, J, Hébert-Losier, K, and Uthoff, A. Multijoint musculoarticular stiffness derived from a perturbation is highly variable. J Strength Cond Res 35(9): 2498–2503, 2021—Testing musculoarticular stiffness may provide insights into multijoint elastic properties. Yet, most research has focused on quantifying stiffness, or elastic potential, at a single joint. The purpose of this study was to quantify the test-retest reliability of musculoarticular stiffness derived from the perturbation technique across the bench pull, bench press, and squat movements. Eight resistance-trained men performed bench pull, bench press, and squat repetition maximums, after which a perturbation protocol was tested over multiple days. During the 3 movements, a brief perturbation was applied to the bar. The resulting sinusoidal wave was measured by an underbench force plate and a linear position transducer attached to the bar. From the sinusoidal wave, stiffness was derived and found to be unreliable across movements and days (change in mean: −35.1 to 15.8%; coefficient of variation: 7.1–111%; intraclass correlation: −0.58 to −0.89). Squat data were removed from the analysis entirely because of the inability to consistently determine the perturbations on the force plate. Practitioners need to be aware that musculoarticular stiffness as measured using the perturbation technique on the movements performed in this study has considerable limitations in terms of reproducibility.
RLS-Based Adaptive Feedforward Control of Cranes with Double Pendulum Dynamics

Sway damping control of cranes with uncertain double pendulum configuration is a common problem in practice since payload geometry and chain length between hook and load are usually unknown. In order to improve reference tracking accuracy during operation and reduce overshoots as well as residual load sway after set point transitions, this paper presents an indirect adaptive feedforward controller based on differential flatness and a parameter adaptation using recursive least squares estimation (RLS). In addition, a linear-quadratic-gaussian feedback controller with verified robustness is used for stabilization and disturbance rejection. For experimental validation the proposed control scheme is applied at a lab-scale bridge crane.
Neural Program Lattices

We propose the Neural Program Lattice (NPL), a neural network that learns to perform complex tasks by composing low-level programs to express high-level programs. Our starting point is the recent work on Neural Programmer-Interpreters (NPI), which can only learn from strong supervision that contains the whole hierarchy of low-level and high-level programs. NPLs remove this limitation by providing the ability to learn from weak supervision consisting only of sequences of low-level operations. We demonstrate the capability of NPL to learn to perform long-hand addition and arrange blocks in a grid-world environment. Experiments show that it performs on par with NPI while using weak supervision in place of most of the strong supervision, thus indicating its ability to infer the high-level program structure from examples containing only the low-level operations.
Can clients understand our instructions?

This study was designed to determine whether or not clients in an ambulatory care setting read at a level that allowed them to comprehend the written materials available for patient education. First, 106 adults waiting for clinic appointments were interviewed, and their reported and actual reading levels were compared. Reported reading levels, indicated by the clients' last grade completed in school, were significantly higher (mean—3.1 grades) than their actual reading levels, indicated by scores on the Wide Range Achievement Test (WRAT). Second, the readability levels of written materials available for patient education were evaluated. The mean readability level for the 28 instructional texts examined was 11.2 grades. The majority (54.7%) of study participants read at levels that did not allow them to comprehend any of the patient education materials available at their site of primary care. In addition, 25 percent of the texts examined were beyond the comprehension of all participants.
Body composition , energy expenditure and physical activity Intrauterine growth restriction and overweight , obesity , and stunting in adolescents of indigenous communities of Chiapas , Mexico

Background/objectives Intrauterine growth restriction (IUGR) and low-birth-weight (LBW) are determinant factors in the development of metabolic diseases in children and adolescents. To estimate the magnitude of the association between LBW and IUGR with stunting or obesity among adolescents of two indigenous regions of the southern State of Chiapas, Mexico. Subjects/methods We assessed a random sample of 303 adolescents selected from a birth cohort study (2003) conducted in three hospitals serving urban and rural communities of Tzotzil-Tzeltal and Selva regions of Chiapas, Mexico. Sociodemographic and anthropometric data from a sample of adolescents were correlated with their anthropometric data at birth (weight, length for age). Logistic regression models were fitted to estimate odds ratios (OR) with 95% confidence intervals to measure the magnitude of the association among the variables of interest. Models were adjusted for potential confounders. Results In all, 12% of the sample had LBW and 28.8% IUGR. In total, 29% of adolescents were overweight/obese and 21% were stunted. We found a statistically significant association between IUGR and a lower risk of being overweight/obese. A higher probability for stunting was observed for LBW and IUGR. Conclusions Stunting and overweight/obesity prevalence in this population of adolescents was high and was associated with IUGR.
EMI Evaluation and Filter Design of a SiC-Based 3-Level UPS

Uninterruptible power supply (UPS) systems are widely used in data centers or hospitals where continuity of electric power has to be ensured to protect critical loads. The adoption of SiC MOSFETs in the UPS systems enables improvement of both efficiency and power density of the systems. However, more concern on electromagnetic interference (EMI) noise arises because of the high switching speed. Furthermore, the UPS under study is comprised of multiple power conversion stages: rectifier, inverter and dc-dc stage. The EMI mechanism changes with the operation mode of UPS, which complicates the evaluation and containment. In this paper, EMI evaluation and EMI containment with filters have been investigated for a full-SiC UPS comprised of three-level Neutral Point Clamped (NPC) phase legs. An EMI test environment is established for conducted EMI emission measurement under different modulation methods and operation modes. EMI filters are designed to meet the IEC 62040-2 standard and verified with the prototype.
Reinforcement Learning for Robots with special reference to the Inverse kinematics solutions

Reinforcement learning is an important learning paradigm apart from supervised and unsupervised learning which is particularly suitable for Robotics system due to its inherent structural complexity, high degrees of nonlinearity and few parameter predictability. As a result of which an accurate mathematical model is difficult to build which has close resemblance with the field behaviours of the robot. To help solve this problem, Q learning based reinforcement algorithm has been proposed for learning the inverse kinematics mapping. The results have been compared with the analytical solutions of the well-known inverse kinematics solution.
Linear and Nonlinear Low Level Control of a Soft Pneumatic Actuator

The research on soft material robots has been a highly discussed topic in recent years. Due to the nonlinear material behavior, the control of the pressure in the actuators chambers is difficult. In this paper a concept for low level control of soft pneumatic actuators is developed. For this purpose a test bed with a proportional directional valve is designed. The concept includes mathematical models of the control element. The actuator is modeled as a sphere. For the valve the flow through the opened area is modeled and the tubes friction and systems leakage are also considered. All needed and unknown parameters are identified with particle swarm identification. Due to the non-linearity of the valve and the actuator model, approaches for nonlinear control will be examined. A state space representation of the plant and control element will be assembled. First a PID controller is developed, which is tuned with the Ziegler-Nichols method. In contrast, a robust control theory, the sliding mode control, is investigated. It will be shown, that the PID controller as well as the sliding mode control are compatible with the low level control. It becomes apparent, that the PID controller reacts inferior compared to the sliding mode controller, if there is a system change like rising in leakage. The control strategies are also tested on the real plant and are appropriate strategies for tracking a trajectory.
Comparing the effects of 6 months aerobic exercise and resistance training on metabolic control and β‐cell function in Chinese patients with prediabetes: A multicenter randomized controlled trial

It is clear that aerobic training (AT) can delay pancreatic exhaustion and slow the progression from prediabetes to type 2 diabetes (T2D), but there is little information regarding the effects of resistance training (RT) in people with prediabetes. This study compared the effectiveness of RT and AT in improving metabolic control and protecting β‐cell function in people with prediabetes.