Miracle-dz/UniFAR-FTUs huggingface dataset:
Generalized Chebyshev Function of Arbitrary Order With Real-Frequency Zero Pairs in an Explicit Rational Polynomial Expression

Generalized Chebyshev functions of an arbitrary order with up to three real-frequency zero pairs are derived in an explicit rational polynomial expression. Given in-band ripple level and positions of the zero pairs, numerator of the rational function is a sum of Chebyshev polynomials of the first kind weighted by constants specified by the zeros, and the denominator is simply a successive product of $\left(a_{i}^{2}-\omega^{2}\right)$, given that $\pm a_{i}$ are the designated real-frequency zero pair. Based on these analytical generalized Chebyshev filtering expressions, effort required by computer in synthesis of a lowpass prototype filter is at most a root-searching routine for polynomials. The whole synthesis process is straight-forward and needs neither iteration nor optimization.
Four-way Power Combiner with Spring Contact Probes for High Power SSPA Modules

We propose a low-loss, high-heat dissipative fourway power combiner that can be applied to multiple monolithic microwave integrated circuits (MMIC) with flip-chip bonding for high power solid-state power amplifier modules. This structure mainly consists of a two-way power combiner comprising an air-filled substrate integrated waveguide (ASIW) and the Gysel power combiner formed on glass substrate to reduce loss. In addition, we employ spring contact probes to connect the ASIW to glass substrate. We achieve close contact between the MMIC and heat sink to reduce thermal resistance due to the flexibility of spring contact probes. We design and fabricate the proposed structure without MMIC to confirm the high performance of the power combiner. The simulation and measurement results of the prototype are similar, and the combiner loss is 0.5–1.0 dB.
A 14 Bit 500 MS/s CMOS DAC Using Complementary Switched Current Sources and Time-Relaxed Interleaving DRRZ

A 14 bit 500 MS/s current-steering digital-to-analog converter (DAC) was designed and fabricated in 0.13 μm CMOS process. For traditional wide-band current-steering DACs, the spurious-free dynamic range (SFDR) is limited by nonlinear distortions from the code-dependent load variations and the code-dependent switching glitches. They are analyzed in this paper and mitigated by the proposed complementary switched current sources (CSCS) and time-relaxed interleaving digital- random-return-to-zero (TRI-DRRZ), respectively. The proposed techniques are fabricated and measured, with an SFDR of 84.8 dB at 11 MHz signal frequency and 73.5 dB at 244 MHz. The DAC consumes 299 mW from a mixed power supply of 1.2 V and 2.5 V with an active area of 1.85×0.65 mm2.
Feasibility of Cervical Spine Fracture Detection Using Non-Conventional Slices

Cervical spine fractures are a medical emergency that must be dealt with within a certain period. It can lead to paralysis or severe life-threatening effects if there is a delay in the identification of fractures. It can be treated well if detected in the early stages. A system that automates the process of fracture detection in the cervical spine would assist radiologists and doctors in detecting fractures faster and overcoming diagnostic or human errors. This can be achieved with the help of Computer-assisted detection (CAD) systems. We propose a Convolutional Neural Network (CNN) based approach for the automated detection of cervical spine fractures. We have provided a proof of concept using the sagittal and coronal slices generated from axial view CT scans to predict fractures in the cervical spine. The system performs a binary classification task of detecting fracture and non-fracture cases in the cervical spine. We have used a dataset provided by the Radiology Society of North America which contains 2,018 records with a marginal difference in the number of positive and negative cases.
Fast Randomized Kernel Methods With Statistical Guarantees

One approach to improving the running time of kernel-based machine learning methods is to build a small sketch of the input and use it in lieu of the full kernel matrix in the machine learning task of interest. Here, we describe a version of this approach that comes with running time guarantees as well as improved guarantees on its statistical performance. By extending the notion of \emph{statistical leverage scores} to the setting of kernel ridge regression, our main statistical result is to identify an importance sampling distribution that reduces the size of the sketch (i.e., the required number of columns to be sampled) to the \emph{effective dimensionality} of the problem. This quantity is often much smaller than previous bounds that depend on the \emph{maximal degrees of freedom}. Our main algorithmic result is to present a fast algorithm to compute approximations to these scores. This algorithm runs in time that is linear in the number of samples---more precisely, the running time is $O(np^2)$, where the parameter $p$ depends only on the trace of the kernel matrix and the regularization parameter---and it can be applied to the matrix of feature vectors, without having to form the full kernel matrix. This is obtained via a variant of length-squared sampling that we adapt to the kernel setting in a way that is of independent interest. Lastly, we provide empirical results illustrating our theory, and we discuss how this new notion of the statistical leverage of a data point captures in a fine way the difficulty of the original statistical learning problem.
Study of CFRP adhesive bonds influenced by manufacturing-related contaminations

Composite materials are commonly used in many branches of industry. One of the effective methods to join CFRP parts is the adhesive bonding. There is a search of effective methods for quality assurance of bonded parts. There is a need for pre- and post-bond inspection to ensure proper bonding and verify its quality. Research reported here focuses on post-bond inspection of bonded CFRP parts. In this paper we report investigations of samples that were modified with contamination that can be encountered during the manufacturing process of the CFRP parts. The contaminations were introduced before adhesive bonding, and the effect of the contamination on the quality bond is studied. First of the investigated cases was release agent contamination prepared by dip-coating of clean CFRP plates. The release agent is used during the production of composite elements and can contaminate the surface to be bonded. The second case was the moisture contamination. It was obtained by conditioning of the samples in humid conditions. Moisture contamination can be gained from water-coupled ultrasonics or during transportation of unprotected parts. The third type of contamination had more local character. It simulated fingerprints. Artificial sweat was used. The fingerprint contamination can be caused by improper handling of the parts. Apart from single contamination, also mixed contamination cases were studied, as well as curved samples. The samples were studied in non-destructive approach. It was shown that for some of the cases the detection is possible.
Petunia, Your Next Supermodel?

Plant biology in general, and plant evo–devo in particular would strongly benefit from a broader range of available model systems. In recent years, technological advances have facilitated the analysis and comparison of individual gene functions in multiple species, representing now a fairly wide taxonomic range of the plant kingdom. Because genes are embedded in gene networks, studying evolution of gene function ultimately should be put in the context of studying the evolution of entire gene networks, since changes in the function of a single gene will normally go together with further changes in its network environment. For this reason, plant comparative biology/evo–devo will require the availability of a defined set of ‘super’ models occupying key taxonomic positions, in which performing gene functional analysis and testing genetic interactions ideally is as straightforward as, e.g., in Arabidopsis. Here we review why petunia has the potential to become one of these future supermodels, as a representative of the Asterid clade. We will first detail its intrinsic qualities as a model system. Next, we highlight how the revolution in sequencing technologies will now finally allows exploitation of the petunia system to its full potential, despite that petunia has already a long history as a model in plant molecular biology and genetics. We conclude with a series of arguments in favor of a more diversified multi-model approach in plant biology, and we point out where the petunia model system may further play a role, based on its biological features and molecular toolkit.
Pothole Detection Using Deep Learning

Potholes are a significant road infrastructure problem that poses safety risks to drivers and causes substantial damage to vehicles. Accurate and real time detection of potholes is crucial for timely repairs and road maintenance. This paper presents a novel approach for pothole detection using YOLOv8, an advanced version of the You Only Look Once (YOLO) object detection algorithm. The proposed method leverages the advantages of YOLOv8, which combines state-of-the-art object detection techniques with improved network architecture for enhanced accuracy and efficiency. A comprehensive dataset of road images containing various pothole instances is collected and used to train the YOLOv8 model. Transfer learning techniques are employed to fine-tune the model for pothole detection specifically. To evaluate the performance of the proposed method, extensive experiments are conducted on different road scenarios, including varying lighting conditions, road types, and pothole sizes. The results demonstrate that the YOLOv8-based pothole detection system achieves high accuracy and real-time processing capability, making it suitable for deployment in smart city infrastructure and vehicle navigation systems. The contributions of this work lie in the development of an effective and efficient pothole detection system using YOLOv8, capable of identifying potholes accurately in real-world scenarios. This system can significantly aid road maintenance authorities in identifying potholes promptly, facilitating timely repairs and ultimately leading to safer and smoother road conditions for drivers and pedestrians alike.
Ultrasound biomicroscopy and iris pigment dispersion: a case―control study

Background/aims The study involved eyes affected by pigment dispersion syndrome (PDS) or pigmentary glaucoma (PG) investigated by ultrasound biomicroscopy (UBM). Different irido-corneal parameters were assessed and compared with those from healthy controls. The aim was to investigate the capacity of the UBM in differentiating the cases and, potentially, in confirming the pathogenic mechanisms. Methods Patients with a first diagnosis of PDS or PG were included. A cohort of healthy volunteers matched for sex, age and refractive errors was recruited. All underwent UBM examination: the following parameters were assessed in relaxed and stimulated accommodative state in one eye: iris–lens contact (ILC), irido-corneal angle (ICA) and iris concavity (IC). A receiver operating characteristic (ROC) analysis assessed the ability of UBM to discriminate between subjects with and without PDS/PG. Results There were 24 eyes in the case group: four diagnosed as PG and the remaining 20 as PDS. There were 25 eyes in the control group. The two groups were statistically superimposable except for baseline intraocular pressure, which was higher in the case group (p=0.0001). All UBM parameters were statistically different between the two groups. ICA in near vision was the best-performing parameter, reaching a sensitivity (=specificity) of 0.875 with a cut-off at 53.0°. The second most sensitive parameter was IC, still in near vision. Conclusion All UBM parameters examined were statistically different between the two groups. ROC analysis showed ICA and IC in near vision to be the most discriminatory parameters. This evidence confirms the importance of iris movements in inducing the particular features of PDS/PG.
Late-onset agoraphobia: general population incidence and evidence for a clinical subtype.

OBJECTIVE The purpose of this study was to estimate the general population incidence of late-life agoraphobia and to define its clinical characteristics and risk factors. METHOD A total of 1,968 persons ≥65 years old were randomly recruited from the electoral rolls of the district of Montpellier, France. Prevalent and incident agoraphobia diagnosed with a standardized psychiatric examination and validated by a clinical panel were assessed at baseline and over a 4-year follow-up. RESULTS The 1-month baseline prevalence of agoraphobia was estimated to be 10.4%. Among persons with agoraphobia, 10.9% reported having their first episode at age 65 or above. During the 4-year follow-up, 11.2% of participants without agoraphobia at baseline had a first episode, resulting in an incidence rate of 32 per 1,000 person-years. These 132 incident late-onset cases were associated with higher incidence rates of anxiety disorders and suicidal ideation. Of the incident cases, only two were characterized by past or concurrent panic attacks, a rate that was not significantly different from that of the noncase group. The principal baseline risk factors for incident cases, derived from a multivariate model incorporating all significant risk factors, were younger age at onset (odds ratio=0.94, 95% CI=0.90-0.99), poorer visuospatial memory performance (odds ratio=1.60, 95% CI=1.02-2.49), severe depression (odds ratio=2.62, 95% CI=1.34-5.10), and trait anxiety (odds ratio=1.73, 95% CI=1.03-2.90). No significant association was found with cardiac pathologies. CONCLUSIONS Agoraphobia has a high prevalence in the elderly, and unlike cases in younger populations, late-onset cases are not more common in women and are not associated with panic attacks, suggesting a late-life subtype. Severe depression, trait anxiety, and poor visuospatial memory are the principal risk factors for late-onset agoraphobia.
Bidirectional English-Marathi Translation using Pretrained Models: A Comparative Study of Different Pre-Trained Models

This study investigates the use of pre-trained models for English-to-Marathi translation. The purpose of this study is to investigate English-to-Marathi translation utilising pre-trained multilingual language models. The research examines multiple translation models accessible in the Hugging Face library, such as mbart-large-50-many-to-many-mmt, IndicBART, m2m100_1. 2B, Helsinki-NLP/opus-mt-mr-en, and umtS-base. BLEU score, pre-cision, brevity penalty, ChrF score, TER score, Google Blue and Rouge are among the assessment criteria used. Because of this, we now have a bidirectional translation model, which is formed by the integration of two unidirectional models-one that translates English to Marathi and the other that translates Marathi to English. In spite of the inherent difficulties posed by language asymmetry and the limited parallel data available in bidirectional models, the purpose of this study is to investigate potential solutions to these roadblocks. According to the findings, the performance of the optimized MBART model has significantly improved, whilst the performance of the Helsinki-NLP model has essentially stayed the same. Notably, making use of MBART's setup and weight transfer led to significant improvements being made to the AI4Bharat model.
Algebraic Complexity of Path Problems

— Algcbraic complexity ofpath problems is studied using straight line programs over arbitrary semirings as a computational model. In contrast to n 3 lower bounds in the literature, graph sensitive bounds are proven which applyfor any input graph andany semiring. It is shown that these bounds are tightjor all cycle-free graphs and some cyclic graphs. Résumé. — On étudie la complexité algébrique des problèmes de cheminement avec des programmes linéaires sur des semi-anneaux quelconques en guise de modèle de calcul. On donne des bornes dépendant du graphe, qui s'appliquent à n'importe quel graphe d'entrée et n'importe quel semi-anneau, par opposition aux bornes en n 3 que l'on trouve dans la littérature. Ces bornes sont stricte pour tous les graphes sans cycles. and their and helpful discussions, and
What is the shape of the distribution of protein conformations at equilibrium?

According to the thermodynamic hypothesis, the native state of proteins is that in which the free energy of the system is at its lowest, so that at normal temperature and pressure, proteins evolve to that state. We selected four proteins representative of each of the four classes, and for each protein make four simulations, one starting from the native structure and the other three starting from the structure obtained by threading the sequence of one protein onto the native backbone fold of the other three proteins. Because of their large conformational distances with respect to the native structure, the three alternative initial structures cannot be considered as local minima within the native ensemble of the corresponding protein. As expected, the initial native states are preserved in the . 5 μs simulations performed here and validate the simulations. On the other hand, when the initial state is not native, an analysis of the trajectories does not reveal any evolution towards the native state, during that time. These results indicate that the distribution of protein conformations is multipeak shaped, so that apart from the peak corresponding to the native state, there are other peaks associated with average structures that are very different from the native and that can last as long as the native state.
Skills associated with employment positions in SMEs and favourable attitudes toward self-employment: Longitudinal evidence from students who participated in the shell technology enterprise programme

Abstract Successive British governments have encouraged young people to accumulate skills and attributes that would enable them to obtain jobs in small and medium-sized enterprises (SMEs) as well as develop careers in enterprise. This article evaluates the contribution of the 1994 Shell Technology Enterprise Programme (STEP) that subsidised the placement of students in SMEs. In 1997, responses were gathered from STEP students as well as a control group of non-STEP students. The human capital profiles of students reporting full-time employment positions in smaller private firms as well as those reporting a favourable attitude towards self-employment or business ownership were ascertained. Participation in the programme was not found to be significantly associated with the selected outcomes. Skills and attributes honed by the programme were, however, significantly associated with the selected outcomes. Policy-makers need to appreciate that the skills and attributes reported by students associated with the propensity to obtain employment positions in smaller private firms are not the same as those associated with the propensity to report a favourable attitude towards self-employment or business ownership.
Fuzzy redundancy resolution and motion coordination for underwater vehicle-manipulator systems

The problem of redundancy resolution and motion coordination between the vehicle and the manipulator in underwater vehicle-manipulator systems (UVMSs) is addressed in this paper. UVMSs usually possess more degrees of freedom than those required to perform end-effector tasks; therefore, they are redundant systems and kinematic control techniques can be applied aimed at achieving additional control objectives besides tracking of the end-effector trajectory. In this paper, a task-priority inverse kinematics approach to redundancy resolution is merged with a fuzzy technique to manage the vehicle-arm coordination. The fuzzy technique is used both to distribute the motion between vehicle and manipulator and to handle multiple secondary tasks. Numerical case studies are developed to demonstrate effectiveness of the proposed technique.
EFFECT OF FORMULATION FACTORS ON ORODISPERSIBLE TRIPTAN FORMULATIONS â€“ NOVEL APPROACH IN TREATMENT OF MIGRAINE

Â Objective: The present research work is an attempt to determine the effect of various diluents and superdisintegrants on drug release of eletriptan orodispersible tablets and designs an optimized formulation using 22 factorial design. Further, evaluate the tablets for various pre-compression and post-compression parameters.Methods: The drug excipient compatibility study was conducted by infrared spectroscopy, differential scanning colorimetry and X-ray diffraction studies were conducted to test the purity of the drug. The tablets were formulated by direct compression method using spray dried lactose, mannitol, microcrystalline cellulose, starch as diluents and crospovidone, croscarmellose sodium, and sodium starch glycolate as superdisintegrants. The powder formulations were evaluated for pre-compression parameters such as bulk density, tapped density, Carrâ€™s Index, Hausnerâ€™s ratio, and angle of repose. The tablets were evaluated for post-compression parameters such as the hardness, thickness, friability, weight variation, and disintegrating time in the oral cavity, in vitro drug release kinetics studies, and accelerated stability studies. The formulations were optimized by 22 factorial design.Results: The drug and excipients were compatible, and no interaction was found. The drug was pure, and all the pre-compression parameters were within Indian Pharmacopoeial Limits. Post-compression parameters were also within limits. The disintegration time was found to be 27 s for the formulation F29 containing Croscarmellose sodium (5%) and Mannitol as diluent, and in vitro drug release was found to be 99.67% in 30 min and follows first-order kinetics. This was also the optimized formulation by 22 factorial design with a p=0.013. Conclusion: The orodispersible tablets of eletriptan were successfully formulated, and the optimized formulation was determined that can be used in the treatment of migraine.
Fuzzy control of multivariable nonlinear servomechanisms with explicit decoupling scheme

This paper deals with the problem of controlling multivariable nonlinear servomechanisms by means of fuzzy approaches. A specific system under consideration is a passive nonlinear line-of-sight (LOS) stabilization system with strong interactions between two channels. By using the concept of decentralized control, a control structure is developed that is composed of two control loops, each of which is associated with a single-variable fuzzy controller and a decoupling unit. A simplified fuzzy control algorithm is used to implement the fuzzy controller. We propose two novel approaches to designing the decoupling units. The first one is based on the theory of fuzzy reasoning whereas the second scheme relies on the principle of adaptation. Extensive simulation studies on the LOS system have demonstrated the feasibility and effectiveness of the proposed approach.