Miracle-dz/UniFAR-FTUs huggingface dataset:
Multivariate autoregressive models with exogenous inputs for intracerebral responses to direct electrical stimulation of the human brain

A multivariate autoregressive (MVAR) model with exogenous inputs (MVARX) is developed for describing the cortical interactions excited by direct electrical current stimulation of the cortex. Current stimulation is challenging to model because it excites neurons in multiple locations both near and distant to the stimulation site. The approach presented here models these effects using an exogenous input that is passed through a bank of filters, one for each channel. The filtered input and a random input excite a MVAR system describing the interactions between cortical activity at the recording sites. The exogenous input filter coefficients, the autoregressive coefficients, and random input characteristics are estimated from the measured activity due to current stimulation. The effectiveness of the approach is demonstrated using intracranial recordings from three surgical epilepsy patients. We evaluate models for wakefulness and NREM sleep in these patients with two stimulation levels in one patient and two stimulation sites in another resulting in a total of 10 datasets. Excellent agreement between measured and model-predicted evoked responses is obtained across all datasets. Furthermore, one-step prediction is used to show that the model also describes dynamics in pre-stimulus and evoked recordings. We also compare integrated information—a measure of intracortical communication thought to reflect the capacity for consciousness—associated with the network model in wakefulness and sleep. As predicted, higher information integration is found in wakefulness than in sleep for all five cases.
Subgrouping of fibromyalgia patients on the basis of pressure-pain thresholds and psychological factors.

OBJECTIVE Although the American College of Rheumatology (ACR) criteria for fibromyalgia are used to identify individuals with both widespread pain and tenderness, individuals who meet these criteria are not a homogeneous group. Patients differ in their accompanying clinical symptoms, as well as in the relative contributions of biologic, psychological, and cognitive factors to their symptom expression. Therefore, it seems useful to identify subsets of fibromyalgia patients on the basis of which of these factors are present. Previous attempts at identifying subsets have been based solely on psychological and cognitive features. In this study, we attempt to identify patient subsets by incorporating these features as well as the degree of hyperalgesia/tenderness, which is a key neurobiologic feature of this illness. METHODS Ninety-seven individuals meeting the ACR criteria for fibromyalgia finished the same battery of self-report and evoked-pain testing. Analyzed variables were obtained from several domains, consisting of 1) mood (evaluated by the Center for Epidemiologic Studies Depression Scale [for depression] and the State-Trait Personality Inventory [for symptoms of trait-related anxiety]), 2) cognition (by the catastrophizing and control of pain subscales of the Coping Strategies Questionnaire), and 3) hyperalgesia/tenderness (by dolorimetry and random pressure-pain applied at suprathreshold values). Cluster analytic procedures were used to distinguish subgroups of fibromyalgia patients based on these domains. RESULTS Three clusters best fit the data. Multivariate analysis of variance (ANOVA) confirmed that each variable was differentiated by the cluster solution (Wilks' lambda [degrees of freedom 6,89] = 0.123, P < 0.0001), with univariate ANOVAs also indicating significant differences (all P < 0.05). One subgroup of patients (n = 50) was characterized by moderate mood ratings, moderate levels of catastrophizing and perceived control over pain, and low levels of tenderness. A second subgroup (n = 31) displayed significantly elevated values on the mood assessments, the highest values on the catastrophizing subscale, the lowest values for perceived control over pain, and high levels of tenderness. The third group (n = 16) had normal mood ratings, very low levels of catastrophizing, and the highest level of perceived control over pain, but these subjects showed extreme tenderness on evoked-pain testing. CONCLUSION These data help support the clinical impression that there are distinct subgroups of patients with fibromyalgia. There appears to be a group of fibromyalgia patients who exhibit extreme tenderness but lack any associated psychological/cognitive factors, an intermediate group who display moderate tenderness and have normal mood, and a group in whom mood and cognitive factors may be significantly influencing the symptom report.
Fine-tuning BERT for Persian Patent Classification: A Dataset and Model Exploration

Patent documents are esteemed intellectual assets, garnering significant attention in research and development circles. The complex nature of patent classification forms a foundational step for subsequent tasks in patent analysis. Currently, the manual assignment of classification codes, such as IPC and CPC, is a common practice. In the Iran Patent Office, the IPC code is utilized for classification. This paper presents a public dataset for Persian patents and explores the efficacy of the pre-trained Transformer model for International Patent Classification (IPC) code classification. Leveraging ParsBERT, a BERT model trained on the Persian corpus, we address the challenge of automating the assignment of IPC codes to patents. Notably, major patent offices like USPTO and WIPO are increasingly employing artificial intelligence models for this purpose.
Model Choice and Influential Cases for Survival Studies

Summary. Deletion diagnostics are developed for identifying observations that influence the estimates of regression parameters and the mixture parameter in the families of relative risk functions for failure time data. The diagnostic for the regression parameters is a generalization of Cain and Lange's (1984, Biometrics40, 493–499) measure of individual influence. The generalizations of martingale residuals, Schoenfeld's partial residuals (1982, Biometrika69, 239–241), and score residuals by Therneau, Grambsch, and Fleming (1990, Biometrika77, 147–160) are also obtained. The influence of some observations on regression parameters can be drastically modified as the mixture parameter changes, even for a very small change. In addition, adding or deleting some observations might result in choosing different models. The diagnostics are applied to a family proposed by Guerrero and Johnson (1982, Biometrika69, 309–314). One illustrative example is presented.
Regulation of Activating Transcription Factor-1 and the cAMP Response Element-binding Protein by Ca/Calmodulin-dependent Protein Kinases Type I, II, and IV (*)

The ability of activating transcription factor-1 (ATF1) or the cAMP response element-binding protein (CREB) to enhance transcription can be stimulated by increases in intracellular Ca concentrations. To identify protein kinases which may mediate the ability of Ca to activate these transcription factors, we compared the ability of constitutively active forms of several Ca/calmodulin-dependent protein kinases (CaM kinases) to activate ATF1 or CREB. We find that constitutively active CaM kinase I and IV can activate both ATF1 and CREB. In addition, expression vectors for full-length CaM kinase I and IV were able to augment the ability of Ca influx to activate ATF1 or CREB consistent with a role for these kinases in mediating transcriptional responses to Ca signaling. In contrast, CaM kinase II was unable to activate either ATF1 or CREB. These findings provide a potential mechanism that may permit variation in the ability of ATF1 and CREB to respond to changes in intracellular Ca concentrations depending on differences in the relative concentrations of specific CaM kinases.
Exploiting 2.5D/3D Heterogeneous Integration for AI Computing

The evolution of AI algorithms has not only revolutionized many application domains, but also posed tremendous challenges on the hardware platform. Advanced packaging technology today, such as 2.5D and 3D interconnection, provides a promising solution to meet the ever-increasing demands of bandwidth, data movement, and system scale in AI computing. This work presents HISIM, a modeling and benchmarking tool for chiplet-based heterogeneous integration. HISIM emphasizes the hierarchical interconnection that connects various chiplets through network-on-package. It further integrates technology roadmap, power/latency prediction, and thermal analysis together to support electro-thermal co-design. Leveraging HISIM with in-memory computing chiplets, we explore the advantages and limitations of 2.5D and 3D heterogenous integration on representative AI algorithms, such as DNNs, transformers, and graph neural networks.
Combining Hierarchical Clustering and Machine Learning to Predict High-Level Discourse Structure

We propose a novel method to predict the interparagraph discourse structure of text, i.e. to infer which paragraphs are related to each other and form larger segments on a higher level. Our method combines a clustering algorithm with a model of segment "relatedness" acquired in a machine learning step. The model integrates information from a variety of sources, such as word co-occurrence, lexical chains, cue phrases, punctuation, and tense. Our method outperforms an approach that relies on word co-occurrence alone.
Towards Automated Testing of Multiplexers in Fully Programmable Valve Array Biochips

Fully Programmable Valve Array (FPVA) biochips have attracted much attention as a new generation of continuous-flow microfluidic platform for biochemical experiments automation. With the increasing density of microvalves in FPVA biochips, the control system for managing the open/close of these valves has become more and more complex. To improve the scalability of biochips and reduce the number of control pins, a highly efficient control system using multiplexer and boolean logic has been introduced in FPVA biochips. In the manufacturing and using of such systems, however, various faults such as channel blockage, channel leakage, and reliability issues caused by frequent valve switching can occur in the multiplexers. Accordingly, in this paper, we propose the first automated fault test method for the multiplexer of FPVA control systems. The proposed method includes the following key techniques: 1) an automated test pattern generation algorithm based on integer linear programming and 2) an automated fault test strategy based on image recognition technology. Experiment results on multiple benchmarks have shown that the proposed method can generate fewer test patterns, while achiving 100% fault coverage.
Edge and Region Synergy Driven Active Contour Models for Natural Image Segmentation

Image segmentation is one of the fundamental operations of image processing and Active Contour Models (ACM) are one of the most extensively used algorithms for instant segmentation. The main benefit of ACMs is that it does not require training samples to generate reasonably accurate segmentation of image objects of complex structure, location, and size. Recently, ACMs could achieve much better results in terms of accuracy, initialization robustness, and optimization speed through the combination of edge and region-based information in energy functions. Accordingly, this work discusses, analyzes, and compares the performance of two recently reported synergy-driven ACMs in segmenting images, especially natural images. The experimental results show both models could positively augment the efficacy of the originally developed model in all the performance-assessing parameters of image segmentation.
Use of base metal casting alloys for implant framework: marginal accuracy analysis.

The original protocol for implant prosthesis recommends the use of a gold framework for acrylic and ceramic prosthesis. However, due to its high cost, the use of alternative alloys is desired. This study compares the marginal accuracy of pre-made cylinders versus plastic cylinders cast with two different base metal casting alloys. Five samples each of (1) plastic cylinder cast in cobalt-chromium alloy, (2) plastic cylinder cast in nickel-chromium alloy, and (3) silver-palladium pre-made cylinder (control) were examined for marginal accuracy according to: (A) vertical gap; (B) horizontal gap and (C) horizontal gap depth at the abutment/cylinder interface. Data were submitted to statistical analysis (ANOVA and Student-Newman Keuls, p<0.05). Mean values for vertical, horizontal and gap depth were 4. 13µm, 14. 5µm and 6. 93µm for pre-made cylinder, 23. 18µm, 33. 2µm and 88µm for Ni-Cr cast cylinder and 25. 6µm, 51. 8µm and 114. 54µm for Co-Cr cast cylinder. No statistically significant differences were found between cast groups (1 and 2), but significant better fit was obtained with pre-made metal cylinders when compared to cast cylinders with Ni-Cr and Co-Cr alloys, for all analyses.
Simultaneous Detection of Seven Enteric Viruses Associated with Acute Gastroenteritis by a Multiplexed Luminex-Based Assay

ABSTRACT Rapid and broad diagnostic methods are needed for the identification of viral agents of gastroenteritis. In this study, we used Luminex xMAP technology to develop a multiplexed assay for the simultaneous identification of major enteric viral pathogens, including rotavirus A (RVA), noroviruses (NoVs) (including genogroups GI and GII), sapoviruses (SaV), human astrovirus (HAstV), enteric adenoviruses (EAds), and human bocavirus 2 (HBoV2). The analytical sensitivity allowed detection of 103 (EAds, HBoV2, and RVA) and 104 (NoV GI and GII, SaV, and HAstV) copies per reaction mixture. Compared to conventional PCR, the Luminex-based assay yielded greater than 75% sensitivity and 97% specificity for each virus, and the kappa correlation for detection of all viruses ranged from 0.75 to 1.00. In conclusion, this multiplexed Luminex-based assay provides a potentially rapid, high-throughput, and maneuverable diagnostic tool for major viral pathogens associated with gastroenteritis.
Randomized controlled study to evaluate the effectiveness of dexamethasone oral minipulse therapy versus oral minocycline in patients with active vitiligo vulgaris.

BACKGROUND Oral minocycline has been recently shown to halt disease progression in active vitiligo. AIMS The present study was planned to compare the efficacy and tolerability of oral minocycline with oral mini pulse (OMP) corticosteroids in active vitiligo. METHODS A total of 50 patients with actively spreading vitiligo were randomized to receive either minocycline 100 mg/day (Group I-25 patients) or OMP 2.5 mg dexamethasone on 2 consecutive days in a week (Group II-25 patients) for 6 months. These were followed-up at every 2 weeks interval. Mean vitiligo disease activity score (VIDA) and mean Vitiligo Area Scoring Index (VASI) were assessed in all patients in addition to the photographic comparison before and after treatment. RESULTS Both groups showed a significant decrease in VIDA from 4.0 to 1.64±0.86 (P<0.001) in Group I and from 4.0 to 1.68±0.69 (P<0.001) in Group II. However, the difference between the mean VIDA scores in the two groups was not statistically significant (P=0.60) at the end of treatment period. The mean VASI declined from 1.71±1.45 to 1.52±1.43 Group I (P=0.06) and from 1.39±1.31 to 1.17±1.34 in Group II (P=0.05). The difference between VASI in Group I and II was not significant at the end of 24 weeks of treatment (P=0.11). CONCLUSION Both dexamethasone OMP and oral minocycline are effective drugs for managing the arrest of disease activity in vitiligo.
Molecular Epidemiology Reveals Genetic Diversity amongst Isolates of the Cryptococcus neoformans/C. gattii Species Complex in Thailand

To gain a more detailed picture of cryptococcosis in Thailand, a retrospective study of 498 C. neoformans and C. gattii isolates has been conducted. Among these, 386, 83 and 29 strains were from clinical, environmental and veterinary sources, respectively. A total of 485 C. neoformans and 13 C. gattii strains were studied. The majority of the strains (68.9%) were isolated from males (mean age of 37.97 years), 88.5% of C. neoformans and only 37.5% of C. gattii strains were from HIV patients. URA5-RFLP and/or M13 PCR-fingerprinting analysis revealed that the majority of the isolates were C. neoformans molecular type VNI regardless of their sources (94.8%; 94.6% of the clinical, 98.8% of the environmental and 86.2% of the veterinary isolates). In addition, the molecular types VNII (2.4%; 66.7% of the clinical and 33.3% of the veterinary isolates), VNIV (0.2%; 100% environmental isolate), VGI (0.2%; 100% clinical isolate) and VGII (2.4%; 100% clinical isolates) were found less frequently. Multilocus Sequence Type (MLST) analysis using the ISHAM consensus MLST scheme for the C. neoformans/C. gattii species complex identified a total of 20 sequence types (ST) in Thailand combining current and previous data. The Thai isolates are an integrated part of the global cryptococcal population genetic structure, with ST30 for C. gattii and ST82, ST83, ST137, ST141, ST172 and ST173 for C. neoformans being unique to Thailand. Most of the C. gattii isolates were ST7 = VGIIb, which is identical to the less virulent minor Vancouver island outbreak genotype, indicating Thailand as a stepping stone in the global spread of this outbreak strain. The current study revealed a greater genetic diversity and a wider range of major molecular types being present amongst Thai cryptococcal isolates than previously reported.
High-Efficiency Rectenna Design for Batteryless Implantable Medical Devices Powered by RF Energy Harvesting in the ISM Band

The healthcare industry is presently undergoing a paradigm shift from a hospital-centric to an individual-centric model, driven by the integration of wireless power transmission technology. This comprehensive study specifically highlights the critical role played by rectennas in capturing RF energy for wireless power transfer, particularly in implantable medical devices and body area network (BAN) applications. Advancements, challenges, and strategies for optimizing RF conversion efficiency are explored, with particular emphasis placed on the meticulous design and optimization of a rectenna circuit using ADS software. The primary objective is to contribute substantively to the ongoing development of efficient and reliable portable medical devices, specifically those utilized in implants and BAN wireless sensors for WSN applications. These devices are characterized by robustness, reliability, and battery-free functionality. The development of self-powered IoT healthcare devices is prioritized, aligning with the broader goal of enhancing the efficiency and dependability of portable medical technologies.
Expansion of the Receptor-Like Kinase/Pelle Gene Family and Receptor-Like Proteins in Arabidopsis1[w]

Receptor-like kinases (RLKs) are a family of transmembrane proteins with versatile N-terminal extracellular domains and C-terminal intracellular kinases. They control a wide range of physiological responses in plants and belong to one of the largest gene families in the Arabidopsis genome with more than 600 members. Interestingly, this gene family constitutes 60% of all kinases in Arabidopsis and accounts for nearly all transmembrane kinases in Arabidopsis. Analysis of four fungal, six metazoan, and two Plasmodium sp. genomes indicates that the family was represented in all but fungal genomes, indicating an ancient origin for the family with a more recent expansion only in the plant lineages. The RLK/Pelle family can be divided into several subfamilies based on three independent criteria: the phylogeny based on kinase domain sequences, the extracellular domain identities, and intron locations and phases. A large number of receptor-like proteins (RLPs) resembling the extracellular domains of RLKs are also found in the Arabidopsis genome. However, not all RLK subfamilies have corresponding RLPs. Several RLK/Pelle subfamilies have undergone differential expansions. More than 33% of the RLK/Pelle members are found in tandem clusters, substantially higher than the genome average. In addition, 470 of the RLK/Pelle family members are located within the segmentally duplicated regions in the Arabidopsis genome and 268 of them have a close relative in the corresponding regions. Therefore, tandem duplications and segmental/whole-genome duplications represent two of the major mechanisms for the expansion of the RLK/Pelle family in Arabidopsis.
Utilizing a New Approach in a Multiple Linear Regression Model to Predict Insurance Charges

Insurance industries primarily rely on premiums as a source of income. Consequently, developing an accurate algorithm for predicting insurance charges is essential for these industries. The development of artificial intelligence and machine learning techniques has given rise to generating algorithms to predict insurance charges. This research presents a methodology to enhance the performance of the regression model, providing better outcomes than previous examinations. The performance of the regression model is analogous to the Random Forest and XG-boost algorithms. Although the regression method may not have better results in a mean absolute error, it performed better in the median absolute error value. Despite the simplicity of the regression models, they have demonstrated exemplary performance compared to previous studies and other models.
Kirchhoff inversion for incident waves synthesized from common‐shot data gathers

Synthesis is a process for producing reflection responses from more general sources or from prescribed incident waves by combining common-shot data gathers. Synthesis can provide survey-wide data sets, similar in that regard to common-offset data gathers, but with the added advantage that each synthesized data set is a solution to a single wave equation. A common-offset data set does not have this last feature. Thus, synthesized data sets can be processed by true amplitude wave equation migration. The output is then known to be true amplitude, as well, in the same sense as is the output of Kirchhoff inversion. Alternatively, the Kirchhoff inversion of synthesized data has a Beylkin determinant that is expressed in terms of the WKBJ Green’s function amplitude. This is in contrast to 3D common offset inversion where the Beylkin determinant is most difficult to compute. We present here a theory of data synthesis based on application of Green’s theorem to the ensemble of common-shot gathers and prescribed more general sources or prescribed incident waves. Specific examples include delayed-shot line sources and incident dipping plane waves at the upper surface. We also discuss two cases in which waves are prescribed at depth, back-projected to the upper surface and then used to generate a synthesized data set.