Miracle-dz/UniFAR-FTUs huggingface dataset:
Twists and Turns: A Chiropractic Roller Coaster Experience Unraveling the Intricacies of Bilateral Vertebral Artery Dissection

The primary insult in vertebral artery dissections (VADs) involves a tear in the vertebral artery intima, resulting in potential thrombus formation and an elevated risk of cerebrovascular events, such as stroke. Despite its relatively low overall incidence rate, VADs contribute to a significant proportion of ischemic strokes within the younger population. VAD has been associated with various risk factors including but not limited to neck trauma from chiropractic manipulation and significant neck movements. Our patient initially presented with a worsening occipital headache but was discharged due to the absence of any red-flag symptoms. However, the patient shortly returned to the ED upon worsening symptoms, and despite the lack of apparent neurological deficits, the patient's history of cervical spine manipulation and exposure to neck trauma risk activities (roller coaster riding) increased suspicion for VAD. This case highlights the importance of considering VAD as a differential diagnosis in young patients presenting with unexplained headaches and neck pain following events that exert stress on the vertebral arteries, such as roller coaster rides and chiropractic neck manipulation. When managed properly, the long-term prognosis of VAD is generally favorable; however, the risk of recurrent dissection and stroke still remains. Thus, this case further emphasizes the need for timely intervention and the role of dual anti-platelet therapy (DAPT) in the management of VAD to prevent further complications such as stroke.
Enabling Versatility and Dexterity of the Dual-Arm Manipulators: A General Framework Toward Universal Cooperative Manipulation

Grasping and manipulating various kinds of objects cooperatively is the core skill of a dual-arm robot when deployed as an autonomous agent in a human-centered environment. This requires fully exploiting the robot's versatility and dexterity. In this work, we propose a general framework for dual-arm manipulators that contains two correlative modules. The learning-based dexterity-reachability-aware perception module deals with vision-based bimanual grasping. It employs an end-to-end evaluation network and probabilistic modeling of the robot's reachability to deliver feasible and dexterity-optimum grasp pairs for unseen objects. The optimization-based versatility-oriented control module addresses the online cooperative manipulation control by using a hierarchical quadratic programming formulation. Self-collision avoidance and dual-arm manipulability ellipsoid tracking with high reliability and fidelity are simultaneously achieved based on a learned lightweight distance proxy function and a speed-level tracking technique on Riemannian manifold. Intrinsic system safety is guaranteed, and a novel interface for skill transfer is enabled. A long-horizon rearrangement experiment, a bimanual turnover manipulation, and multiple comparative performance evaluation verify the effectiveness of the proposed framework.
The Relationship Between Plasma Gelsolin Levels and Myeloperoxidase in Patients Undergoing Hemodialysis: A Prospective, Observational, Controlled Study

Objective: Given the association of inflammatory conditions with the development of comorbidities, particularly cardiovascular diseases, it is crucial to monitor inflammation in hemodialysis patients. This study aimed to evaluate plasma gelsolin and myeloperoxidase (MPO) levels before and after dialysis sessions and to assess their relationship with inflammation. Materials and Methods: The study included 16 healthy volunteers and 30 patients receiving regular hemodialysis treatment. Along with routine biochemical analyses, plasma gelsolin and MPO levels were measured in blood samples taken from the study group before and after the sessions. Results: Plasma gelsolin levels were found to be statistically higher both before and after dialysis compared to the control group (p=0.000); however, there was no significant change during the session (p=0.094). Conversely, plasma MPO activity, which was significantly higher before dialysis, increased at the end of the session (p=0.000). Conclusion: It can be concluded that elevated levels of gelsolin are associated with a chronic inflammatory response, as indicated by high-sensitivity C-reactive protein (hs-CRP) and MPO levels. Consequently, gelsolin could be considered a supportive treatment strategy for these patients.
Short-term needs trump conservation in household livelihood decision-making around Saadani National Park, Tanzania

Abstract This research explores the influence of attitudes towards conservation affecting livelihood decision-making of households in rural Tanzania through a case study of three villages adjacent to Saadani National Park. Key informant interviews, focus group discussions and semi-structured interviews revealed that attitudes towards conservation were not a direct influence on livelihood decisions. Instead, people felt powerless over forces that have reduced resource productivity and undermined their ability to maintain the level of benefits from their livelihood activities. Changing environmental conditions, harmful harvesting practices, restricted access to land and impacts of other resource users were reported as the major reasons for the natural resource-based livelihood challenges that residents face. Household respondents reported the need to adapt livelihood practices to boost or restore that productivity and compensate for diminished resource access. Short-term need drives decision-making where people are vulnerable to change, not long-term considerations of resource integrity. The main barriers that impede the influence of positive conservation attitudes are low resource productivity, small-scale economies and entrenched cultural traditions.
Metabolomic Analysis Reveals Association between Decreased Ovarian Reserve and In Vitro Fertilization Outcomes

In vitro fertilization (IVF) is a highly effective treatment for infertility; however, it poses challenges for women with decreased ovarian reserve (DOR). Despite the importance of understanding the impact of DOR on IVF outcomes, limited research has explored this relationship, particularly using omics approaches. Hence, we conducted a study to investigate the association between DOR and IVF outcomes, employing a metabolomic approach. We analyzed serum samples from 207 women undergoing IVF treatment, including 89 with DOR and 118 with normal ovarian reserve (NOR). Our findings revealed that DOR was significantly associated with unfavorable IVF outcomes, characterized by a reduced oocyte count, lower embryo quality, and decreased rates of pregnancy and live births. Furthermore, we identified 82 metabolites that displayed significant alterations in DOR patients, impacting diverse metabolic pathways. Notably, a distinct panel of metabolites, including palmitic acid, stearic acid, LysoPC(9:0(CHO)/0:0), PC(18:0/9:0(CHO)), and PC(16:0/9:0(CHO)), exhibited discriminatory power between the DOR and NOR groups, showcasing a strong correlation with IVF outcomes. These findings emphasize the crucial role of metabolomic disruptions in influencing IVF outcomes among women with DOR.
Polynomial-Time Verification of PCTL Properties of MDPs with Convex Uncertainties

We address the problem of verifying Probabilistic Computation Tree Logic (PCTL) properties of Markov Decision Processes (MDPs) whose state transition probabilities are only known to lie within uncertainty sets. We first introduce the model of Convex-MDPs (CMDPs), i.e., MDPs with convex uncertainty sets. CMDPs generalize Interval-MDPs (IMDPs) by allowing also more expressive (convex) descriptions of uncertainty. Using results on strong duality for convex programs, we then present a PCTL verification algorithm for CMDPs, and prove that it runs in time polynomial in the size of a CMDP. This result allows us to lower the previously known algorithmic complexity upper bound for IMDPs from co-NP to PTIME, and it is valid also for more expressive (convex) uncertainty models. We validate the proposed approach on two case studies: the verification of a consensus protocol and of a dynamic configuration protocol for IPv4 addresses. A concise version of the results presented in this thesis can be found in [1]: A. Puggelli, W. Li, A. L. Sangiovanni-Vincentelli, S. A. Seshia, Polynomial-Time Verification of PCTL Properties of MDPs with Convex Uncertainties, Computer Aided Verification, 2013.
Toward content-centric privacy in ICN: attribute-based encryption and routing

We design a content-centric privacy scheme for Information-Centric Networking (ICN). We enhance ICN's ability to support data confidentiality by introducing attribute-based encryption into ICN and making it specific to the data attributes. Our approach is unusual in that it preserves ICN's goal to decouple publishers and subscribers for greater data accessibility, scalable multiparty communication and efficient data distribution. Inspired by application-layer publish-subscribe, we enable fine-grained access control with more expressive policies. Moreover, we propose an attribute-based routing scheme that offers interest confidentiality. A prototype system is implemented based on CCNx, a popular open source version of ICN, to showcase privacy preservation in Smart Neighborhood and Smart City applications.
Growing Cell Structures (GCS) - A Constructive Learning Neural Network for Tool Wear Estimation Application

Tool wear is one of the major factors that affect the automation of machining operations. There is a need to reliably detect the condition of the tool because it affects the product quality, increases machine downtime and sometimes affect the machine tool and the personnel. Tool condition monitoring (TCM) is important in the successful automation of manufacturing processes. In this paper, a new constructive learning algorithm proposed by Fritzke, namely Growing Cell Structures (GCS) is being used for tool wear estimation in face milling operation, thereby monitoring the condition of the tool. GCS generates compact network architecture in less training time and performs well on new untrained data, establishing its feasibility in tool wear estimation applications. The performance of this network has been compared with that of another constructive learning algorithm based neural network namely the Resource Allocation Network (RAN). GCS has been found to be effective and efficient for tool wear estimation.
LEGISLASI HUKUM KEWARISAN DI INDONESIA

Inheritance law is one part of the civil law as a wholeand is the smallest part of family law. Inheritancelaw in Indonesia is still very pluralistic covers threeareas of law, namely the customary inheritance law,Islamic law and the civil law of inheritance (BW). The third system of inheritance law applies despitetogether but in reality do not always go hand inhand, and often lead to conflict. For people who areMuslims, Islamic inheritance law is based on IslamicLaw Compilation (KHI) is not a legal provision thatis imperative. Thus Islamic law for Muslims inIndonesia are voluntary (choice of law). How toshape legislation inheritance law in Indonesia, be atopic of studies in this paper.
Prediction of Recurrence in Patients with Cervical Cancer Using MARS and Classification

This study applied advanced data mining techniques for recurrent cervical cancer in survival analysis. The medical records and pathology were accessible by the Chung Shan Medical University Hospital Tumor Registry. Following a literature review, expert consultation, and collection of patients’ data, twelve variables studied included age, cell type, tumor grade, tumor size, pT, pStage, surgical margin involvement, LNM, Number of Fractions of Other RT, RT target Summary, Sequence of Locoregional Therapy and Systemic Therapy, LVSI. Two data mining approaches were considered where individuals are expected to experience repeated events, along with concomitant variables. After correcting for the four most important prognostic factors: pStage, Pathologic T, cell type and RT target Summary. Finally, clinical trials should randomize patients stratified by these prognostic factors, and precise assessment of recurrent status could improve outcome.
Rapid Prototyping of Distributed Real-Time Embedded Systems Using the AADL and Ocarina

Building Distributed Real-Time Embedded systems requires a stringent methodology, from early requirements capture to full implementation. However, there is a strong link between the requirements and the final implementation (e.g. scheduling, resource dimensioning). Therefore, a rapid prototyping process based on automation of tedious and error-prone tasks (analysis, code generation) is required to speed up the development cycle. In this article, we show how the AADL (Architecture, Analysis and Description Language), appeared late 2005, helps solving these issues thanks to a dedicated tool-suite. We then detail the prototyping process and its current implementation: Ocarina.
JSBML: a flexible Java library for working with SBML

Summary: The specifications of the Systems Biology Markup Language (SBML) define standards for storing and exchanging computer models of biological processes in text files. In order to perform model simulations, graphical visualizations and other software manipulations, an in-memory representation of SBML is required. We developed JSBML for this purpose. In contrast to prior implementations of SBML APIs, JSBML has been designed from the ground up for the Java™ programming language, and can therefore be used on all platforms supported by a Java Runtime Environment. This offers important benefits for Java users, including the ability to distribute software as Java Web Start applications. JSBML supports all SBML Levels and Versions through Level 3 Version 1, and we have strived to maintain the highest possible degree of compatibility with the popular library libSBML. JSBML also supports modules that can facilitate the development of plugins for end user applications, as well as ease migration from a libSBML-based backend. Availability: Source code, binaries and documentation for JSBML can be freely obtained under the terms of the LGPL 2.1 from the website http://sbml.org/Software/JSBML. Contact: jsbml-team@sbml.org Supplementary information: Supplementary data are available at Bioinformatics online.
Encyclopedia of Data Warehousing and Mining Second Edition

Product or company names used in this set are for identification purposes only. Inclusion of the names of the products or companies does not indicate a claim of ownership by IGI Global of the trademark or registered trademark. Encyclopedia of data warehousing and mining / John Wang, editor. -2nd ed. p. cm. Includes bibliographical references and index. Summary: "This set offers thorough examination of the issues of importance in the rapidly changing field of data warehousing and mining"-Provided by publisher. All work contributed to this encyclopedia set is new, previously-unpublished material. The views expressed in this encyclopedia set are those of the authors, but not necessarily of the publisher. If a library purchased a print copy of this publication, please go to http://www.igi-global.com/agreement for information on activating the library's complimentary electronic access to this publication. INTRODUCTION The amounts of data become increasingly large in recent years as the capacity of digital data storage worldwide has significantly increased. As the size of data grows, the demand for data reduction increases for effective data mining. Instance selection is one of the effective means to data reduction. This article introduces basic concepts of instance selection, its context, necessity and functionality. It briefly reviews the state-of-the-art methods for instance selection. Selection is a necessity in the world surrounding us. It stems from the sheer fact of limited resources. No exception for data mining. Many factors give rise to data selection: data is not purely collected for data mining or for one particular application; there are missing data, redundant data, and errors during collection and storage; and data can be too overwhelming to handle. Instance selection is one effective approach to data selection. It is a process of choosing a subset of data to achieve the original purpose of a data mining application. The ideal outcome of instance selection is a model independent, minimum sample of data that can accomplish tasks with little or no performance deterioration.
PeanutDB: an integrated bioinformatics web portal for

Background The peanut ( Arachis hypogaea ) is an important crop cultivated worldwide for oil production and food sources. Its complex genetic architecture ( e.g. , the large and tetraploid genome possibly due to unique cross of wild diploid relatives and subsequent chromosome duplication: 2n = 4x = 40, AABB, 2800 Mb) presents a major challenge for its genome
Sequential Multi-Frame Neural Beamforming for Speech Separation and Enhancement

This work introduces sequential neural beamforming, which alternates between neural network based spectral separation and beamforming based spatial separation. Our neural networks for separation use an advanced convolutional architecture trained with a novel stabilized signal-to-noise ratio loss function. For beamforming, we explore multiple ways of computing time-varying covariance matrices, including factorizing the spatial covariance into a time-varying amplitude component and a time-invariant spatial component, as well as using block-based techniques. In addition, we introduce a multi-frame beamforming method which improves the results significantly by adding contextual frames to the beamforming formulations. We extensively evaluate and analyze the effects of window size, block size, and multi-frame context size for these methods. Our best method utilizes a sequence of three neural separation and multi-frame time-invariant spatial beamforming stages, and demonstrates an average improvement of 2.75 dB in scale-invariant signal-to-noise ratio and 14.2% absolute reduction in differential word error rate over strong baselines, across four challenging reverberant speech enhancement and separation tasks.
Drought Stress Induced Different Response Mechanisms in Three Dendrobium Species under Different Photosynthetic Pathways

Many Dendrobium species, which hold a high status and value in traditional Chinese medicine, grow on barks and rocks in the wild, often encountering harsh environments and facing droughts. However, the molecular mechanisms underlying the shift in the photosynthetic pathway induced by drought remain unclear. To address this issue, three Dendrobium species with different photosynthetic pathways were selected for sequencing and transcriptome data analysis after drought treatment. The findings included 134.43 GB of sequencing data, with numerous Differentially Expressed Genes (DEGs) exhibiting different response mechanisms under drought stress. Gene Ontology (GO)–KEGG-based enrichment analysis of DEGs revealed that metabolic pathways contributed to drought tolerance and alterations in photosynthetic pathways. Phosphoenolpyruvate Carboxylase (PEPC) was subjected to phylogenetic tree construction, sequence alignment, and domain analysis. Under drought stress, variations were observed in the PEPC gene structure and expression among different Dendrobium species; the upregulation of Dc_gene2609 expression may be caused by dof-miR-384, which resulted in the shift from C3 photosynthesis to CAM, thereby improving drought tolerance in Dendrobium. This study revealed the expression patterns and roles of PEPC genes in enhancing plant drought tolerance and will provide an important basis for in-depth research on Dendrobium’s adaptation mechanisms in arid environments.
Concomitant Syndromic Diagnosis of Mpox and Other Vesicular Viruses in Patients with Skin and Genital Lesions

The recent multi-country outbreak of the zoonotic monkeypox virus (MPXV) infection in humans without an epidemiological link with endemic areas has raised concerns about the route of transmission. Since the infection spread largely among men who have sex with men who, in most cases, presented primary lesions of the genital and oral mucosa, sexual transmission has been proposed. In the present study, we retrospectively evaluated specimens of vesicular lesions collected from the skin and genital tract of 35 patients (23 positive and 12 negative) presenting at our Institute for monkeypox (mpox) diagnosis by using a novel molecular syndromic vesicular virus panel (VVP) assay. All MPXV-positive samples but one was confirmed; however, the viral syndromic analysis revealed that 8.6% of them were coinfected with one or more viruses, and 17% had at least a virus different from the MPXV. The percentage of coinfections increased to more than 25% when nonviral pathogens, such as gonorrhea and syphilis, were also considered. These results show the usefulness of syndromic diagnosis in cases where MPXV is suspected (and vice versa) and at the same time highlight that the broader screening of sexually transmitted infections in the population with high-risk sexual behavior is critical to ensure a complete etiology and appropriate treatment.
Reversing Shoreline Armoring: Quantifying the Effectiveness of Restoration on Coastal Biota of Puget Sound

Reversing Shoreline Armoring: Quantifying the Effectiveness of Restoration on Coastal Biota of Puget Sound Timothy Seung-Chul Lee Chair of the Supervisory Committee: Assistant Professor, Ryan P. Kelly School of Marine & Environmental Affairs Shoreline armoring is prevalent around the world with unprecedented human population growth and urbanization along coastal habitats. While armoring structures, such as riprap and bulkheads, are built to prevent beach erosion and protect coastal infrastructure from storms and flooding, such structures can deteriorate habitats for migratory fish species, disrupt aquatic-terrestrial connectivity, and reduce overall coastal ecosystem health. One question is whether armoring is reversible, allowing restoration via armoring removal and related actions of sediment nourishment and replanting of native riparian vegetation. Relative to armored shorelines, natural shorelines retain valuable habitats for macroinvertebrates and other coastal biota. Remarkably, few assessments of the responses of coastal biota to shoreline-armoring removal exist. Here, I use preand post-restoration data for five biotic measures (wrack % cover, saltmarsh % cover, number of logs, macroinvertebrate counts and richness) from a set of restored shorelines in Puget Sound, WA, USA. I find that a broad suite of ecosystem metrics responds strongly and positively, and that these results are evident after less than a year. Restoration responses remain positive and statistically significant across different shoreline elevations and temporal trajectories. This meta-analysis suggests that removing shoreline armoring is an effective technique for restoration projects aimed at improving the health and productivity of coastal ecosystems, and these results may be applicable regionally and globally.