Miracle-dz/UniFAR-FTUs huggingface dataset:
Targeted In Situ Biosynthetic Transcriptional Activation in Native Surface-Level Human Articular Chondrocytes during Lesion Stabilization

Objective: Safe articular cartilage lesion stabilization is an important early surgical intervention advance toward mitigating articular cartilage disease burden. While short-term chondrocyte viability and chondrosupportive matrix modification have been demonstrated within tissue contiguous to targeted removal of damaged articular cartilage, longer term tissue responses require evaluation to further clarify treatment efficacy. The purpose of this study was to examine surface chondrocyte responses within contiguous tissue after lesion stabilization. Methods: Nonablation radiofrequency lesion stabilization of human cartilage explants obtained during knee replacement was performed for surface fibrillation. Time-dependent chondrocyte viability, nuclear morphology and cell distribution, and temporal response kinetics of matrix and chaperone gene transcription indicative of differentiated chondrocyte function were evaluated in samples at intervals to 96 hours after treatment. Results: Subadjacent surface articular cartilage chondrocytes demonstrated continued viability for 96 hours after treatment, a lack of increased nuclear fragmentation or condensation, persistent nucleic acid production during incubation reflecting cellular assembly behavior, and transcriptional up-regulation of matrix and chaperone genes indicative of retained biosynthetic differentiated cell function. Conclusions: The results of this study provide further evidence of treatment efficacy and suggest the possibility to manipulate or induce cellular function, thereby recruiting local chondrocytes to aid lesion recovery. Early surgical intervention may be viewed as a tissue rescue, allowing articular cartilage to continue displaying biological responses appropriate to its function rather than converting to a tissue ultimately governed by the degenerative material property responses of matrix failure. Early intervention may positively impact the late changes and reduce disease burden of damaged articular cartilage.
Privacy Games Along Location Traces

The mainstream approach to protecting the privacy of mobile users in location-based services (LBSs) is to alter (e.g., perturb, hide, and so on) the users’ actual locations in order to reduce exposed sensitive information. In order to be effective, a location-privacy preserving mechanism must consider both the privacy and utility requirements of each user, as well as the user’s overall exposed locations (which contribute to the adversary’s background knowledge). In this article, we propose a methodology that enables the design of optimal user-centric location obfuscation mechanisms respecting each individual user’s service quality requirements, while maximizing the expected error that the optimal adversary incurs in reconstructing the user’s actual trace. A key advantage of a user-centric mechanism is that it does not depend on third-party proxies or anonymizers; thus, it can be directly integrated in the mobile devices that users employ to access LBSs. Our methodology is based on the mutual optimization of user/adversary objectives (maximizing location privacy versus minimizing localization error) formalized as a Stackelberg Bayesian game. This formalization makes our solution robust against any location inference attack, that is, the adversary cannot decrease the user’s privacy by designing a better inference algorithm as long as the obfuscation mechanism is designed according to our privacy games. We develop two linear programs that solve the location privacy game and output the optimal obfuscation strategy and its corresponding optimal inference attack. These linear programs are used to design location privacy--preserving mechanisms that consider the correlation between past, current, and future locations of the user, thus can be tuned to protect different privacy objectives along the user’s location trace. We illustrate the efficacy of the optimal location privacy--preserving mechanisms obtained with our approach against real location traces, showing their performance in protecting users’ different location privacy objectives.
Ubiquitous Healthcare: A New Frontier in E-Health

The Center for Medicare and Medicaid Service projects that by the year 2011 the total healthcare expenditure would reach $2.8 trillion and would amount to 17% of the GDP. Several surveys in the past equivocally agree that the population of the world is aging and this is resulting in increased healthcare utilization/expenses. The current research evaluates ubiquitous healthcare as a strategy that can be deployed as a means of pushing prevention and disease management in the hands of the patients where intervention from the healthcare sector is provided as and when needed. Wireless communication technologies, biomedical sensors/monitoring technologies and ad-hoc networking are some of the primary technologies that form the foundation to promoting ubiquitous healthcare. The current research develops architecture of ubiquitous healthcare depicting enabling technologies and interaction of the patients in a ubiquitous healthcare environment. The technologies that enable various facets of ubiquitous healthcare are evaluated in terms of technical as well as non-technical issues and a classification framework is produced. The current applications of ubiquitous healthcare are evaluated and challenges opportunities and future research areas associated with realizing the vision of ubiquitous healthcare are discussed.
High-efficiency voltage regulation stage in energy harvesting systems

A high-efficiency voltage regulation stage in an energy harvesting system is presented. In an energy harvesting system, the availability of energy is uncertain. If energy is harvested from energy resources, the system operates; if not, the system does not work. Therefore, the energy harvesting system starts and stops repeatedly according to the presence or absence of energy. The repeated on and off state in the energy harvesting system decreases operating efficiency which is an important factor in such a system with the limited amount of harvested energy. To improve the efficiency of the system that repeatedly switch between on and off states, the energy dissipated in the transitional state should be minimized. In this work, a voltage regulation stage is implemented with two additional switches, two low power comparators and digital control logic in addition to the conventional regulation stage. The first switch determines the input voltage level of the regulation stage, and the second switch prevents undesired energy dissipation in the boosting state. When the regulation stage supplies power to a 100 ohm load resistor with a 100 uF load capacitor for 50 ms, the efficiency is improved up to 38%, and boosting time is reduced by 42% in comparison with the conventional regulation structure.
Assessing the climatic and environmental impacts of mid‐tropospheric anticyclones over Alaska

Ongoing climatic and cryospheric changes observed throughout the greater Alaska region are interconnected and often linked to oceanic and atmospheric patterns and processes that operate on varying spatiotemporal scales. To evaluate the long‐term, mid‐tropospheric circulation field across Alaska, and possible connections to climate and environmental change in the Pacific sector of the Arctic, the Alaska Blocking Index (ABI) is developed over the domain (54°–76°N, 125°–180°W) using daily gridded 500 hPa geopotential height fields derived from the ERA‐40 (1958–1978) and ERA‐Interim (1979–2014) data sets, 1958–2014. Climatological characteristics of the seasonal and annual ABI conditions are evaluated and periods of prevalent blocking conditions are identified and subsequently linked to possible local and large‐scale forcing mechanisms. The ABI has exhibited positive trends during all seasons and annually since 1979. Many of the extreme high ABI values occurred since 2000, including the highest annual values in 2013 and 2014. Anomalous blocking patterns in all seasons are associated with diminished snow depth and sea‐ice cover, positive near‐surface air temperature anomalies, and anticyclonic flows of heat and moisture across the domain. The ABI is also shown to differ from the long‐term variability and atmospheric circulation responses associated with phases of the Pacific–North American pattern and Pacific Decadal Oscillation, revealing some notable spatial and temporal disconnects between the region‐centric, high‐latitude blocking flow and some of the predominant modes of sea surface temperature and middle tropospheric circulation variability in the Northern Hemisphere.
Teaching Financial Data Mining using Stocks and Futures Contracts

Financial data mining models is considered to be “the hardest way to make easy money. ” Data miners are certainly motivated by the prospect of discovering a financial “Holy Grail. ” However, designing and implementing a successful model poses many intellectual challenges. These include securing and cleaning data; acquiring a sufficient amount of financial domain knowledge; bounding the complexity of the problem; and properly validating results. Teaching financial data mining is especially difficult due to the student’s limited financial domain knowledge and the relatively short period (one semester) for building financial models. This paper describes an application of a financial data mining term project based on Stock and E-Mini futures contracts and discusses “lessons learned” from assigning similar term projects over six different semesters. Results of each case study results are presented and discussed.
The influence of 2 condensation techniques on the marginal seal of packable resin composite restorations.

OBJECTIVE To evaluate the effect of manual condensation versus a combination of manual and mechanical, or automatic, condensation on the gingival marginal seal of packable resin composite restorations. METHOD AND MATERIALS Two packable composites, Pyramid Dentin (Bisco Dental) and Filtek P-60 (3M Espe), were tested. The study consisted of 37 extracted caries-free human molars and premolars. In each tooth, 2 standardized Class 2 cavities were prepared and restored using the incremental technique; the mesial restoration was condensed by hand instrument, and the distal by a combination of the manual and mechanical condenser (KaVo). Restored teeth were subjected to automatic thermal stresses and cycling load stresses. Teeth were immersed in 0.5% basic fuchsin at 37 degrees C for 96 hours. Samples were sectioned mesiodistally in 3 sections. Dye penetration at the gingival margin was examined. RESULTS Automatic condensation of Filtek P-60 and Pyramid demonstrated better sealing properties, with a median dye penetration of 0 and 1, respectively (on a dye penetration scale of 0 to 3), compared to manual condensation, median of 2 (P = .043) and 3 (P = .079), respectively. Better sealing ability was shown with P-60 than with Pyramid Dentin when manual condensation was used (P = .037). No significant difference was observed between the 2 products when tested with automatic condensation (P = .066). CONCLUSION In this in vitro study the combination of manual and automatic condensation resulted in reduced gingival margin microleakage for both packable composites.
Computational models of classical conditioning: a comparative study

We describe computer simulation of a number of associative models of classical conditioning in an attempt to assess the strengths and weaknesses of each model. The behavior of the Sutton-Barto model, the TD model, the Klopf model, the Balkenius model and the Schmajuk-DiCarlo model are investigated in a number of simple learning situations. All models are shown to have problems explaining some of the available data from animal experiments. The ISI curves for trace and delay conditioning for all the models are presented together with simulations of acquisition and extinction, reacquisition, blocking, conditioned inhibition, secondary conditioning and facilitation by an intermittent stimulus. We also present cases where some of the models show an unexpected behavior.
Static stages for heterogeneous programming

Heterogeneous hardware is central to modern advances in performance and efficiency. Mainstream programming models for heterogeneous architectures, however, sacrifice safety and expressiveness in favor of low-level control over performance details. The interfaces between hardware units consist of verbose, unsafe APIs; hardware-specific languages make it difficult to move code between units; and brittle preprocessor macros complicate the task of specializing general code for efficient accelerated execution. We propose a unified low-level programming model for heterogeneous systems that offers control over performance, safe communication constructs, cross-device code portability, and hygienic metaprogramming for specialization. The language extends constructs from multi-stage programming to separate code for different hardware units, to communicate between them, and to express compile-time code optimization. We introduce static staging, a different take on multi-stage programming that lets the compiler generate all code and communication constructs ahead of time. To demonstrate our approach, we use static staging to implement BraidGL, a real-time graphics programming language for CPU-GPU systems. Current real-time graphics software in OpenGL uses stringly-typed APIs for communication and unsafe preprocessing to generate specialized GPU code variants. In BraidGL, programmers instead write hybrid CPU-GPU software in a unified language. The compiler statically generates target-specific code and guarantees safe communication between the CPU and the graphics pipeline stages. Example scenes demonstrate the language's productivity advantages: BraidGL eliminates the safety and expressiveness pitfalls of OpenGL and makes common specialization techniques easy to apply. The case study demonstrates how static staging can express core placement and specialization in general heterogeneous programming.
Exploring the interactions between metabolic dysfunction-associated fatty liver disease and micronutrients: from molecular mechanisms to clinical applications

Metabolic (dysfunction)-associated fatty liver disease (MAFLD) has emerged as a significant global health concern, representing a major cause of liver disease worldwide. This condition spans a spectrum of histopathologic stages, beginning with simple fatty liver (MAFL), characterized by over 5% fat accumulation, and advancing to metabolic (dysfunction)-associated steatohepatitis, potentially leading to hepatocellular carcinoma. Despite extensive research, there remains a substantial gap in effective therapeutic interventions. This condition’s progression is closely tied to micronutrient levels, crucial for biological functions like antioxidant activities and immune efficiency. The levels of these micronutrients exhibit considerable variability among individuals with MAFLD. Moreover, the extent of deficiency in these nutrients can vary significantly throughout the different stages of MAFLD, with disease progression potentially exacerbating these deficiencies. This review focuses on the role of micronutrients, particularly vitamins A, D, E, and minerals like iron, copper, selenium, and zinc, in MAFLD’s pathophysiology. It highlights how alterations in the homeostasis of these micronutrients are intricately linked to the pathophysiological processes of MAFLD. Concurrently, this review endeavors to harness the existing evidence to propose novel therapeutic strategies targeting these vitamins and minerals in MAFLD management and offers new insights into disease mechanisms and treatment opportunities in MAFLD.
Regularization Effects in Deep Learning Architecture

This research examines the impact of three widely utilized regularization approaches -- data augmentation, weight decay, and dropout --on mitigating overfitting, as well as various amalgamations of these methods. Employing a Convolutional Neural Network (CNN), the study assesses the performance of these strategies using two distinct datasets: a flower dataset and the CIFAR-10 dataset. The findings reveal that dropout outperforms weight decay and augmentation on both datasets. Additionally, a hybrid of dropout and augmentation surpasses other method combinations in effectiveness. Significantly, integrating weight decay with dropout and augmentation yields the best performance among all tested method blends. Analyses were conducted in relation to dataset size and convergence time (measured in epochs). Dropout consistently showed superior performance across all dataset sizes, while the combination of dropout and augmentation was the most effective across all sizes, and the triad of weight decay, dropout, and augmentation excelled over other combinations. The epoch-based analysis indicated that the effectiveness of certain techniques scaled with dataset size, with varying results.
Dispersal‐Vicariance Analyses of Intercontinental Disjuncts: Historical Biogeographical Implications for Angiosperms in the Northern Hemisphere

Ten North Temperate taxa representing diverse angiosperm lineages were analyzed for biogeographic histories using the dispersal‐vicariance analysis method to gain insights into the origin and evolution of disjunct distributions in the Northern Hemisphere. Results indicate four general biogeographic patterns: (1) origin and speciation in eastern Asia with subsequent expansion into North America and/or Europe (e.g., Aralia sect. Aralia, Symplocarpus, and possibly Asarum, Aesculus, and Chrysosplenium); (2) origin in eastern Asia and western North America with subsequent spread into eastern North America (e.g., Calycanthus and Boykinia); (3) a disjunct origin in eastern Asia and eastern North America with subsequent dispersal from eastern Asia into eastern North America (e.g., Panax); and (4) a widespread origin in the Northern Hemisphere with subsequent fragmentation by intercontinental vicariance (e.g., Cornus and Trautvetteria). Although there are caveats, the results indicate that the disjunct distributions of angiosperm lineages in the Northern Hemisphere cannot be explained with a simple vicariance model. Most lineages may have been restricted ancestrally to one or two adjacent areas and then secondarily expanded their ranges via dispersal. A noteworthy finding was the one‐way intercontinental plant exchange from the Old World to the New World and biased dispersal within each continent. There was more dispersal from the west to the east in North America but more dispersal from the east to the west in Eurasia. Such asymmetrical dispersal has also been documented in animals. The results also indicate that eastern Asia and western North America were the centers of origin for a majority of lineages examined, implying that these two areas were important sources of temperate angiosperm evolution in the Northern Hemisphere. The results further support a complex evolutionary history of angiosperms in the Northern Hemisphere and suggest pseudocongruence among lineages in phylogenetic relationships and distributional patterns.
A predictive contour inertia snake model for general video tracking

We present a modified snake model for the problem of general video object tracking. We introduce a new external force into the snake equation based on the predictive contour such that the active contour is attracted to a shape similar to the one in the previous video frame. New methods of contour prediction and contour smoothing are presented. The proposed methods can deal with the problem of an object's stopping movement temporarily and can also avoid the problem of the snake tracking into the object interior. Global affine motion estimation is applied to eliminate the effect of camera motion and hence the method can be applied in a general video environment. Experimental results show that the proposed method exhibits increased robustness over a traditional snake algorithm and works well for general video object tracking.
Yield Estimate (230 kt) for a Mueller‐Murphy Model of the 3 September 2017, North Korean Nuclear Test (mbNEIC = 6.3) From Teleseismic Broadband P Waves Assuming Extensive Near‐Source Damage

The 3 September 2017 underground nuclear test (mbNEIC = 6.3) is the largest of six announced North Korean explosions. The event generated many P wave seismograms at global broadband seismic stations with good signal‐to‐noise ratio for periods less than ~5 s. Instrument deconvolution provides 435 stable broadband P wave ground displacement records in the period range 0.1 to 5.0 s. These are stacked in 26 azimuth/distance windows to average path and receiver effects. Waveform stacks and average amplitude of 4‐Hz ground displacements are modeled assuming a Mueller‐Murphy explosion source model for a granite source medium. Nonelastic pP delays consistent with burial depths in the mountainous source topography are considered, and explosion yield and an average constant‐Q attenuation operator are estimated by fitting the waveforms. For a source depth of 750 m in heavily damaged environment, the estimated yield = 230 ± 50 kt and t* = 0.78 ± 0.03 s.
``Namanya juga Pesantren'': A Photovoice Study about Self-adjustment of Students in Islamic Boarding School

Pondok Pesantren (PP) or Islamic boarding school is a popular religious educational institution in Indonesia. The characteristic of PP required students to live in a boarding school, this encouraged students to be able to adapt to the differences and limitations of PP. This study aims to find out how students adapt to PP. The participants are four female students in grade 2 of a PP junior high school in the city of Ternate, North Maluku. The method used in this study is photovoice and analyzed using thematic analysis with Nvivo 12 Pro software. Four themes of adjustment emerged from the findings are as follows: new habits, religious habits, facing and resolving challenges, and relationships. Keywords: adjustment, Islamic boarding school, photovoice
The Evaluation of Similarity Metrics in Collaborative Filtering Recommenders

—Collaborative ﬁltering recommenders predict user opinions regardless of item content. Memory-based implementations generate recommendations on demand, without any pre-computation. Even though such algorithms are slow, they are known for their superior personalization. We study collaborative ﬁltering recommendations on the Netﬂix dataset. It is essentially a set of (user id, item id, rating) tuples that ﬁt perfectly into a relational database model, with standard data manipulation operations. The simple structure of our system allows consistent and repeatable measurements. Additionally, it natively supports multi-threaded processing, which helps address the inherent performance drawbacks of our approach. We evaluate multiple similarity measures in a traditional collaborative ﬁltering process. We also consider combinations of complementary measures, especially in edge cases when one of them falls short, e.g., a user with uniform ratings. We examine prediction accuracy, classiﬁcation accuracy, confusion statistics, and actual/predicted distribution compatibility to ﬁnd the best way to quantify vector similarity.