Miracle-dz/UniFAR-FTUs huggingface dataset:
Age-related advanced glycation end-product accumulation impairs mitochondrial regulation after vitrification

Abstract Vitrification is an important assisted reproductive technology, although it induces mitochondrial dysfunction in embryos. Herein, we aimed to investigate whether age-associated accumulation of advanced glycation end-products (AGEs) in oocytes impairs the recovery of embryos from cryopreservation-induced mitochondrial dysfunction/damage. Mouse eight-cell stage embryos developed in vitro were vitrified and warmed and incubated up to the blastocyst stage. AGE levels in oocytes were higher in both aged mice and AGE accumulation mouse models (MGO-mice) than those in young and control mice. In addition, the level of SIRT1 upregulation was lower for embryos of aged and MGO-mice than that for embryos of young and control mice. The highest mitochondrial DNA (mtDNA) content was detected in blastocysts derived from vitrified embryos of aged and MGO-mice. The spent culture medium of blastocysts derived from both aged and MGO-mice contained higher mtDNA content than that of the blastocysts derived from young and control mice. EX527 increased mtDNA content in the spent culture medium of vitrified embryos derived from young mice. In addition, p62 aggregate levels were higher in vitrified embryos of control mice than those in vitrified embryos of MGO-mice. The SIRT1 activator, resveratrol, increased p62 aggregation levels in vitrified embryos derived from young and aged mice, whereas vitrification did not affect p62 aggregation levels in embryos from aged mice. Therefore, age-associated AGE accumulation induces decreased responsive SIRT1 upregulation following vitrified–warmed treatment and impairs mitochondrial quality control activity in vitrified embryos. Summary Sentence Accumulation of AGEs inhibits responsive SIRT1 upregulation after vitrification and warming, which negatively affects mitochondrial quality control system in embryos. Graphical Abstract
Stereotactic ablation: A game changer?

For both primary and metastatic liver cancer, thermal ablation represents an interesting alternative to surgery. However, except for a small fraction of patients, conventional ultrasound‐ and CT‐guided single‐probe approaches have not achieved oncologic outcomes comparable with surgery. In this overview, we describe our stereotactic ablation workflow and discuss the short‐ and long‐term results of stereotactic radiofrequency ablation (SRFA) and stereotactic microwave ablation (SMWA) for the treatment of primary and secondary liver tumours. The advantages of this method are discussed together with a summary of the existing stereotactic techniques for thermal ablation and the clinical data that support them. Stereotactic ablation is based on an optical navigation system and a specialized aiming tool. The workflow includes advanced three‐dimensional planning, precise needle/probe placements according to the plan and intraoperative image fusion to check the needle positions and the ablation margins. Stereotactic ablation offers all the advantages of a minimally invasive procedure while producing oncological results comparable with surgery. The number of locally treatable liver cancers may be significantly expanded with these cutting‐edge instruments and methods. We firmly believe that it can become a cornerstone in the treatment of liver cancers.
Review of retracted papers in the field of neurology

Despite the growing awareness of academic fraud, its prevalence in the field of neurology has not been fully assessed. This review aims to analyze the characteristics of the retracted papers in the field of neurology and the reasons for the retraction to better understand the trends in this area and to assist to avoid retraction incidents.
Agmatine prevents the memory impairment and the dysfunction of hippocampal GSK‐3β and ERK signaling induced by Aluminum nanoparticle in mice

The growing usage of Aluminum nanoparticles (Al‐NP) and its exposure may influence body function. Considering the proposed relationship between Al and the pathogenesis of Alzheimer’s disease (AD) and the concern about the effect of this nanoparticle on brain health and cognitive function, the use of neuroprotective agents might be helpful. According to the reported neuroprotective effects of agmatine, in the present study the possible protective effect of agmatine was assessed in mice model of Al‐NP induced memory impairment. was investigated in the present study. In addition, due to the roles of hippocampal Glycogen synthase kinase 3 beta (GSK‐3β) and ERK signaling in memory and its disorders, these pathways were also investigated.
The challenges to control epilepsy in an isolated indigenous tribe in Brazil's Amazon: 15 years of follow-up

Abstract Background Epilepsy is a common neurological disease that affects people all over the world, but it is rarely described in indigenous peoples. Objective To study the epilepsy characteristics and risk factors for seizure control in people from an isolated indigenous population. Methods This is a retrospective and historical cohort study conducted from 2003 to 2018 (15 years), at a neurology outpatient clinic, of 25 Waiwai tribes' indigenous individuals with epilepsy, inhabitants of an isolated forest reserve in the Amazon. Clinical aspects, background, comorbidities, exams, treatment, and response were studied. Factors that impacted seizure control over 24 months were identified using Kaplan-Meier curves and Cox and Weibull regression models. Results The majority of cases started in childhood, with no difference regarding gender. Focal epilepsies were predominant. Most patients had tonic-clonic seizures. A quarter of them had a family history, and 20% had referred febrile seizures. There was intellectual disability in 20% of patients. Neurological examination and psychomotor development were altered in one third of the participants. The treatment controlled 72% of the patients (monotherapy in 64%). Phenobarbital was the most prescribed anti-seizure medication, followed by carbamazepine and valproate. The most relevant factors that impacted seizure control over time were abnormal neurological exam and family history. Conclusion Family history and abnormal neurological exam were predicted risk factors for refractory epilepsy. Even in an isolated indigenous tribe, the partnership between the indigenous people and the multidisciplinary team ensured treatment adherence. The public healthcare system must guarantee modern anti-seizure medications, mainly for this vulnerable population, which has no other source of treatment.
Lifestyle activities in mid-life contribute to cognitive reserve in middle-aged individuals at risk for late-life Alzheimer's disease, independent of education and occupation

It is now acknowledged that Alzheimer's disease (AD) neuropathology starts decades before the onset of clinical symptoms, but it remains unknown whether modifiable lifestyle factors can protect against these incipient AD processes, early, in mid-life. Cognitive reserve can explain cognitive preservation in some older adults despite ageing or dementia symptoms, but it is not known whether it can protect against neurodegeneration in mid-life. We asked whether modifiable lifestyle activities contribute to cognitive reserve in mid-life, and whether it can offset the risk of AD in individuals who are cognitively healthy. Cognition, structural, and functional brain health measures were assessed at baseline and two years follow-up, in a cohort of middle-aged participants (N = 210; 40--59 years). Mid-life activities were measured using the Lifetime of Experiences Questionnaire. We assessed the impact of lifestyle activities and known risk factors for sporadic late-onset AD (i.e., the Cardiovascular Risk Factors Aging and Dementia [CAIDE] score) on measures of cognition and brain health. Multivariable linear regression found that mid-life activities made a unique contribution to cognition, independent of education and occupation. Crucially, mid-life activities moderated the relationship between cognitive ability (verbal and visuospatial functions, and conjunctive short-term memory binding) and brain health. Cognitive ability of people with higher mid-life activities, particularly those with high dementia risk scores, was less dependent on their brain functional architecture. Impaired visuospatial function is one of the earliest cognitive deficits in AD and has previously been associated with increased AD risk in this cohort. Additionally, conjunctive memory functions have been found impaired in the pre-symptomatic stages of AD. These findings suggest that modifiable activities contribute uniquely to cognitive reserve in midlife, and may offset the risk of AD. The modifiability of these activities supports their targeting by public health initiatives aimed at dementia prevention.
Afghan EFL Teachers’ perceptions towards Grammar-Translation Method (GTM)

Abstract The purpose of the present study was to explore the perceptions of Afghan EFL teachers towards the use of Grammar-Translation Method (GTM) in English classrooms. It aimed to investigate the use of different techniques of teaching English to students through the application of GTM in classrooms. Furthermore, the study sought to determine how GTM helped teachers to use translation technique to translate short passages and other language items and effects of GTM on Afghan teaching classrooms through students’ performance. The study also tried to find out differences in the perceptions teachers by gender, age, first language, and teaching experience. The data collected from 150 participants who were teaching English at Takhar University and other English language centers. The study employed Statistical Package for the Social Sciences (SPSS) version 24.0 to analyze the data. The results of the study revealed that teachers liked and welcomed GTM to be applied in English classrooms. Furthermore, the results also showed that participants considered GTM a very important method of teaching because it helped them teach grammar rules properly. Another finding of the study was that teachers would often translate short passages, instructions and any language items into L1 in order to help learners to learn the target language. Moreover, the study revealed that applying Grammar-Translation Method in language classroom affected the students’ performance. It also showed that there were not any statistically significant differences by their gender, age, and teaching experience except their language.
Consequential effects of using competing perspectives to predict learning style in e-learning systems

Abstract The learning processes have been significantly impacted by technology. Numerous learners have adopted technology-based learning systems as the preferred form of learning. It is then necessary to identify the learning styles of learners to deliver appropriate resources, engage them, increase their motivation, and enhance their satisfaction and learning outcomes. Adopting mixed method, this study evaluated the effects of using collaborative and automatic perspectives to predict VARK learning styles. Participants were first-year undergraduate Computer Science students. Questionnaires were administered and activity/event data were collected for analysis. Using Naive Bayes, J48, OneR, and SMO classifiers to extract patterns in activity/event data, the experimental results of the automatic perspective indicated improved classification of learning styles and performance of students compared with the collaborative technique. The prediction relevance of multimodal and read/write learning styles and accuracy of classification were better than other learning styles. Kinesthetic was not automatically identified. The students have different learning preferences in the same discipline; however, multimodal and read/write learning styles were dominant in both perspectives. Students who understood varied and simple formats of learning imagery objects were more likely to respond effectively to related assessments, and those who received varieties of course contents and information had their performance improved.
A dream, a visual diary: disruptive narrative modes in When the Camera Stopped Rolling (Jane Castle, 2021)

ABSTRACT Dubbed ‘a forgotten trailblazer’ of Australian filmmaking, Lilias Fraser was also the mother of cinematographer, Jane Castle, who spent more than a decade piecing together When the Camera Stopped Rolling (2021), a multifaceted documentary that draws on a rich archive of photographs, home movies and film footage shot by three generations of the Fraser-Castle family. Describing her love-hate relationship with the film, Castle says, ‘The final form was found through the making, rather than having a plan and applying a plan. I didn't know what it was about until it was finished. ’ In its final form, When the Camera Stopped Rolling disrupts audience expectations of a hagiographic or elegiac narrative celebrating the lifetime achievements of Lilias Fraser. Ultimately, When the Camera Stopped Rolling is Jane Castle's story: an exquisite work of autofiction and self-extraction from the Fraser-Castle family and its audio-visual archives.
Mottness Collapse in 1 T − TaS 2 − x Se x Transition-Metal Dichalcogenide: An Interplay between Localized and Itinerant Orbitals

Recent experiments have shown that the transition-metal dichalcogenide 1T-TaS${}_{2-x}$Se${}_{x}$ can transition from a Mott insulator to a superconductor by varying the S/Se ratio. New measurements with a scanning tunneling microscope along with first-principles calculations reveal the mechanism underlying this transition.
Noise filtering for accurate measurement of line edge roughness and critical dimension from SEM images

Measurements of the line edge roughness (LER) and critical dimension (CD) from scanning electron microscope (SEM) images are often required for analyzing circuit patterns transferred onto substrate systems. A common approach is to employ image processing techniques to detect feature boundaries from which the LER and CD are computed. SEM images usually contain a significant level of noise which affects the accuracy of measured LER and CD. This requires reducing the noise level by a certain type of low-pass filter before detecting feature boundaries. However, a low-pass filter also tends to destroy the boundary detail. Therefore, a careful selection of low-pass filter is necessary in order to achieve the high accuracy of LER and CD measurements. In this paper, a practical method to design a Gaussian filter for reducing the noise level in SEM images is proposed. The method utilizes the information extracted from a given SEM image in adaptively determining the sharpness and size of a Gaussian filter. The results from analyzing the effectiveness of the Gaussian filter designed by the proposed method are provided.Measurements of the line edge roughness (LER) and critical dimension (CD) from scanning electron microscope (SEM) images are often required for analyzing circuit patterns transferred onto substrate systems. A common approach is to employ image processing techniques to detect feature boundaries from which the LER and CD are computed. SEM images usually contain a significant level of noise which affects the accuracy of measured LER and CD. This requires reducing the noise level by a certain type of low-pass filter before detecting feature boundaries. However, a low-pass filter also tends to destroy the boundary detail. Therefore, a careful selection of low-pass filter is necessary in order to achieve the high accuracy of LER and CD measurements. In this paper, a practical method to design a Gaussian filter for reducing the noise level in SEM images is proposed. The method utilizes the information extracted from a given SEM image in adaptively determining the sharpness and size of a Gaussian filter. The resu.
A modified method for determining the focal ratio degradation and length properties of optical fibres in astronomy

Focal ratio degradation (FRD) is a major contributor to throughput and light loss in a fibre spectroscopic telescope system. We combine the guided mode theory in geometric optics and a well-known model, power distribution model (PDM), to predict and explain the FRD dependence properties. We present a robust method by modifying the energy distribution method (EDM) with \emph{f-intercept} to control the input condition. This method provides a way to determine the proper position of the fibre end on the focal plane to improve energy utilization and FRD performance, which lifts the relative throughput up to 95\% with variation of output focal ratio less than 2\%. And this method can also help to optimize the arrangement of the position of focal-plane plate to enhance the coupling efficiency in a telescope. To investigate length properties, we modified PDM by introducing a new parameter, focal distance \emph{f}, into the original model to make it available for multi-position measurement system. The results show that the modified model is robust and feasible for measuring the key parameter \emph{d}$_0$ to simulate the transmission characteristics. The output focal ratio in the experiment does not follow the prediction trend but shows an interesting phenomenon that the output focal ratio increases at first to the peak, then decreases and remains stable finally with increasing fibre length longer than 15m, which provides a reference for choosing appropriate length of fibre to improve the FRD performance for the design of the fibre system in a telescope.
Reaction Mechanisms and Kinetic Constants used in Mechanistic Models of Coagulation and Fibrinolysis

Computational modeling has gained a strong foothold as a tool for understanding and simulating biological phenomena like blood coagulation. However, exceptional complexity of these phenomena (that include hundreds of individual biochemical processes and a few biophysical processes) complicates development of reliable models and interpretation of the results. It is thus of great importance that a model of hemostasis designed for a particular application should be reproducible, apart from making robust predictions. Such a model would further reflect useful pharmacological implications not only with respect to identifying drug targets but also in understanding drug effects on their respective targets. We show, using a sample model, that model predictions vary significantly with the use of different values available in the literature for the same kinetic constant. We thus highlight the importance of having consensus of kinetic constants used in the formulation of mechanistic models for coagulation, and document values for each kinetic constant that can be used in such models, and for varying reaction conditions (synthetic, in vitro, in vivo).
Numerical simulation of Burgers’ equation using cubic B-splines

Abstract In this paper, a numerical θ scheme is proposed for solving nonlinear Burgers’ equation. By employing Hopf-Cole transformation, the nonlinear Burgers’ equation is linearized to the linear Heat equation. The resulting Heat equation is further solved by cubic B-splines. The time discretization of linear Heat equation is carried out using Crank-Nicolson scheme θ = 1 2 $\left( {\theta = {\textstyle{1 \over 2}}} \right)$ as well as backward Euler scheme (θ = 1). Accuracy in temporal direction is improved by using Richardson extrapolation. This method hence possesses fourth order accuracy both in space and time. The system of matrix which arises by using cubic splines is always diagonal. Therefore, working with splines has the advantage of reduced computational cost and easy implementation. Stability of the schemes have been discussed in detail and shown to be unconditionally stable. Three examples have been examined and the L2 and L∞ error norms have been calculated to establish the performance of the method. The numerical results obtained on applying this method have shown to give more accurate results than existing works of Kutluay et al. [1], Ozis et al. [2], Dag et al. [3], Salkuyeh et al. [4] and Korkmaz et al. [5].
QueryX: Symbolic Query on Decompiled Code for Finding Bugs in COTS Binaries

Extensible static checking tools, such as Sys and CodeQL, have successfully discovered bugs in source code. These tools allow analysts to write application-specific rules, referred to as queries. These queries can leverage the domain knowledge of analysts, thereby making the analysis more accurate and scalable. However, the majority of these tools are inapplicable to binary-only analysis. One exception, joern, translates a binary code into decompiled code and feeds the decompiled code into an ordinary C code analyzer. However, this approach is not sufficiently precise for symbolic analysis, as it overlooks the unique characteristics of decompiled code. While binary analysis platforms, such as angr, support symbolic analysis, analysts must understand their intermediate representations (IRs) although they are mostly working with decompiled code.In this paper, we propose a precise and scalable symbolic analysis called fearless symbolic analysis that uses intuitive queries for binary code and implement this in QueryX. To make the query intuitive, QueryX enables analysts to write queries on top of decompiled code instead of IRs. In particular, QueryX supports callbacks on decompiled code, using which analysts can control symbolic analysis to discover bugs in the code. For precise analysis, we lift decompiled code into our IR named DNR and perform symbolic analysis on DNR while considering the characteristics of the decompiled code. Notably, DNR is only used internally such that it allows analysts to write queries regardless of using DNR. For scalability, QueryX automatically reduces control-flow graphs using callbacks and ordering dependencies between callbacks that are specified in the queries. We applied QueryX to the Windows kernel, the Windows system service, and an automotive binary. As a result, we found 15 unique bugs including 10 CVEs and earned $180,000 from the Microsoft bug bounty program.
Building Volumetric Beliefs for Dynamic Environments Exploiting Map-Based Moving Object Segmentation

Mobile robots that navigate in unknown environments need to be constantly aware of the dynamic objects in their surroundings for mapping, localization, and planning. It is key to reason about moving objects in the current observation and at the same time to also update the internal model of the static world to ensure safety. In this letter, we address the problem of jointly estimating moving objects in the current 3D LiDAR scan and a local map of the environment. We use sparse 4D convolutions to extract spatio-temporal features from scan and local map and segment all 3D points into moving and non-moving ones. Additionally, we propose to fuse these predictions in a probabilistic representation of the dynamic environment using a Bayes filter. This volumetric belief models, which parts of the environment can be occupied by moving objects. Our experiments show that our approach outperforms existing moving object segmentation baselines and even generalizes to different types of LiDAR sensors. We demonstrate that our volumetric belief fusion can increase the precision and recall of moving object segmentation and even retrieve previously missed moving objects in an online mapping scenario.