Miracle-dz/UniFAR-FTUs huggingface dataset:
Task Cortical Connectivity Reveals Different Network Reorganizations between Mild Stroke Patients with Cortical and Subcortical Lesions

Accumulating efforts have been made to investigate cognitive impairment in stroke patients, but little has been focused on mild stroke. Research on the impact of mild stroke and different lesion locations on cognitive impairment is still limited. To investigate the underlying mechanisms of cognitive dysfunction in mild stroke at different lesion locations, electroencephalograms (EEGs) were recorded in three groups (40 patients with cortical stroke (CS), 40 patients with subcortical stroke (SS), and 40 healthy controls (HC)) during a visual oddball task. Power envelope connectivity (PEC) was constructed based on EEG source signals, followed by graph theory analysis to quantitatively assess functional brain network properties. A classification framework was further applied to explore the feasibility of PEC in the identification of mild stroke. The results showed worse behavioral performance in the patient groups, and PECs with significant differences among three groups showed complex distribution patterns in frequency bands and the cortex. In the delta band, the global efficiency was significantly higher in HC than in CS (p = 0.011), while local efficiency was significantly increased in SS than in CS (p = 0.038). In the beta band, the small-worldness was significantly increased in HC compared to CS (p = 0.004). Moreover, the satisfactory classification results (76.25% in HC vs. CS, and 80.00% in HC vs. SS) validate the potential of PECs as a biomarker in the detection of mild stroke. Our findings offer some new quantitative insights into the complex mechanisms of cognitive impairment in mild stroke at different lesion locations, which may facilitate post-stroke cognitive rehabilitation.
Does sticky cost represent a distortion of cost accounting principles? A critical view of ten divisive issues

Purpose : This paper arguably discusses the theory and reasoning of sticky cost across ten divisive issues covering the determinants, measurement and utility of cost stickiness classification. The paper shows that several neglected factors in literature impact the elasticity of cost groups such as cost behavior of cost items within cost groups in the short and long term, type of activity of business firms under study, production resources and selling price considerations, and absence of strategic management accounting techniques within business firms. Method : An empirical study posited that describing SG&A expenses behavior as sticky cost as a result of using financial variables, will not differ from the use of physical variables as explanatory variables of this stickiness. Financial and non-financial information for all EGX 100 is extracted from Egypt for Information Dissemination) EGID) for years 2016 to 2020. The final sample included 248 observations for 61 industrial firms. Anderson, Banker, and Janakiraman (2003) model is used in three regression equations to test the combined hypothesis of the research. Findings : Result of the statistical analysis reveals that pricing changes of revenue represent the main cause of cost stickiness behavior and replacing physical variables instead of financial variables may provide different results for many studies that addressed cost stickiness behavior. Originality : The paper develops suggestions of how future research should focus on aligning what is proposed by developed theories in accounting research with basics of accounting principles and the beneficial reflection of such theories in practice on business firms. The paper concludes that cost structure and control in addition to other factors impact the detection of short-term cost management decisions.
The spectral density for scalar elds in de Sitter spaceat one-loop

We review the Kallen-Lehmann spectral representation in �at spacetime before moving on to de Sitter space. We compute one-loop corrections of de Sitter invariant two-point functions in the Lorentzian signature which are de�ned by the interacting Euclidean vacuum for scalar �elds with cubic interactions. These apply to all massive scalars in the complementary and principal series. Our investigations are motivated by the behaviour of the spectral density at the one-loop level whereby we can �nd a general expression relating the two-point function and the free propagators. Using well established techniques for treating quantum �elds in de Sitter, we compute the spectral density for speci�c cases, in both complementary and principal series in three dimensions and discuss the nature of particle stability. We also comment on extending this beyond the one-loop level.
Monkeypox Diagnosis With Interpretable Deep Learning

As the world gradually recovers from the impacts of COVID-19, the recent global spread of Monkeypox disease has raised concerns about another potential pandemic, highlighting the urgency of early detection and intervention to curb its transmission. Deep Learning (DL)-based disease prediction presents a promising solution, offering affordable and accessible diagnostic services. In this study, we harnessed Transfer Learning (TL) techniques to tweak and assess the performance of an array of six different DL models, encompassing VGG16, InceptionResNetV2, ResNet50, ResNet101, MobileNetV2, VGG19, and Vision Transformer (ViT). Among this diverse collection, it was the modified versions of the VGG19 and MobileNetV2 models that outshone the others, boasting striking accuracy rates ranging from an impressive 93% to an astounding 99%. Our results echo the findings of recent research endeavors that similarly showcase enhanced performance when developing disease diagnostic models armed with the power of TL. To add to this, we used Local Interpretable Model Agnostic Explanations (LIME) to lend a sense of transparency to our model’s predictions and identify the crucial features correlating with the onset of Monkeypox disease. These findings offer significant implications for disease prevention and control efforts, particularly in remote and resource-limited areas.
Candida parapsilosis sensu stricto Antifungal Resistance Mechanisms and Associated Epidemiology

Fungal diseases cause millions of deaths per year worldwide. Antifungal resistance has become a matter of great concern in public health. In recent years rates of non-albicans species have risen dramatically. Candida parapsilosis is now reported to be the second most frequent species causing candidemia in several countries in Europe, Latin America, South Africa and Asia. Rates of acquired azole resistance are reaching a worrisome threshold from multiple reports as in vitro susceptibility testing is now starting also to explore tolerance and heteroresistance to antifungal compounds. With this review, the authors seek to evaluate known antifungal resistance mechanisms and their worldwide distribution in Candida species infections with a specific focus on C. parapsilosis.
Continuous doping of a cuprate surface: Insights from 
in situ
 angle-resolved photoemission

The cuprate superconductors distinguish themselves from the conventional superconductors in that a small variation in the carrier doping can significantly change the superconducting transition temperature (T_c), giving rise to a superconducting dome where a pseudogap (ref. 1,2) emerges in the underdoped region and a Fermi liquid appears in the overdoped region. Thus a systematic study of the properties over a wide doping range is critical for understanding the superconducting mechanism. Here, we report a new technique to continuously dope the surface of Bi2Sr2CaCu2O8+x through an ozone/vacuum annealing method. Using in-situ ARPES, we obtain precise quantities of energy gaps and the coherent spectral weight over a wide range of doping. We discover that the d-wave component of the quasiparticle gap is linearly proportional to the Nernst temperature that is the onset of superconducting vortices (ref. 3), strongly suggesting that the emergence of superconducting pairing is concomitant with the onset of free vortices, with direct implications for the onset of superconducting phase coherence at T_c and the nature of the pseudogap phenomena.
A dynamic SLAM algorithm for fusion of semantic and depth information

Simultaneous Localization and Mapping (SLAM) plays a critical role in the field of intelligent mobile robots. However, the traditional visual SLAM framework is based on the strong assumption of a static environment, which is not applicable in dynamic real-world environments. This paper presents a SLAM algorithm that combines semantic and depth information. Firstly, we combine object detection and geometric methods to identify dynamic regions. Secondly, dynamic and static feature points are distinguished using a depth information classification method in these dynamic regions. Then, we eliminate the dynamic feature points and only pass the static feature points to other threads. Finally, we evaluate our approach on the public TUM RGB-D datasets and compare it against other state-of-the-art methods. The experimental results demonstrate the proposed SLAM algorithm has good accuracy and stability in dynamic environments.
Spermatogenesis after gonadotoxic childhood treatment: follow-up of 12 patients

Abstract STUDY QUESTION What is the long-term impact of presumed gonadotoxic treatment during childhood on the patient’s testicular function at adulthood? SUMMARY ANSWER Although most patients showed low testicular volumes and some degree of reproductive hormone disruption 12.3 (2.3–21.0) years after gonadotoxic childhood therapy, active spermatogenesis was demonstrated in the semen sample of 8 out of the 12 patients. WHAT IS KNOWN ALREADY In recent decades, experimental testicular tissue banking programmes have been set up to safeguard the future fertility of young boys requiring chemo- and/or radiotherapy with significant gonadotoxicity. Although the risk of azoospermia following such therapies is estimated to be high, only limited long-term data are available on the reproductive potential at adulthood. STUDY DESIGN, SIZE, DURATION This single-centre prospective cohort study was conducted between September 2020 and February 2023 and involved 12 adult patients. PARTICIPANTS/MATERIALS, SETTING, METHODS This study was carried out in a tertiary care centre and included 12 young adults (18.1–28.3 years old) who had been offered testicular tissue banking prior to gonadotoxic treatment during childhood. All patients had a consultation and physical examination with a fertility specialist, a scrotal ultrasound to measure the testicular volumes and evaluate the testicular parenchyma, a blood test for assessment of reproductive hormones, and a semen analysis. MAIN RESULTS AND THE ROLE OF CHANCE Testicular tissue was banked prior to the gonadotoxic treatment for 10 out of the 12 included patients. Testicular volumes were low for 9 patients, and 10 patients showed some degree of reproductive hormone disruption. Remarkably, ongoing spermatogenesis was demonstrated in 8 patients at a median 12.3 (range 2.3–21.0) years post-treatment. LIMITATIONS, REASONS FOR CAUTION This study had a limited sample size, making additional research with a larger study population necessary to verify these preliminary findings. WIDER IMPLICATIONS OF THE FINDINGS These findings highlight the need for multicentric research with a larger study population to establish universal inclusion criteria for immature testicular tissue banking. STUDY FUNDING/COMPETING INTEREST(S) This study was conducted with financial support from the Research Programme of the Research Foundation-Flanders (G010918N), Kom Op Tegen Kanker, and Scientific Fund Willy Gepts (WFWG19-03). The authors declare no competing interests. TRIAL REGISTRATION NUMBER NCT04202094; https://clinicaltrials.gov/ct2/show/NCT04202094? id=NCT04202094&draw=2&rank=1 This study was registered on 6 December 2019, and the first patient was enrolled on 8 September 2020.
Exploring the Antioxidant, Neuroprotective, and Anti-Inflammatory Potential of Olive Leaf Extracts from Spain, Portugal, Greece, and Italy

The leaves of the olive tree (Olea europaea L.) are one of the major solid wastes from the olive industry. Globally, the European Union is the largest producer of olive by-products, with Spain, Italy, Greece, and Portugal accounting for almost the entire production. Many questions remain to be solved concerning olive leaves (OL), including those related to possible differences in composition and/or biological activities depending on their geographical origin. In the present work, OL from Spain, Italy, Greece, and Portugal have been characterized according to their phytochemical profile, antioxidant capacity, neuroprotective activity, and anti-inflammatory effects. The Spanish and Italian OL samples presented the highest antioxidant and neuroprotective activities, while the Greek OL showed the lowest. These results were strongly associated with the content of oleoside methyl ester and p-hydroxybenzoic acid for the Spanish and Italian samples, respectively, whereas the content of decarboxymethyl elenolic acid dialdehyde form (hydrated) was negatively associated with the mentioned biological activities of the Greek samples. No country-related effect was observed in the anti-inflammatory activity of OL. Comprehensively, this work could provide a useful tool for manufacturers and R&D departments in making environmentally friendly decisions on how OL can be used to generate nutraceutical products based on the composition and origin of this by-product.
Dermatomyositis Presenting with Generalized Subcutaneous Edema

Generalized subcutaneous edema is rare in dermatomyositis. We herein report an 82-year-old woman with dermatomyositis who presented with generalized subcutaneous edema. Three weeks before admission, she first noticed facial edema, and the symptoms exacerbated, with limb edema occurring. On admission, muscle weakness in the limbs and skin rash were noted. Her muscle enzyme levels were elevated, and serum anti-transcriptional intermediary factor 1-γ antibody was detected. She was diagnosed with dermatomyositis and treated with corticosteroids and tacrolimus, which improved her muscle weakness, muscle enzymes, and edema. Thus, generalized subcutaneous edema can occur during dermatomyositis, with facial edema as the initial symptom.
Effects of Pre-Emulsification with Thermal-Denatured Whey Protein on Texture and Microstructure of Reduced-Sodium Processed Cheese

Thermal-denatured whey protein-milk fat emulsion gels with different degrees of pre-emulsification were prepared by pre-emulsifying milk fat with thermal-denatured whey protein and used in the preparation of reduced-sodium processed cheeses. The effect of the thermal-denatured whey protein pre-emulsification process on the texture and microstructure of reduced-sodium processed cheeses was evaluated by studying the composition, color, texture, functional properties, microstructure and sensory analysis of the processed cheeses. The results showed that compared with cheese without pre-emulsified fat (1.5% ES control), the moisture content of cheese with pre-emulsified 100% fat (1.5% ES100) increased by 5.81%, the L* values increased by 7.61%, the hardness increased by 43.24%, and the free oil release decreased by 38%. The microstructure showed that the particle size of fat was significantly reduced, and the distribution was more uniform. In addition, compared with the cheese added with 3% emulsifying salt (3% ES control), the amount of emulsifying salt in the 1.5% ES100 decreased by 50%, but the fat distribution of the two kinds of cheese tended to be consistent, and there was no obvious change in texture characteristics and meltability. Sensory scores increased with the increase in pre-emulsification degree. Overall, the pre-emulsification of milk fat with thermal-denatured whey protein can reduce the sodium content of processed cheese and improve its quality.
Evaluation of the role of FMR1 CGG repeat allele in Parkinson’s disease from the Chinese population

Objective There is controversial evidence that FMR1 premutation or “gray zone” (GZ) allele (small CGG expansion, 45–54 repeats) was associated with Parkinson’s disease (PD). We aimed to explore further the association between FMR1 CGG repeat expansions and PD in a large sample of Chinese origin. Methods We included a cohort of 2,362 PD patients and 1,072 controls from the Parkinson’s Disease and Movement Disorders Multicenter Database and Collaborative Network in China (PD-MDCNC) in this study and conducted repeat-primed polymerase chain reaction (RP-PCR) for the size of FMR1 CGG repeat expansions. Results Two PD patients were detected with FMR1 premutation (61 and 56 repeats), and the other eleven PD patients were detected with the GZ allele of FMR1 CGG repeat expansions. Those thirteen PD patients responded well to levodopa and were diagnosed with clinically established PD. Specifically, one female PD patient with GZ allele was also found with premature ovarian failure. However, compared to healthy controls, we found no significant enrichment of GZ allele carriers in PD patients or other subgroups of PD cases, including the subgroups of female, male, early-onset, and late-onset PD patients. Furthermore, we did not find any correlation between the FMR1 gene CGG repeat sizes and age at onset of PD. Conclusion It suggested that FMR1 premutation was related to PD, but the GZ allele of FMR1 CGG repeat expansions was not significantly enriched in PD cases of Chinese origin. Further larger multiple ethnic studies are needed to determine further the role of the FMR1 GZ allele in PD.
Analysis of the Effect of Soil Roughness in the Forward-Scattering Interference Pattern Using Second-Order Small Perturbation Method Simulations

Soil moisture (SM) is a key geophysical variable that can be estimated at regional scales using remote sensing techniques, by making use of the known relationship between soil reflectivity and the dielectric constant in the microwave regime. In this context, the exploitation of available illuminators of opportunity that currently emit large amounts of power at microwave frequencies (compared to typical synthetic aperture radar systems) is promising. Some published techniques estimate SM by analyzing the interference pattern (IP) between direct and reflected signal as measured by a single antenna (i.e., IP technique). In this letter, a new approach to simulate the IP is proposed, in which the soil roughness is modeled straightforwardly using the second-order small perturbation model. Results illustrate that the “notch” in the VV-polarization IP (related to the Brewster angle) can only be directly observed for very low values of soil rms roughness (<inline-formula> <tex-math notation="LaTeX">$s < 0.5$ </tex-math></inline-formula> cm). For typical values of soil roughness (<inline-formula> <tex-math notation="LaTeX">$s\sim 1.2$ </tex-math></inline-formula> cm), the notch disappears and only a minimum in the IP is observed near the Brewster angle.
Surface Modifications of Superparamagnetic Iron Oxide Nanoparticles with Polyvinyl Alcohol, Chitosan, and Graphene Oxide as Methylene Blue Adsorbents

Synthetic dye contamination of wastewater has long been a social issue, with adsorption being the most focused upon research technique among wastewater treatment. Using the co-precipitation method, superparamagnetic iron oxide nanoparticles (SPIONs) with the size of 13.6 ± 1.9 nm were synthesized. By adsorbing methylene blue (MB) on the modified surface of SPIONs using polyvinyl alcohol, chitosan, and graphene oxide, the entrapment efficiency at pH 7 can be up to 87.00 ± 0.16% after 13 days, and the highest MB loading capacity was 3.638 ± 0.009%, while the highest loading amount achieved was 36.385 ± 0.095 mg/g. The cumulative desorption capacity of the adsorbent at pH 3.8 was at its maximum at 8.94 ± 0.66% after 30 days. The results of the experiments indicated that the compound has a favorable impact on the adsorption of synthetic dyes; nevertheless, more research is needed to determine the ideal ratio, temperature, and pH levels for this chemical.
Development of Teaching Materials to Support Merdeka Curriculum Learning on Solubility and Solubility Product in F Phase

By the Covid-19 pandemic which shows that students' interest in learning is decreasing and cause learning loss, the Ministry of Education and Culture is trying to restore learning given the difficulties that have arisen with launching an merdeka curriculum, the teachers and students need using learning tools as learning resources in accordance with the merdeka curriculum. This research aims to develop teaching materials to support merdeka curriculum learning on the solubility and solubility product in the F phase and reveal the validity and practicality developed. This type of research is development research using the Plomp model. This research is limited to the formation of a valid and practical prototype IV. The instrument used in this study was a questionnaire in the form of a questionnaire of validation and practicality sheets. This study conducted a validity test using the Aiken's V formula and a practicality test using the practicality using the category of practicality level adaption from Purwanto. Validation was carried out by 5 experts, namely 3 lecturers and 2 chemistry teachers. The practicality sheet was filled in by 2 chemistry teachers and 9 Phase F students at SMAN 7 Padang. Also one to one evaluation by 3 students. The validity test data processing results are 0.89 which shows the valid category. For the results of data processing for the practicality test of students, namely 88% and the teacher's practicality test is 94% which shows a very practical category. It can be concluded that teaching materials to support merdeka curriculum learning on solubility and solubility product are valid and practical
Role of synaptic variability in resistive memory-based spiking neural networks with unsupervised learning

Resistive switching memories (RRAMs) have attracted wide interest as adaptive synaptic elements in artificial bio-inspired spiking neural networks (SNNs). These devices suffer from high cycle-to-cycle and cell-to-cell conductance variability, which is usually considered as a big challenge. However, biological synapses are noisy devices and the brain seems in some situations to benefit from the noise. It has been predicted that RRAM-based SNNs are intrinsically robust to synaptic variability. Here, we investigate this robustness based on extensive characterization data: we analyze the role of noise during unsupervised learning by spike-timing dependent plasticity (STDP) for detection in dynamic input data and classification of static input data. Extensive characterizations of multi-kilobits HfO2-based oxide-based RAM (OxRAM) arrays under different programming conditions are presented. We identify the trade-offs between programming conditions, power consumption, conductance variability and endurance features. Finally, the experimental results are used to perform system-level simulations fully calibrated on the experimental data. The results demonstrate that, similarly to biology, SNNs are not only robust to noise but a certain amount of noise can even improve the network performance. OxRAM conductance variability increases the range of synaptic values explored during the learning process. Moreover, the reduction of constraints on the OxRAM conductance variability allows the system to operate at low power programming conditions.