Miracle-dz/UniFAR-FTUs huggingface dataset:
Phytochemical, Antioxidant potential and ftir analysis on the matured leaves of Camellia Oleifera abel

Phytochemicals are physiologically active compounds and are derived from plants. Majority of the phytochemicals have been known to bear therapeutic activities like antibacterial, antioxidant, antifungal, antispasmodic, anticancer, hepatoprotective etc. The aim of this study is to evaluate the phytochemicals in the matured leaves of Camellia oleifera belonging to the family Theaceae. The phytochemicals were extracted from the dried matured leaves of C. oleifera using solvent extraction method. The preliminary phytochemical analysis showed the presence of alkaloids, tannins, saponins, phenols and flavonoids in the ethanolic extract. Further the antioxidant property of the leaf extract was carried out using standard procedure. The extract was subjected to FTIR analysis. The study shows that the ethanolic extracts possess secondary metabolites and antioxidant properties that are therapeutically valuable.
Deep Learning Method for Heliostat Instance Segmentation

Heliostat instance segmentation (HST-IS) is a crucial component of the heliostat tracking system at Heliogen’s Lancaster test facility. The system estimates the mirror normal of each heliostat by performing a nonlinear optimization-based fitting strategy using approximations of the non-shaded, non-blocked sunlit pixels on each heliostat, and the tracking system uses these estimates to improve performance. HST-IS is fundamentally challenging due to variability in lighting conditions and heliostat size relative to the capturing camera. Deep learning-based convolutional neural networks (CNN) have emerged in recent years by demonstrating noteworthy precision in tasks such as object recognition, detection, and segmentation. CNN-based methods offer a robust augmentation to HST-IS methods as they capture a context-less hierarchy of image features. In this study, we developed deep learning models to automatically segment heliostat instances from elevated images taken from the field. We study various image parameters and architectural customizations to optimize for scalability, robustness, and accuracy in our predictions. We perform robust evaluations of our best model to quantify gaps between model development and real-world deployment and provide evidence for utility in the field.
Prevalence of Secondary Hyperparathyroidism in Hemo- Dialysis Patients

Introduction: One persistent complication of chronic kidney disease is secondary hyperparathyroidism. Early diagnosis of this disease will reduce morbidity in patients undergoing hemodialysis. Aims & Objectives: To determine the prevalence of secondary hyperparathyroidism in chronic kidney disease patients at National Institute of Kidney Diseases, SZH Lahore. Place and Duration of Study: A cross sectional study was conducted at Nephrology Department of Shaikh Zayed Hospital (SZH) Lahore after getting approval from Institutional Review Board of National Health Research Complex (NHRC). It was conducted from September 2023 to November 2023 &140 hemo-dialysis patients were selected. Material & Methods: We measured serum parathyroid hormone, hemoglobin and other variables, at Biochemistry laboratory of Sheikh Zayed Hospital, in 140 hemodialysis patients. Serum samples were measured for PTH levels using ELISA method. The data was analyzed using SPSS version 20.P value ? 0.05 was considered significant. Results: Fifteen patients had secondary hyperparathyroidism out of 140 hemodialysis patients. Hyperparathyroidism was observed in 10.71 % of the patients. Hyperparathyroidism patients had significantly low calcium, hemoglobin levels & higher phosphate levels. Conclusion: The prevalence of secondary hyperparathyroidism is low at 10.71% of patients undergoing hemodialysis at National Institute of Kidney Disease, SZH Lahore.
Sortilin Expression Levels and Peripheral Immunity: A Potential Biomarker for Segregation between Parkinson’s Disease Patients and Healthy Controls

Parkinson’s disease (PD) is characterized by substantial phenotypic heterogeneity that limits the disease prognosis and patient’s counseling, and complicates the design of further clinical trials. There is an unmet need for the development and validation of biomarkers for the prediction of the disease course. In this study, we utilized flow cytometry and in vitro approaches on peripheral blood cells and isolated peripheral blood mononuclear cell (PBMC)-derived macrophages to characterize specific innate immune populations in PD patients versus healthy donors. We found a significantly lower percentage of B lymphocytes and monocyte populations in PD patients. Monocytes in PD patients were characterized by a higher CD40 expression and on-surface expression of the type I membrane glycoprotein sortilin, which showed a trend of negative correlation with the age of the patients. These results were further investigated in vitro on PBMC-derived macrophages, which, in PD patients, showed higher sortilin expression levels compared to cells from healthy donors. The treatment of PD-derived macrophages with oxLDL led to higher foam cell formation compared to healthy donors. In conclusion, our results support the hypothesis that surface sortilin expression levels on human peripheral monocytes may potentially be utilized as a marker of Parkinson’s disease and may segregate the sporadic versus the genetically induced forms of the disease.
Application of the Compound Interest Model in Analyzing Long-Term Investments on Nvdia Company Stock

Long-term investment is a strategic decision that requires careful planning and in-depth analysis. One approach to analyze the potential returns from long-term investments is through the application of the compound interest model. This model considers the accumulation of interest on both the principal amount and the previously earned interest, providing a more realistic picture of investment growth over time.This research aims to explore how the application of the compound interest model can enhance the analysis of long-term investments. The analysis of these variables provides a comprehensive picture of the dynamics of investment growth and opens up opportunities for more informed investment decision-making. This research emphasizes the importance of a thorough understanding of the key variables in the compound interest model to enhance the accuracy of investment decisions.The findings of this research are expected to offer practical guidance for investors and financial practitioners in managing their portfolios more intelligently and measurably. These findings make a significant contribution to the development of more effective long-term investment strategies, thereby enhancing portfolio performance and overall investment outcomes.
Synthesis of Novel Artemisinin, Ciprofloxacin, and Norfloxacin Hybrids with Potent Antiplasmodial Activity

The synthesis and antiplasmodial evaluation of new hybrids combining the pharmacophore structures of artemisinin, ciprofloxacin or norfloxacin, and 7-chloroquinoline are reported in this study. The first step for all of the syntheses is the obtainment of key piperazine esters intermediates bearing the drugs ciprofloxacin and norfloxacin. Using these platforms, 18 final compounds were synthesized through a multistep procedure with overall yields ranging between 8 and 20%. All compounds were screened for their antiplasmodial activity against the chloroquine-resistant Plasmodium falciparum FcB1 strain. Compounds 20, 21, 22, and 28, bearing an artesunate fragment with ciprofloxacin, exhibited IC50 values in the range of 3.5–5.4 nM and excellent selectivity indices. Among the compounds bearing the artesunate moiety on the norfloxacin, two of them, 23 and 24, afforded IC50 values of 1.5 nM and 1.9 nM, respectively. They also showed excellent selectivity indices. The most potent compounds were also evaluated against the CQ-resistant Dd2 strain of Plasmodium falciparum, demonstrating that those compounds incorporating the artesunate fragment were the most potent. Finally, the combination of artesunate with either ciprofloxacin or norfloxacin moieties in a single molecular entity proved to substantially enhance the activity and selectivity when compared to the administration of the unconjugated counterparts artesunate/ciprofloxacin and artesunate/norfloxacin.
Effects of Balsa Fish Skin Gelatin, Lentinula edodes Mushrooms, Soy Protein Isolate, and Starch on the Sensory Quality and Characterization of Physicochemical and Antioxidant Properties of New Sausage

Sausages are loved by people for their unique texture, satisfying chewiness, and pleasant flavor. However, in the production of sausages, red meat and a large amount of fat are mainly used, and long-term consumption will increase the risk of diseases such as obesity, heart disease, hypertension, and cancer. Our previous studies have shown that the intake of red meat and fat can be reduced through the replacement of lean meat and fat in sausages by Lentinula edodes and Pleaurotus eryngii mushrooms, but this will lead to the deterioration of the gel of sausage products and seriously affect the sensory quality of sausages. In this study, the response surface method was used to optimize the amount of balsa fish skin gelatin, soy protein isolate, and starch added to, and the proportion of Lentinula edodes mushrooms replacing lean meat in, the new sausage, with Pleaurotus eryngii mushrooms replacing fat. The results show that Lentinula edodes mushrooms replaced 36.1% of the lean meat, and the addition of 0.96% balsa fish skin gelatin, 10.61% starch, and 9.94% soy protein isolate resulted in the highest sensory score and the sensory quality being the closest to that of traditional sausages. Compared with the control group, this novel sausage exhibits characteristics such as lower fat and saturated fatty acid content, reduced energy levels, and higher levels of amino acids (aspartic acid, glutamic acid, cysteine, methionine, and proline) and polyunsaturated fatty acids. The total phenolic content of the novel sausage is 12.52 times higher than that of the control. In comparison with the control group, the novel sausage demonstrates a 65.58% increase in DPPH radical scavenging activity and a 3.88-fold improvement in ABTS+ radical scavenging activity. These findings highlight the outstanding antioxidant performance of the novel sausage. This study provides new ideas for improving the sensory quality of new sausages, promoting the healthy development of the sausage industry, and promoting the high-value utilization of edible mushrooms.
Supportivtherapie beim Pankreaskarzinom

In frühen Stadien präsentieren sich Patienten mit einem Pankreaskarzinom typischerweise mit unspezifischen Symptomen wie abdominellen Beschwerden (Völlegefühle, Übelkeit) und Rückenschmerzen. Diese Befundkonstellation führt in Kombination mit der aggressiven Tumorbiologie des Pankreaskarzinoms dazu, dass nur rund 20 % der Tumoren in einem primär resektablen Stadium erkannt werden, bei weiteren ca. 20 % handelt es sich um lokal fortgeschrittene Tumoren und ca. 60 % sind bei Diagnosestellung bereits metastasiert [1].
Corporate Social Responsibility and other factors affecting Tax Avoidance

The primary objective of this research is to obtain empirical evidence for the influence of corporate social responsibility (CSR) and other factors including return on asset, leverage, sales growth, capital intensity ratio, inventory intensity ratio, firm size, financial distress, accounting conservatism on tax avoidance. Population used in this research are consumer non-cyclicals and consumer cyclicals companies listed on the Indonesian Stock Exchange (IDX) from 2020 to 2022. The study employs a purposive sampling technique with the final result meeting the criteria on 62 companies, 186 data over a three-year period from 2020 to 2022. This research used multiple regression method to analyze the data. The results reveal that return on asset, sales growth, and inventory intensity ratio influence tax avoidance. On contrary, leverage, capital intensity ratio, firm size, financial distress, accounting conservatism, and corporate social responsibility show no influence on tax avoidance. Depending on the amount of profitability the business experiences, it will decide what steps to take to maximize its net profit. In other side, companies that incur costs that can be counted as tax deductions feel that the company no longer needs to avoid taxes.
Role of Satisfaction with Life, Sex and Body Mass Index in Physical Literacy of Spanish Children

Physical activity (PL) is essential to achieve good health, prevent cardiovascular diseases, obesity and overweight, as well as to achieve a better quality of life. Therefore, PL could become the tool to increase the practice of physical activity among young people, thus increasing life satisfaction (LS) given its positive relationship with physical activity. A single-measure cross-sectional correlational study was carried out, involving 135 children aged 8–12 years from Extremadura. They were administered the SWLS questionnaire and the Canadian assessment of physical literacy (CAPL-2). Significantly higher levels of PL (p = 0.010) were found in normal-weight children compared to overweight and obese children, due to the physical competence domain score (p < 0.001). PL was directly related to SWLS (p < 0.001), but inversely related to BMI (p = 0.018). The daily physical activity behaviour domain was explained by SWLS (p < 0.001) and sex (p < 0.001). Physical competence was described by SWLS (p < 0.001) and BMI (p = 0.045). Finally, the motivation and confidence domain were only significantly associated with SWLS (p < 0.001). It was concluded that boys and girls of normal weight achieved higher levels of PL and LS than those with overweight and obesity, establishing a negative relationship of PL with BMI and positive with LS.
Optimal Compensation Strategy for Demand Side Response to Improve the Renewable Energy Consumption

Herein, efforts are mainly made to investigate the way to promote new energy to be better absorbed in the multi-energy market where comprehensive demand response participates in competition. Considering the future trend of new energy power generation, a multi-market trading framework for IDR (integrated demand response) resources to get involved in competition is hereby proposed to address the problem of wind and electricity abandonment. The integrated demand response exchange (IDRX) market is introduced. In the case of scarce power resources, IDR users can increase their power demand response ability through gas-electric replacement, sell power load reduction resources in IDRX market and purchase natural gas resources for power replacement. The integrated demand response aggregator (IDRA) obtains power load reduction resources through the IDRX market and satisfies the gas purchase demand of IDR users. Meanwhile, the obtained power load reduction resources are used by IDRA to compete in the power wholesale market, and participate in the natural gas market demand bidding competition. Based on this multi-market trading framework, a compensation mechanism is introduced, a two-layer optimization model is constructed. The optimum compensation coefficient is calculated using the benders decomposition algorithm. Finally, an example is given to verify the validity of the hereby proposed trading framework, and the results indicate that the new energy can be better absorbed under the trading framework.
Multimodal Soft Amphibious Robots Using Simple Plastic-Sheet-Reinforced Thin Pneumatic Actuators

A large challenge in the field of soft amphibious robotics is achieving high maneuverability and multiterrain adaptability through multimodal locomotion in hybrid terrestrial–aquatic environments. To address this issue, drawing inspiration from fruit-fly larvae and Spanish dancer sea slugs, a novel tethered soft amphibious robot with multimodal locomotion is proposed in this article, performing forward, backward, turning, and self-overturn motions both on land and in water. It leverages plastic-sheet-reinforced thin pneumatic actuators, which are constructed from thermoplastic membranes and embedded with a nonstretchable plastic sheet, enabling bidirectional bending with large angles. The robot achieves a forward jumping velocity of 1.77 BL/s and a forward swimming velocity of 0.69 BL/s, both faster than previously reported soft amphibious robots; connecting two actuator units in parallel, it achieves agile turning with a velocity of 111.8$^\circ$/s. Our proposed robot demonstrates exceptional multiterrain adaptability, facile terrestrial–aquatic transition capabilities, and underwater buoyancy adjustment ability. Especially when accidentally overturned, it can recover itself without external assistance, a capability rarely achieved by other soft robots.
How Plant Toxins Cause Early Larval Mortality in Herbivorous Insects: An Explanation by Modeling the Net Energy Curve

Plants store chemical defenses that act as toxins against herbivores, such as toxic isothiocyanates (ITCs) in Brassica plants, hydrolyzed from glucosinolate (GLS) precursors. The fitness of herbivorous larvae can be strongly affected by these toxins, causing immature death. We modeled this phenomenon using a set of ordinary differential equations and established a direct relationship between feeding, toxin exposure, and the net energy of a larva, where the fitness of an organism is proportional to its net energy according to optimal foraging theory. Optimal foraging theory is widely used in ecology to model the feeding and searching behavior of organisms. Although feeding provides energy gain, plant toxins and foraging cause energy loss for the larvae. Our equations explain that toxin exposure and foraging can sharply reduce larval net energy to zero at an instar. Since herbivory needs energy, the only choice left for a larva is to stop feeding at that time point. If that is significantly earlier than the end of the last instar stage, the larva dies without food. Thus, we show that plant toxins can cause immature death in larvae from the perspective of optimal foraging theory.
Clinical Relevance and Interplay between miRNAs in Influencing Glioblastoma Multiforme Prognosis

Glioblastoma multiforme (GBM) is usually treated with surgery followed by adjuvant partial radiotherapy combined with temozolomide (TMZ) chemotherapy. Recent studies demonstrated a better survival and good response to TMZ in methylguanine-DNA methyltransferase (MGMT)-methylated GBM cases. However, approximately 20% of patients with MGMT-unmethylated GBM display an unexpectedly favorable outcome. Therefore, additional mechanisms related to the TMZ response need to be investigated. As such, we decided to investigate the clinical relevance of six miRNAs involved in brain tumorigenesis (miR-181c, miR-181d, miR-21, miR-195, miR-196b, miR-648) as additional markers of response and survival in patients receiving TMZ for GBM. We evaluated miRNA expression and the interplay between miRNAs in 112 IDH wt GBMs by applying commercial assays. Then, we correlated the miRNA expression with patients’ clinical outcomes. Upon bivariate analyses, we found a significant association between the expression levels of the miRNAs analyzed, but, more interestingly, the OS curves show that the combination of low miR-648 and miR-181c or miR-181d expressions is associated with a worse prognosis than cases with other low-expression miRNA pairs. To conclude, we found how specific miRNA pairs can influence survival in GBM cases treated with TMZ.
Internet de las cosas

Este es un curso de introduccion a la IoT (Internet de las cosas). En los capitulos primeros capitulos se introducen los conceptos basicos sobre la IoT. Seguidamente se presentan nociones basicas sobre el protocolo de internet IPv6 que es el mas utilizado en el entorno de la IoT y se describen las principales aplicaciones, el estado actual del mercado y las tecnologias que permiten la existencia de la IoT. Finalmente se analizan los retos de futuro que se consideran mas importantes.
Variation of Indonesian throughflow and the El Niño‐Southern Oscillation

The expendable bathythermograph (XBT) line Fremantle-Sunda Strait transects the eastern Indian Ocean between northwestern Australia and Java. It was established in 1983 with low-density sampling and upgraded to a frequently repeated line (>18 times per year) in 1987 to monitor currents. The observations during 1983 to 1994 are described and related to the field of wind stress. Variation of thermal structure shows a rich mixture of annual, semiannual, and interannual timescales. Empirical orthogonal function (EOF) analysis of anomalies of sea surface temperature (SST), dynamic height, and depth of the 20°C isotherm D20 identifies two distinctive signals. The El Nino - Southern Oscillation (ENSO) signal (EOF 1) appears throughout the region and is strongest off the coast of Australia. A modulation of the annual signal (EOF 2) appears off the coast of Java. EOF 2 has a shorter timescale than the ENSO signal, and its temporal coefficients are correlated to zonal winds over the equatorial Indian Ocean. For both EOFs, anomalously low SST and dynamic height occur at the same time as anomalously shallow D20 and vice versa for opposite anomalies. The XBT data are used with a climatological temperature-salinity relationship to calculate net, relative (0/400 dbar) geostrophic transports T through the section. For long timescales, T is representative of Indonesian throughflow. The variations associated with ENSO show a maximum during the La Nina of 1988–1989 and minima during the El Ninos of 1986–1987 and 1991–1994. The peak-to-trough amplitude of the ENSO signal is 5 Sv. The ENSO signal in throughflow is discussed in terms of earlier studies. For the shorter timescales, T is representative of currents from the Indian Ocean flowing in and out of the region between northwestern Australia and Indonesia, changing the volume of upper layer water stored there. Associated with EOF 2, a sharp peak in westward transport developed during May to October 1994.
THE CLOUDY FUTURE OF GOVERNMENT IT: CLOUD COMPUTING AND THE PUBLIC SECTOR AROUND THE WORLD

Cloud computing is fast creating a revolution in the way information technology is used and procured by organizations and by individuals. In this article, we examine what cloud computing is and the importance of this new model of computing. We then examine non-military uses of cloud computing in governments across the globe, from the Unites States to Europe and Asia. Then, we look at the resource – people and computing – issues involved in shirting to cloud computing. The author then presents his six-step “Cloud Migration Strategy” for governmental agencies to shift to cloud computing. Finally, we look “over the horizon” to the implications for public sector organizations and the information technology community as the cloud computing revolution progresses.