Miracle-dz/UniFAR-FTUs huggingface dataset:
Real-Time FPGA-Based Digital Signal Processing and Correction for a Small Animal PET

The small animal positron emission tomography (PET) is dedicated to small animal imaging, which requires high position and energy precision, as well as good flexibility and efficiency of the electronics. This paper presents the design of a digital signal processing logic for a marmoset brain PET system based on lutetium-yttrium oxyorthosilicate (LYSO) crystal arrays, SiPMs, and the resistive network readout method. We implement 32-channel signal processing in a single Xilinx Artix-7 Field-Programmable Gate Array (FPGA). The logic is designed to support four online modes which are regular data processing mode, flood map construction mode, energy spectrum construction mode, and raw data mode. Several functions are integrated, including 2-D) raw position calculation, crystal locating, events filtering, and synchronization detection. Furthermore, a series of online corrections is also integrated, such as photon peak correction to 511 keV and time measurement result correction with crystal granularity. A gigabit ethernet interface is utilized for data transfer, look-up tables (LUTs) configuration, and command issuing. The pipeline logic works at 125 MHz with a signal processing capability beyond the required data rate of 1 000 000 events/s/channel. A series of initial tests is conducted. The results indicate that the logic design meets the application requirement.
Mechanism of DNA Intercalation by Chloroquine Provides Insights into Toxicity

Chloroquine has been used as a potent antimalarial, anticancer drug, and prophylactic. While chloroquine is known to interact with DNA, the details of DNA–ligand interactions have remained unclear. Here we characterize chloroquine–double-stranded DNA binding with four complementary approaches, including optical tweezers, atomic force microscopy, duplex DNA melting measurements, and isothermal titration calorimetry. We show that chloroquine intercalates into double stranded DNA (dsDNA) with a KD ~ 200 µM, and this binding is entropically driven. We propose that chloroquine-induced dsDNA intercalation, which happens in the same concentration range as its observed toxic effects on cells, is responsible for the drug’s cytotoxicity.
On the Effects of Type II Left Censoring in Stable and Chaotic Compartmental Models for Infectious Diseases: Do Small Sample Estimates Survive Censoring?

In this paper, we discuss a selection of tools from dynamical systems and order statistics, which are most often utilized separately, and combine them into an algorithm to estimate the parameters of mathematical models for infectious diseases in the case of small sample sizes and left censoring, which is relevant in the case of rapidly evolving infectious diseases and remote populations. The proposed method relies on the analogy between survival functions and the dynamics of the susceptible compartment in SIR-type models, which are both monotone decreasing in time and are both determined by a dual variable: the hazard function in survival prediction and the number of infected people in SIR-type models. We illustrate the methodology in the case of a continuous model in the presence of noisy measurements with different distributions (Normal, Poisson, Negative Binomial) and in a discrete model, reminiscent of the Ricker map, which admits chaotic dynamics. This estimation procedure shows stable results in experiments based on a popular benchmark dataset for SIR-type models and small samples. This manuscript illustrates how classical theoretical statistical methods and dynamical systems can be merged in interesting ways to study problems ranging from more fundamental small sample situations to more complex infectious disease and survival models, with the potential that this tools can be applied in the presence of a large number of covariates and different types of censored data.
Microvascular Capillary and Precapillary Cardiovascular Disturbances Strongly Interact to Severely Affect Tissue Perfusion and Mitochondrial Function in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Evolving from the Post COVID-19 Syndrome

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a frequent, debilitating and still enigmatic disease. There is a broad overlap in the symptomatology of ME/CFS and the Post-COVID-19 Syndrome (PCS). A fraction of the PCS patients develop the full clinical picture of ME/CFS. New observations in microvessels and blood from patients suffering from PCS have appeared and include microclots and malformed pathological blood cells. Capillary blood flow is impaired not only by pathological blood components but also by prothrombotic changes in the vascular wall, endothelial dysfunction, and the expression of adhesion molecules in the capillaries. These disturbances can finally cause a low capillary flow and even capillary stasis. A low cardiac stroke volume due to hypovolemia and the inability of the capacitance vessels to adequately constrict to deliver the necessary cardiac preload generate an unfavorable low precapillary perfusion pressure. Furthermore, a predominance of vasoconstrictor over vasodilator influences exists, in which sympathetic hyperactivity and endothelial dysfunction play a strong role, causing the constriction of resistance vessels and of precapillary sphincters, which leads to a fall in capillary pressure behind the sphincters. The interaction of these two precapillary cardiovascular mechanisms causing a low capillary perfusion pressure is hemodynamically highly unfavorable in the presence of a primary capillary stasis, which is already caused by the pathological blood components and their interaction with the capillary wall, to severely impair organ perfusion. The detrimental coincidence of microcirculatory and precapillary cardiovascular disturbances may constitute the key disturbance of the Post-COVID-19 syndrome and finally lead to ME/CFS in predisposed patients because the interaction causes a particular kind of perfusion disturbance—capillary ischemia/reperfusion—which has a high potential of causing mitochondrial dysfunction by inducing sodium- and calcium-overload in skeletal muscles. The latter, in turn, worsens the vascular situation through the generation of reactive oxygen species to close a vicious cycle from which the patient can hardly escape.
Maternal dietary intake of fish and child neurodevelopment at 3 years: a nationwide birth cohort—The Japan Environment and Children's Study

Background Results on the association between fish intake during pregnancy and a reduction in neurodevelopmental delays in children have been inconsistent, with some reports finding an association and others finding none. Because neurodevelopmental delays are more pronounced at the age of 3 years, their association needs to be examined at this age. Methods After exclusion and multiple imputation from a dataset comprising 104,057 records from the Japan Environment and Children's Study, logistic regression analysis was conducted in quintiles to evaluate the association between maternal fish intake during pregnancy and child neurodevelopment at age 3 years in 91,909 mother–child pairs. The Food Frequency Questionnaire (FFQ), validated in the Japan Public Health Center-Based Prospective Study for the Next Generation, was used to assess maternal fish intake during pregnancy. The Ages and Stages Questionnaires-3 was used to assess children's neurodevelopment in five domains: communication, gross motor, fine motor, problem-solving, and personal-social. Results Consistently lower odds were found for the highest vs. lowest quintile for the domains of communication, fine motor, problem-solving, and personal-social but not gross motor skills, with adjusted odd ratios (95% confidence intervals) of 0.89 (0.80–0.998), 0.90 (0.83–0.97), 0.86 (0.80–0.94), 0.87 (0.77–0.98), and 1.04 (0.94–1.16), respectively. The trend for lower odds of symptoms of neurodevelopmental delays across quintiles of higher maternal fish intake were significant for fine motor, problem-solving, and personal-social but not communication or gross motor. Conclusions Fish consumption during pregnancy may be associated with a reduced risk of neurodevelopmental delay in 3-year-olds, particularly in the fine motor, problem-solving, and personal-social domains. Continued investigation after the age of 3 could further clarify the association.
Computerized ionospheric tomography based on geosynchronous SAR

Computerized ionospheric tomography (CIT) based on spaceborne synthetic aperture radar (SAR) is an emerging technique to construct the three‐dimensional (3‐D) image of ionosphere. The current studies are all based on the Low Earth Orbit synthetic aperture radar (LEO SAR) which is limited by long repeat period and small coverage. In this paper, a novel ionospheric 3‐D CIT technique based on geosynchronous SAR (GEO SAR) is put forward. First, several influences of complex atmospheric environment on GEO SAR focusing are detailedly analyzed, including background ionosphere and multiple scattering effects (induced by turbulent ionosphere), tropospheric effects, and random noises. Then the corresponding GEO SAR signal model is constructed with consideration of the temporal‐variant background ionosphere within the GEO SAR long integration time (typically 100 s to 1000 s level). Concurrently, an accurate total electron content (TEC) retrieval method based on GEO SAR data is put forward through subband division in range and subaperture division in azimuth, obtaining variant TEC value with respect to the azimuth time. The processing steps of GEO SAR CIT are given and discussed. Owing to the short repeat period and large coverage area, GEO SAR CIT has potentials of covering the specific space continuously and completely and resultantly has excellent real‐time performance. Finally, the TEC retrieval and GEO SAR CIT construction are performed by employing a numerical study based on the meteorological data. The feasibility and correctness of the proposed methods are verified.
A preliminary evaluation of lake morphometric traits influence on the maximum colonization depth of aquatic plants

Underwater light regime is widely considered the principal determinant of aquatic plant depth distribution. The majority of previous studies dealing with macrophytes in lakes have singled out Secchi disk transparency (SD) values as the key empirical proxy to explain the maximum depth of macrophyte colonization (Zc). Few studies have investigated the role played by lake morphometry in structuring macrophyte beds. Using a balanced dataset including 20 Italian lakes (10 shallow and 10 deep lakes), we analysed transparency and lake morphometric traits to investigate their possible effects on Zc. Our results demonstrate that lake area plays a significant role, and confirm a direct influence of SD values on Zc. Considering lakes with an equal degree of transparency, smaller lakes may yield a lower Zc than larger ones. Morphology has a great influence on lake ecological characteristics especially on water thermal conditions and mixing depth. Based on our data, we argue that the thermal stratification plays a non negligible role in explaining macrophytes zonation, due to its influence on macrophytes life cycles and phytoplankton vertical distribution. Therefore, the present data suggest the need to enhance and refine our knowledge about the relationship between aquatic plants distribution and lake thermal conditions to better model the response of macrophytes to climate change and eutrophication.
Comparative Analysis of Nutritional Values, Bioactive Compounds and Antinutrients in Tartary and Common Buckwheat Leaves

Among the millets grown in the Himalayan region of India, common and tartary buckwheat are the most cultivated species. Due to its extensive nutritional and antioxidant characteristics, buckwheat is attracting much interest, especially in producing nutrient-rich healthy foods. The objective of this study was to investigate nutritional values (protein, lysine, arginine and tryptophan content), bioactive compounds (total phenolic and flavonoid contents, antioxidant and rutin content) and antinutrients (phytate, tannin and oxalate) in tartary and common buckwheat leaves. Till now, very little information is available on the phytochemical constituents of buckwheat leaves as compared to the seeds. Common buckwheat leaves contain significantly (p < 0.05) more protein (22.21 ± 0.23 gm/100 g), lysine (12.41 ± 0.41 gm/ 100 g protein), arginine (6.61 ± 0.29 gm/100 g protein) and tryptophan (3.58 ± 0.36 gm/100 g protein) content then tartary buckwheat. There were relatively minor differences in the contents of amino acids. The results showed that the phenol (1768.16 ± 0.78 mg GAE/100 g), flavonoid (678.31 ± 0.27 mg QE/100 g), total antioxidant activity (52.89 ± 0.77 mg/100 g), rutin (11.32 ± 0.10 gm/100 gm), phytate (2.84 ± 0.07 gm/100 gm), tannin (2.76 ± 0.08 gm/100 gm), and oxalate (4.27 ± 0.03 gm/100 gm) content of the tartary buckwheat samples were significantly (p < 0.05) higher as compared to that of the common buckwheat leaves. On the basis of this study, it can be concluded that tartary buckwheat leaves are superior as green vegetables compared to common buckwheat for preventative nutrition.
Decentralization Is Good or Not? Defending Consensus in Ethereum 2.0

Proof-of-Stake (PoS) protocols are widely accepted as a viable substitute for the Proof-of-Work-based consensus, which is why recent blockchain-based cryptocurrencies and applications, most notably Ethereum 2.0, are using some variant of PoS as the basis for the consensus protocol. However, the implementation of PoS protocols in Ethereum 2.0 are not without its share of problems and vulnerabilities, especially with respect to the malicious behavior of validator nodes. In this paper, we first review the basic tenets of PoS protocols. We then discuss some of the recently described attacks on the Ethereum 2.0 consensus, and we also show that some of the design rationales adopted in PoS implementation—the decentralization of the voting process in particular—have, in actuality, enabled attacks that can be launched at a very low cost to the attacker. We also propose simple remedies that can reduce or eliminate the impact of those attacks and can evaluate the performance of the Ethereum 2.0 consensus when these remedies are applied.
Adaptation and validation of the west haven-yale multidimensional pain inventory for Pakistani population.

Objective To evaluate the adapted version of West Haven-Yale Multidimensional Pain Inventory for patients with chronic pain. METHODS The multiphase study was conducted from January to December 2021. The factorial structure of the Urdu version of West Haven-Yale Multidimensional Pain Inventory was evaluated on a sample of adult patients aged 18- 45 years with non-specific chronic pain, taken from public and private hospitals and clinics of Lahore, Pakistan. The Urdu version was then subjected to factor analysis, while Cronbach's alpha, composite reliability, convergent and discriminant validity of the scale were also calculated. Data was analysed using SPSS 24. RESULTS Of the 306 subjects, 204(66.7%) were females and 102(33.3%) were men. The overall mean age was 30.94+/-8.44 years. There were 166(54.2%) subjects who were married, and 137(44.8%) reported experiencing pain daily. The confirmatory factor analysis showed a 45-item structure for 12 sub-scales as the best fit. The statistics for the final model were observed as minimum discrepancy function by degrees of freedom divided was 1.69, root mean square error of approximation was 0.05, and standardised root mean square residual was 0.06. Comparative fit index value was 0.91 and Tucker-Lewis coefficient was 0.90. Cronbach's alpha reliability ranged between 0.68 and 0.89 for the subscales, while for the total scale, it was 0.72. Conclusion The Urdu version of West Haven-Yale Multidimensional Pain Inventory was found to be a reliable and valid tool for chronic pain assessment for patients in Pakistan.
Perceived behavioral traits as key determinants of entrepreneurial intention in higher education institutions

This article examines how a business school's environment encourages the formation of entrepreneurial intentions among its students. Building on insights from the theory of planned behaviour and the business event model, a structural equation model was applied on a sample of 283 Costa Rican university students. The main results of the study suggest that the entrepreneurial training provided by the business school contributes to improve students' entrepreneurial intentions. However, this effect develops through an indirect mechanism: that is, entrepreneurial training positively influences students’ attitudes toward entrepreneurship which, in turn, impact students’ perception on entrepreneurial self-efficacy. The proposed model rooted in cognitive frameworks allows business schools, and higher education institutions in general, to measure and evaluate the effectiveness of their entrepreneurial training programs in promoting entrepreneurial intentions.
Exploratory Architectures Analysis of Various Pre-trained Image Classification Models for Deep Learning

—The image classification is one of the significant applications in the area of Deep Learning (DL) with respective to various sectors. Different types of neural network architectures are available to perform the image classification and each of which produces the different accuracy. The dataset and the features used are influence the outcome of the model. The research community is working towards the generalized model at least to the domain specific. On this gesture the contemporary survey of various Deep Learning models is identified using knowledge information management methods to move further to provide optimal architecture and also to generalized Deep Learning model to classify images narrow down to the sector specific. The study systematically presents the different types of architecture, its variants, layers and parameters used for each version of Deep Learning model. Domain specific applications and limitations of the type of architecture are detailed. It helps the researchers to select appropriate Deep Learning architecture for specific sector.
The Fabrication of Polymer-Based Curcumin-Loaded Formulation as a Drug Delivery System: An Updated Review from 2017 to the Present

Turmeric contains curcumin, a naturally occurring compound with noted anti-inflammatory and antioxidant properties that may help fight cancer. Curcumin is readily available, nontoxic, and inexpensive. At high doses, it has minimal side effects, suggesting it is safe for human use. However, curcumin has extremely poor bioavailability and biodistribution, which further hamper its clinical applications. It is commonly administered through oral and transdermal routes in different forms, where the particle size is one of the most common barriers that decreases its absorption through biological membranes on the targeted sites and limits its clinical effectiveness. There are many studies ongoing to overcome this problem. All of this motivated us to conduct this review that discusses the fabrication of polymer-based curcumin-loaded formulation as an advanced drug delivery system and addresses different approaches to overcoming the existing barriers and improving its bioavailability and biodistribution to enhance the therapeutic effects against cancer and other diseases.
Effects of Different Treatments on Seed Germination and Breaking Seed Dormancy in Wild Luffa Species

Comprehending general combining ability (GCA) and specific combining ability (SCA) is pivotal in maize breeding for successful hybrid development. GCA signifies the overall genetic worth of a parent, while SCA demonstrates unique interactions between parents. In instances where GCA variances surpass SCA variances, early assessments become more effective, enabling the anticipation of superior hybrids based on parental GCA impacts. Assessing the combining ability of maize becomes increasingly crucial with escalating temperatures, which can adversely affect maize growth and crop yield. Research conducted in Prayagraj involved utilizing 7x7 half diallel crosses of maize initially developed during the Rabi 2022 season, followed by their subsequent planting in a randomized block design (RBD) during spring 2023. The primary aim of the study was to evaluate the general combining ability (GCA) and specific combining ability (SCA) effects exhibited by the parents and hybrids, respectively, in order to identify superior-performing parents and hybrids among them. The results showcased strong positive GCA in MILCT-145F (P7) and MILC-2050 (P6), while specific heat-tolerant hybrids, such as P7xP1, P6xP2 exhibited outstanding performance in grain yield and other associated traits.
Impact of Quality of Work Life on Employees' Commitment to Private Commercial Banks of Hetauda

The quality of work life (QWL) and employee commitment have been a subject of interest among managers and academicians for a long period to enhance organizational performance. Quality of work life is the quality of the relationship between employees and the total work environment, concern for the impact of work on individuals as well as on organisation effectiveness, and the idea of participation in organisational problem-solving and decision-making in concurrence with the ascertained importance of an employee’s role in the service exchange process. This present study attempts to test the relationship between the quality of work life and employee commitment in the commercial bank of Hetauda. The research is a cross-sectional field survey and correlational study. Among a total of 240 employees currently working in Hetauda, 150 employees were selected as the sample of the study in 2023. In order to fulfil the research objectives, the primary data were collected using structured questionnaires. Purposive sampling was used to collect data. Data were analyzed using both descriptive and inferential statistics tools as per the requirement to study the responses and findings were derived. The result of the study indicated that there was a positive correlation between the quality of work life (supervisor support, working conditions, professional development, adequate remuneration and work-life balance) and employee commitment (affective commitment, normative commitment and continuance commitment). The study concluded that there were theoretical and practical implications. Regression analysis showed that there was a significant impact of quality work life on employees (affective commitment, normative commitment and continuance commitments).