Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploring the Challenges of Diagnosing Thyroid Disease with Imbalanced Data and Machine Learning: A Systematic Literature Review

Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid disease predictions. A systematic literature review (SLR) strategy is used in this study to give a comprehensive overview of the existing literature on forecasting data on thyroid disease diagnosed using ML. This study includes 168 articles published between 2013 and 2022, gathered from high-quality journals and applied meta-analysis. The thyroid disease diagnoses (TDD) category, techniques, applications, and solutions were among the many elements considered and researched when reviewing the 41 articles of cited literature used in this research. According to our SLR, the current technique's actual application and efficacy are constrained by several outstanding issues associated with imbalance. In TDD, the technique of ML increases data-driven decision-making. In the Meta-analysis, 168 documents have been processed, and 41 documents on TDD are included for observation analysis. The limits of ML that are discussed in the discussion sections may guide the direction of future research. Regardless, this study predicts that ML-based thyroid disease detection with imbalanced data and other novel approaches may reveal numerous unrealised possibilities in the future
An evaluation of likelihood-based bandwidth selectors for spatial and spatiotemporal kernel estimates

ABSTRACT Spatial point pattern data sets are commonplace in a variety of different research disciplines. The use of kernel methods to smooth such data is a flexible way to explore spatial trends and make inference about underlying processes without, or perhaps prior to, the design and fitting of more intricate semiparametric or parametric models to quantify specific effects. The long-standing issue of ‘optimal’ data-driven bandwidth selection is complicated in these settings by issues such as high heterogeneity in observed patterns and the need to consider edge correction factors. We scrutinize bandwidth selectors built on leave-one-out cross-validation approximation to likelihood functions. A key outcome relates to previously unconsidered adaptive smoothing regimens for spatiotemporal density and multitype conditional probability surface estimation, whereby we propose a novel simultaneous pilot-global selection strategy. Motivated by applications in epidemiology, the results of both simulated and real-world analyses suggest this strategy to be largely preferable to classical fixed-bandwidth estimation for such data.
Dermatoporosis in Upper Limbs Treated With Polymethylmethacrylate Microspheres Using the BioSculpt® Technique

Dermatoporosis is a syndrome of fragility or chronic cutaneous insufficiency. It presents with localized violaceous spots on the extensor face of the upper limbs of older people, with signs such as senile purpura, actinic purpura, or Bateman purpura, in addition to atrophy of the skin and subcutaneous tissue. These lesions can be painful and a source of morbidity. We report a case of an 80-year-old patient presented for the treatment of dermatoporosis in the upper limbs with polymethylmethacrylate (PMMA) using the BioSculpt®technique. The photographic and ultrasonographic clinical responses of the soft tissue were evaluated before and after nine months of treatment.
Agility and Resilience as antecedents of Supply Chain Performance under moderating effects of Organizational Culture within Humanitarian Setting: A Dynamic Capability View

This study examines the effects of supply chain agility and supply chain resilience on performance under the moderating effect of organizational culture. We have used the dynamic capability view to conceptualize our theoretical models for different phases of humanitarian supply chain (pre-disaster and post-disaster phases). These phases do not have clear boundaries, but overlap chronologically, as well as in terms of ongoing activities. We used partial least squares (PLS) to examine our proposed research hypotheses using 335 responses gathered from organizations in India using survey based questionnaires designed for a single respondent. The results from our data suggest that SCAG and SCRES are two important dynamic capabilities of supply chain, have significant effects on pre-disaster performance (PRE-DP). Moreover, the control orientation does not have significant effect on the path joining SCAG and PRE-DP. However, the control orientation has a significant interaction effect on the path joining SCRES and PRE-DP. Similarly, SCRES has significant effect on post-disaster performance (POST-DP) but SCAG has no significant effect on POST-DP. In contrast to control orientation, the flexible orientation has significant moderation effects on the paths SCAG/SCRES and POST-DP. These findings contribute to our understanding of differential effect of SCAG/SCRES on supply chain performance in different phases under different contexts within the humanitarian setting. The results provide further understanding to practitioners who often struggle to develop appropriate strategies for different phases. Finally, we have noted some limitations of our study and further research opportunities.
A Real-Time and Hardware-Efficient Processor for Skeleton-Based Action Recognition With Lightweight Convolutional Neural Network

Skeleton-based human action recognition (HAR) has been extensively studied these years because body skeleton has the simple but informative representation of human action, which greatly reduces the computation complexity compared with the image-based HAR. As a result, it is suitable for low power implementation in embedded platforms. In this brief, we present a systematic approach to developing a hardware-efficient and low-power processor for real-time skeleton-based HAR. First, a lightweight HAR algorithm only using the one-dimensional convolutional neural network (1D-CNN) is proposed. Second, the singular value decomposition is employed to compress the weights in the fully connected (FC) layers of the proposed convolutional neural network. Third, a hardware processor implementing the proposed algorithm is presented. Aimed at optimizing area and energy, this processor utilizes a flexible structure supporting different kernel sizes of the 1D-CNN and reuses hardware in both convolution layers and FC layers. The proposed processor is implemented under SMIC 65-nm CMOS technology and consumes a total area of 1.016 mm2. Experimental results show that the proposed processor can achieve state-of-the-art classification accuracy in NTU RGB+D dataset and SBU dataset while outperforming previous solutions in area and energy efficiency.
There are many barriers to species' migrations

Temperature-change trajectories are being used to identify the geographic barriers and ther- mal 'cul-de-sacs' that will limit the ability of many species to track climate change by migrating. We ar- gue that there are many other potential barriers to species' migrations. These include stable ecotones, discordant shifts in climatic variables, human land use, and species' limited dispersal abilities. To illus- trate our argument, for each 0.5° latitude/longitude grid cell of the Earth's land surface, we mapped and tallied the number of cells for which future (2060-2080) climate represents an analog of the focal cell's current climate. We compared results when only considering temperature with those for which both temperature and total annual precipitation were considered in concert. We also compared results when accounting for only geographic barriers (no cross-continental migration) with those involving both geo- graphic and potential ecological barriers (no cross-biome migration). As expected, the number of future climate analogs available to each pixel decreased markedly with each added layer of complexity (e.g. the proportion of the Earth's land surface without any available future climate analogs increased from 3% to more than 36% with the inclusion of precipitation and ecological boundaries). While including additional variables can increase model complexity and uncertainty, we must strive to incorporate the factors that we know will limit species' ranges and migrations if we hope to predict the effects of climate change at a high-enough degree of accuracy to guide management decisions.
Impact of alkaloids extract of Moringa olievera Lam. leaves on the development, fertility and demography of the southern cowpea beetle insect Callosobruchus maculatus (F.) (Coleoptera: Bruchidae)

The Southern Cowpea Beetle Callosobruchus maculatus (F.) is one of the most widespread insect pests of stored legumes, causing a considerable loss during storage, decreasing the net weight of the crops, and resulting in reduced the quality of the crops. This study has been conducted to determine the lifetime, fertility and life table parameters of C. maculatus by using an alkaloids extract from Moringa oleifera leaves at different concentrations 1000, 2000, and 3000 ppm. The result was shown that the lowest survival rate was 49% at a concentration of 1000, 2000 ppm, as compared with the control which was 77%. The lowest reproductive rate (Ro) was 4.76 female/female/generation at the concentration of 1000 ppm, compared with the control which was 10.34 female/ female /generation while the lowest rate of egg hatching was 62% at the concentration of 3000 ppm as compared with the control 88%. Similarly, the sex ratio of male: to female was decreased after the use of the three concentrations, mostly at the concentration of 1000 ppm, in which the ratio was 1.31:0.69 compared to 1.11:0.89 for the control. Overall, the life tables curve shows that the survival rate, the ratio of the females and the productivity was affected in a negative way causing a decline in the whole insect population. It is clear from the above that the alkaloids extract of the leaves of the Moringa plant is effective and has an impact on the insect population, and can be an eco-friendly method of controlling on pest population.
Website Assessment and Feature Metrics of University's Website Accessibility: An Evaluation of 15 Top-Ranked Universities of India

Most Universities now use websites as their main source of information where students can interact and exchange their pertinent information. Web accessibility refers to the creation and design of websites, platforms, and tools for all people (abled/disabled). This study analyzes the usability of 15 of India's best universities as determined by Webometrics/QS Ranking 2023. Three key assessment tools—TAW, WAVE, and EIII—are customized for the website analysis. These tools show us the findings of a website's compliance with the WCAG 2.1 (Web Content Accessibility Guidelines). The assessment also identified a few recurring mistakes that could be fixed by simply including accessibility features. The total analysis's findings also emphasized the need for these sites' usability to be improved. The paper offers a list of errors that, if fixed, will benefit user groups with various disabilities, as well as useful recommendations for enhancing these websites' accessibility so that their intended audiences can access the information they provide without any hindrance.
Effect of Mass Shooting on Mental Health of Children and Adolescent

This article discusses the controversial issue of gun control and its impact on mass shootings and mental health, particularly on children and adolescents. The Second Amendment has led to an increase in improper use of firearms, with gun deaths increasing every year. The psychological effects of mass shootings, such as post-traumatic stress disorder, can have long-lasting impacts on children and adolescents. They may experience trauma, anxiety, fear, and social isolation. Witnessing such events can lead to difficulties in managing day-to-day activities and mental health problems. To support children and adolescents after a mass shooting, it is important to ensure that they feel safe and secure, increase security measures in schools and other public places, and provide counseling and therapy services to help them process their trauma and manage their anxiety and other mental health issues. Addressing gun violence is essential in preventing mass shootings from occurring and reducing their impact on young people's mental health.
Effect of incorporation of SnS nanorods on the growth mechanism, crystallinity, optoelectronic performance, and stability of CH3NH3PbI3 perovskite active layer

We present remarkable improvements in the structural, morphological, and optical properties of CH 3 NH 3 PbI 3 perovskite by introducing SnS. To achieve this, we prepared SnS powder hydrothermally at different SnCl 2 :Na 2 S molar concentrations. Rigorous analyses, including XRD, FTIR, SEM, and EDAX, confirmed the formation of a single-phase stoichiometric SnS. Furthermore, we deposited CH 3 NH 3 PbI 3 :SnS nanocomposite films on m-TiO 2 substrates using the slot-die method, varying the SnCl 2 :Na 2 S molar concentrations. The XRD analysis of CH 3 NH 3 PbI 3 :SnS nanocomposites indicated a notable enhancement in the crystallinity of CH 3 NH 3 PbI 3 , attributed to the incorporation of SnS in the film. In addition, optical microscopy and AFM observations revealed that the molar concentration ratio of SnCl 2 :Na 2 S significantly influenced the surface coverage of CH 3 NH 3 PbI 3 :SnS nanocomposites. By carefully optimizing the SnCl 2 :Na 2 S molar concentration ratio (MAPI:SR-2), we achieved a CH 3 NH 3 PbI 3 :SnS nanocomposite film with a minimal surface roughness of 192 nm, low Urbach energy of 169 meV, and an optimum band gap of 1.59 eV, as evidenced by UV-Visible and PL spectroscopy analyses. These exciting results demonstrate that incorporating SnS into CH 3 NH 3 PbI 3 perovskite holds excellent promise as a composite material for various optoelectronic applications. The improved properties offered by this nanocomposite can pave the way for developing more efficient and stable optoelectronic devices based on perovskite technology.
Pengaruh Strategi Bisnis, Metoda Pengembangan Sistem (System Development Life Cycle), Terhadap Kualitas Sistem Informasi Akuntansi (Survei Pada Pt Len Industri Persero-Bumn Industri Strategis di Indonesia)

Penelitian ini bertujuan untuk mengetahui besar pengaruh Strategi Bisnis, Metoda Pengembangan Sistem/System Development Life Cycle (SDLC) terhadap Kualitas Sistem Informasi Akuntansi dan dampaknya terhadap Kualitas Informasi Akuntansi pada PT Len Industri Persero. Fungsi sistem informasi akuntansi adalah untuk menyediakan informasi penting untuk mengurangi ketidakpastian, mendukung pengambilan keputusan, dan mendorong suatu perencanaan lebih baik, penjadwalan, dan pengendalian aktivitas pekerjaan. Sehingga strategi bisnis adalah suatu faktor penting di dalam implementasi sistem informasi akuntansi yang efektif. Penelitian ini menguji pengaruh strategi bisnis, metoda pengembangan sistem (SDLC) pada sukses tidaknya sistem informasi akuntansi dan dampaknya pada informasi akuntansi berkualitas. Penelitian ini menggunakan metoda descriptive dan jenis penelitian yang digunakan adalah verifikatif. Jenis data yang digunakan adalah primer menggunakan data primer menggunakan skala interval untuk pengukurannya. Uji validitas dan realibilitas dilakukan terhadap kuesioner yang telah terkumpul, selanjutnya data yang berskala ordinal dikonversi dalam skala interval kemudian menggunakan msi (measurement succsive interval). Analisis data dilakukan menggunakan SPSS 22. Hasil penelitian menunjukkan bahwa: 1) Strategi Bisnis pada PT Len Industri persero cukup baik, dalam memproses informasi, menyimpan, dan menyampaikan informasi akuntansi. 2) Metode Pengembangan Sistem (System Development Life Cycle) pada PT Len Industri persero kurang baik, proses metode pengembangan sistem yang didesain untuk memberikan keyakinan yang memadai belum efektif dan belum efisien. 3) Kualitas Sistem Informasi Akuntansi pada PT Len Industri persero masih kurang baik, belum adanya informasi akuntansi yang cepat, efisen, serta membantu dalam pengambilan keputusan, perencanaan dan pengendalian perusahaan. 4) Strategi Bisnis berpengaruh terhadap Kualitas Sistem Informasi Akuntansi. Sistem Informasi akuntansi belum sepenuhnya berkualitas karena strategi diferensiasi dalam inovasi dalam operasi, motivasi kerja karyawan dan pengembangan karyawan belum berjalan secara sempurna. 5) Metoda Pengembangan Sistem/System Development Life Cycle (SDLC) berpengaruh terhadap Kualitas Sistem Informasi Akuntansi. Sistem Informasi akuntansi belum sepenuhnya berkualitas karena perencanaan Implementasi dalam mengkomunikasikan implementasi Kualitas Sistem Informasi Akuntansi belum terjaga. 6) Strategi bisnis dan Metode Pengembangan Sistem (System Development Life Cycle) secara bersamaan berpengaruh terhadap Kualitas Sistem Informasi Akuntansi.
Determination of the optimal areas for medicinal and aromatic plants cultivation in Ukraine depending on water and heat supply

of Ukraine was sub-divided into the areas, which are the most suitable for cultivation of concrete medicinal and aromatic plants considering the biological requirements of the latter. Further, crop mapping was performed for visualization of the study results. The maps, created as a result of the study, have no analogues in Ukraine and are of great importance for reasonable allocation of the main production centres for each group of the studied plants. The study has both practical and scientific importance and will benefit to the development of medicinal and aromatic plants cultivation in Ukraine.
Chrysin a promising anticancer agent: recent perspectives

ABSTRACT Honey, propolis, and passionflower contain a flavone known as chrysin. Researchers are studying chrysin to prove its potential to stop cancer cells growth. Chrysin cancer therapeutic potential is of great interest and numerous studies have been done to illustrate this potential. It is associated protein pathways effectively suppress tumor growth within the body. It is shown to have the ability to kill breast, prostate, lung, liver, and stomach cancerous cells. It can block Phosphoinositide 3-kinase/protein kinase B/mammalian target of rapamycin (PI3K/AKT/mTOR) and Mitogen-activated protein kinase/extracellular signal-regulated kinase (MAPK/ERK) signaling in different animals against various cancers. Chrysin has the potential to kill breast cancer cells in a laboratory setting by inhibiting their cell division. Chrysin strongly suppresses Matrix metalloproteinase-9 (MMP-9), Urokinase plasminogen activator (uPA) and Vascular endothelial growth factor (VEGF), i.e. factors that can cause cancer. Chrysin has the ability to suppress the androgen receptor (AR), a protein necessary for prostate cancer development and metastasis. It starts the caspase cascade and blocks protein synthesis to kill lung cancer cells. Unnecessary apoptosis can be prevented by stopping certain protein pathways. Chrysin significantly decreased lung cancer metastasis in various animal-modeled studies. Chrysin induces apoptosis and stops colon cancer cells in the G2/M cell cycle phase. Chrysin suppresses colon cancer-promoting cyclin B1 and cyclin-dependent kinase 2. Chrysin suppressed cyclin B1 and CDK2 production in order to stop cancerous growth. Chrysin prevents tumor growth and cancer spread by blocking blood vessel expansion. Chrysin’s solubility, accessibility and bioavailability may limit its medical use. Chrysin targets numerous cancer-related communication pathways present in cells. Chrysin may reduce the chances of the onset of cancer, it can also serve as an alternative treatment as a whole to prevent and treat various cancers, but more clinical trials and research studies are needed to fully unlock its potential.
Investigation of the Effects of Atmospheric Attenuation and Frequency on MIMO Channel Capacity

The efficiencies of 5G channels, which are highly affected by atmospheric attenuation, are still being investigated. The effects of frequency and atmospheric attenuation parameters such as humidity, temperature, rain, and pressure were investigated in this study using the NYUSIM program. The spatial consistency mode of the NYUSIM channel simulator was turned off, and unnormalized channel capacities were calculated at 28, 45, 60, and 73 GHz frequencies. According to the research results, the rain rate was the atmospheric attenuation parameter that significantly affected MIMO channel capacity. In contrast, the humidity percentage had the slightest impact. The frequency where the channel capacity is most affected by the four determined atmospheric attenuation parameters is 60 GHz, while the frequency where it is least affected is 28 GHz. The study found that using frequencies with high atmospheric attenuation reduces communication efficiency significantly. Furthermore, rain rate has a significant impact on 5G channel performance.
Imaging nested-mirror assemblies – A new generation of neutron delivery systems?

A mirror system for neutron transport with high brilliance transfer from a source or a divergent beam to an instrument is presented. The assembly of nested short elliptical (or very short flat) mirrors located halfway between two common focal points M and M′ images cold neutrons by single reflections from an area around M onto an area of similar size at M′. An absorber on the straight line MM′ blocks the direct view onto the source, with little impact on the transported solid angle. The simple geometry with well-defined, non-grazing angles of reflection off the individual mirrors opens up versatile possibilities to tailor beam size, divergence, wavelength spectrum and polarization to experimental needs. A common small-wavelength cut-off of the transported spectrum can be set by proper choice of the m values of supermirrors. Monochromatic beams can be generated using bandpass supermirrors. Adjustable apertures far away from the instrument define the size and the divergence of the beam at the sample, thus keeping background radiations low. The absence of mirrors in the harsh radiation environment close to an intense source simplifies the maintenance of beam tubes and increases mirror lifetimes.
Age models for peat deposits on the basis of coupled lead-210 and radiocarbon data.

The study presents three examples of age-model construction based on the results of Pb and C dating methods applied to peat deposits. The three sites are ombrotrophic peat bogs: the Misten (Belgium), Slowinskie Bloto (N Poland) and Puscizna Mala (S Poland). All sites have been subjected to multiproxy studies aimed at reconstructing paleoenvironment and human activity, covering the last 1500, 1300 and 1800 years, respectively (De Vleeschouwer et al. 2009A, 2009B, in prep., Fialkiewicz-Koziel, ongoing PhD). A detailed comparison between Pb and postbomb C results in the Misten bog has also been carried out by Piotrowska et al. (2009). In all cores, the Pb activity was calculated using Po and Po activities after acid-extraction from bulk samples, subsequent deposition on silver discs and measurements by alpha spectrometry. Unsupported Pb was detected until 35cm in Slowinskie Bloto, 15cm in the Misten and 19cm in Puscizna Mala. Constant Rate of Supply (CRS) model was then applied to compute ages of each 1-cm core interval.