Miracle-dz/UniFAR-FTUs huggingface dataset:
The Parmalat Scandal: An Analysis of Financial Deception and Its Implications for Global Business

The Parmalat scandal, often compared to Europe's Enron case, highlights one of the biggest financial frauds in global business history. Revealed in 2003, the case exposed an astonishing €14 billion deficit in the company's accounts, resulting from fraud, mismanagement, and oversight failures. This case study delves into the complexities of the Parmalat scandal, exploring its causes, impacts, and lessons for global businesses. It examines inadequate corporate governance, strategic missteps, auditing failures, and ethical violations, highlighting the importance of maintaining an ethical and transparent corporate culture. The role of auditing is emphasized, pointing out deficiencies in both internal and external audits, and the need for stricter controls and a whistleblowing culture. Parmalat's strategic decisions are scrutinized to understand how they contributed to the company's decline. The problematic relationship between majority and minority shareholders is discussed, revealing internal conflicts. The response to the scandal included a push for better corporate governance standards, regulatory reforms, and the adoption of more robust governance models. The importance of an ethical corporate culture, financial transparency, and the empowerment of whistleblowers are underscored as essential for preventing future frauds. The Parmalat case serves as a warning of the need for transparent and ethical practices in business, reinforcing that profitability should not override ethical considerations. This study provides a blueprint for companies to avoid similar pitfalls, highlighting corporate governance, business ethics, and oversight as pillars for trust and economic stability.
Capsule-Networks: Towards Object-Detection Capsule Object-Detector (COD)

—Although Convolutional Neural Networks performed better in object detection, CNNs does not care about spatial relationships existing in an image. In this paper, we try describe "capsule network based object detection" model COD based on the VGG16 model (as a base network), which presents a substantial result in many sections of object detection over Convolution Neural Network based model by achieving the problem of spatial relationships. We used matrix capsules and dynamic EM routing to classify object from different viewpoints. The whole model is grounded on "dynamic routing between capsules", which is suggested by Geoffrey E Hinton. Both proposed theories use capsules that maps feature properties of an object as information for detecting that object which is extracted by capsules and Dynamic routing groups the capsules of lower level into parent level capsules by an iterative dynamic routing process. We train and test our model on Pascal VOC 2007 and dataset. We implement this in python using Keras (Tensorflow as backend) and train our model in Google cloud compute engine. COD achieves an accuracy of 67.3 mAP on Pascal VOC-2007 dataset and performing a comparable performance with Fast R-CNN.
Locally Synthetized 17-β-Estradiol Reverses Amyloid-β-42-Induced Hippocampal Long-Term Potentiation Deficits

Amyloid beta 1-42 (Aβ42) aggregates acutely impair hippocampal long-term potentiation (LTP) of synaptic transmission, and 17β-estradiol is crucial for hippocampal LTP. We tested whether boosting the synthesis of neural-derived 17β-estradiol (nE2) saves hippocampal LTP by the neurotoxic action of Aβ42. Electrophysiological recordings were performed to measure dentate gyrus (DG) LTP in rat hippocampal slices. Using a pharmacological approach, we tested the ability of nE2 to counteract the LTP impairment caused by acute exposure to soluble Aβ42 aggregates. nE2 was found to be required for LTP in DG under physiological conditions. Blockade of steroid 5α-reductase with finasteride, by increasing nE2 synthesis from testosterone (T), completely recovered LTP in slices treated with soluble Aβ42 aggregates. Modulation of the glutamate N-methyl-D aspartate receptor (NMDAR) by memantine effectively rescued the LTP deficit observed in slices exposed to Aβ42, and memantine prevented LTP reduction observed under the blocking of nE2 synthesis. nE2 is able to counteract Aβ42-induced synaptic dysfunction. This effect depends on a rapid, non-genomic mechanism of action of nE2, which may share a common pathway with glutamate NMDAR signaling.
Application of deep brain stimulation for the treatment of childhood-onset dystonia in patients with MEPAN syndrome

Introduction Mitochondrial Enoyl CoA Reductase Protein-Associated Neurodegeneration (MEPAN) syndrome is a rare inherited metabolic condition caused by MECR gene mutations. This gene encodes a protein essential for fatty acid synthesis, and defects cause progressively worsening childhood-onset dystonia, optic atrophy, and basal ganglia abnormalities. Deep brain stimulation (DBS) has shown mixed improvement in other childhood-onset dystonia conditions. To the best of our knowledge, DBS has not been investigated as a treatment for dystonia in patients with MEPAN syndrome. Methods Two children with MEPAN were identified as possible DBS candidates due to severe generalized dystonia unresponsive to pharmacotherapy. Temporary depth electrodes were placed in six locations bilaterally and tested during a 6-day hospitalization to determine the best locations for permanent electrode placement. The Burke-Fahn-Marsden Dystonia Rating Scale (BFMDRS) and Barry-Albright Dystonia Scale (BADS) were used for preoperative and postoperative testing to quantitatively assess dystonia severity changes. Patient 1 had permanent electrodes placed at the globus pallidus internus (GPi) and pedunculopontine nucleus (PPN). Patient 2 had permanent electrodes placed at the GPi and ventralis intermedius nucleus of the thalamus (VIM). Results Both patients successfully underwent DBS placement with no perioperative complications and significant improvement in their BFMDRS score. Patient 2 also demonstrated improvement in the BADS. Discussion We demonstrated a novel application of DBS in MEPAN syndrome patients with childhood-onset dystonia. These patients showed clinically significant improvements in dystonia following DBS, indicating that DBS can be considered for dystonia in patients with rare metabolic disorders that currently have no other proven treatment options.
Discrete Morse theory for random complexes

The main objects considered in the present work are simplicial and CW-complexes with vertices forming a random point cloud. In particular, we consider a Poisson point process in R^n and study Delaunay and Voronoi complexes of the first and higher orders and weighted Delaunay complexes obtained as sections of Delaunay complexes, as well as the Cech complex. Further, we examine theDelaunay complex of a Poisson point process on the sphere S^n, as well as of a uniform point cloud, which is equivalent to the convex hull, providing a connection to the theory of random polytopes. Each of the complexes in question can be endowed with a radius function, which maps its cells to the radii of appropriately chosen circumspheres, called the radius of the cell. Applying and developing discrete Morse theory for these functions, joining it together with probabilistic and sometimes analytic machinery, and developing several integral geometric tools, we aim at getting the distributions of circumradii of typical cells. For all considered complexes, we are able to generalize and obtain up to constants the distribution of radii of typical intervals of all types. In low dimensions the constants can be computed explicitly, thus providing the explicit expressions for the expected numbers of cells. In particular, it allows to find the expected density of simplices of every dimension for a Poisson point process in R^4, whereas the result for R^3 was known already in 1970's.
Open ocean underwater wireless optical communication: chlorophyll and depth dependent variation in attenuation

Underwater wireless optical communication (UWOC) is attracting more research interest as a result of increased interaction of human with underwater world. UWOC technology is expected to play a prominent role in the study of marine biology, ocean environment, prediction of natural disasters, and discovery of natural resources, surveillance and monitoring of deep sea oil. All of this requires exchange of information and communication between divers, ships, remotely operated vehicles and autonomous underwater vehicles. However, the optical waves for underwater communication are faced with some practical challenges. Study research shows that optical waves are rapidly absorbed in water, suspending particles and planktons, indirectly cause significant optical scattering which results to attenuation of optical transmitted signal. Hence there is a need to study how ocean composition affects the attenuation of optical composition in Deep Ocean and how chlorophyll profiles are used to determine regions with high attenuation. Most studies have considered the attenuation to be constant in Deep Ocean irrespective of depth. This project takes a look at the depth dependent optical attenuation in underwater wireless communication for wavelength ranging from (400-700 nm) and at different depth from 0-250 m based on chlorophyll concentration profile (S1-S9). In order to achieve this, a graphic user interface was designed using Matlab to simulate the optical attenuation for different wavelength and varying depths. The 3D Matlab simulation results show how the attenuation of light in Open Ocean can be determined using surface chlorophyll profile S1-S9. The depths where high optical attenuation exists in the ocean are shown to be regions with deep chlorophyll maximum (DCM). The results shows DCM regions for S1, S2, S3, S4, S5, S6, S7, S8, and S9 are 110, 90, 80, 60, 50, 30, 20, 15, 10 m respectively. This DCM region shows low specific chlorophyll absorption coefficients and high optical attenuations. The results also show that attenuation coefficient for under water optical communication systems vary with depth.
Ichthyosis Skin Changes in a Patient With Hereditary Hemochromatosis

Hereditary hemochromatosis (HH) is characterized by elevated iron absorption in the body, leading to iron accumulation with subsequent dysfunction and end-organ damage. While the progression of the disease can result in arthralgias, hepatomegaly, cardiomyopathies, and diabetes, over a third of HH patients present with cutaneous manifestations. We present the case of a 56-year-old male with HH who presented to dermatology with a rash and diffuse scaling. The patient exhibited brown plate-like scales clinically consistent with diffuse ichthyosis vulgaris. While ichthyosis has been seen in patients with idiopathic hemochromatosis, its association with HH is not well reported. Due to the high prevalence of cutaneous involvement in hereditary hemochromatosis, physicians should familiarize themselves with ichthyosis and the other dermatologic manifestations of this disease.
Elevated dust deposition in Tierra del Fuego (Chile) resulting from Neoglacial Darwin Cordillera glacier fluctuations

Atmospheric mineral dust is intrinsically linked with climate. Although dust flux variability on glacial–interglacial timescales is well documented, Holocene dust records remain scarce. To fill this gap, we conducted elemental, isotopic and sedimentological analyses on a peat core from the Karukinka Natural Park in Tierra del Fuego. An 8000‐year‐old mineral dust record was extracted indicating three periods of elevated dust deposition: (i) 8.1–7.4 cal ka BP, (ii) 4.2 cal ka BP and (iii) 2.4–1.4 cal ka BP. The two oldest peaks are related to volcanic eruptions of the Hudson and Monte Burney volcanoes, respectively. The most recent dust peak, however, has a rare earth element and neodymium isotopic composition that resembles the geochemical signature of outwash plain sediments from the Darwin Cordillera. Since the timing of this dust peak corresponds to a period of glacier retreat between Neoglacial advances III and IV, we infer that Holocene aeolian dust fluxes in southern Patagonia are mostly driven by glacial sediment availability. Our results underline the important role of glaciers in producing aeolian dust in high‐latitude regions, and they imply that the current retreat of glaciers worldwide may result in elevated atmospheric dust loads.
Evaluating the Knowledge, Attitudes, and Practices of Saudi Arabian Parents Regarding Red Flags in Developmental Milestones

Background Parents serve a fundamental role in monitoring developmental milestones and identifying potential delays during early childhood, enabling timely interventions. However, previous studies in Saudi Arabia have shown limited awareness among parents regarding age-specific norms and red flags across developmental domains. This knowledge gap can severely impact the detection and management of abnormalities. Hence, a comprehensive understanding of Saudi parental knowledge, attitudes, and practices concerning childhood developmental trajectories is imperative. Methodology This cross-sectional study assessed developmental milestone awareness, beliefs, and behaviors among Saudi parents. A sample of 1,052 parents completed a validated 38-item questionnaire covering knowledge, attitudes, practices, and demographics. Knowledge was assessed across developmental domains using 22 multiple-choice questions, with scores categorized as excellent (≥75%), good (50%-75%), fair (40%-50%), or poor (≤39%). Attitudes and practices were captured on five-point Likert scales. Descriptive and chi-square analyses were conducted using IBM SPSS Statistics for Windows, Version 28.0 (IBM Corp., Armonk, NY). Results The majority of participants were females (844, 80.2%), with a mean age of 38.8 years. Serious knowledge inadequacies existed regarding developmental timelines across domains, especially motor milestones like crawling (93, 29.4% correct), sitting unsupported (45, 27.6%), pointing at objects (278, 26.4%), and responding to names (440, 41.8%). Overall, 2 (0.2%) participants showed excellent and 281 (26.7%) showed good understanding, while 490 (46.6%) had poor knowledge. Significant sociodemographic variations were observed, with women and experienced parents demonstrating greater awareness (P < 0.001). Despite knowledge gaps, 542 (51.5%) actively sought developmental information themselves, and over 50% trusted pediatric guidance. Most participants expressed a willingness to undergo screenings if risk factors existed and reported spending a considerable amount of daily interaction time with their children, focusing on developmental needs. Conclusions Critical developmental milestone knowledge shortfalls and selective attitudes persist among Saudi parents, warranting public education and physician-parent communication that enhance interventions to enable impactful developmental monitoring and prompt responses to abnormalities in a timely manner.
Identifying University Cash Flow Pattern Recognition: A Data Clustering Approach

The fast-developing Chinese higher education and research institutions are faced with more and more serious challenges in their financial regulation. Traditional accounting approaches may fail to distill useful decision-making suggestions confronted with the multi-species and huge-quantity financial “big data”. To reveal valuable information, this research focuses on the pattern recognition of the funding flows in 76 universities under Chinese Ministry of Education. Given the trend feature of the data series detected by the Mann-Kendall Non-Parameter Ranking Test, the low-frequency parts of the funding flows are distilled with wavelet transform to represent their basic features. Results show a clear hierarchy structure in the investments and expenses of universities according to their “titles” and advantage disciplines. Specifically, the comprehensive universities fall to different categories according to their “titles”, while the professional universities are classified according to their disciplines. The scientific and technical focused universities show larger variance among different categories than other specific discipline focused universities.
Effects of nutrients and water level fluctuation on wetland plants.

Nutrient elements are necessary for the sustainability of environment,while excessive nutrients have potential impacts on the stability of wetland ecosystem,especially on the dynamics of wetland plant communities.The nutrients in wetland habitat decide the growth of its plants,and the dominant species and their richness of plant communities.Accumulation of nutrients has significant effects on the primary productivity,biomass and its allocation,and species diversity of wetland plants.Water is the key factor in wetland system,and the fluctuation of water level affects wetland structure and characteristics.Species composition,species diversity,and plant community succession all show significant responses to moisture content and water level fluctuation in wetland.Nutrients and water level fluctuation are the important factors determining the composition,structure,and function of wetland ecosystem.Some research proposals in the future were put forward in the paper.
Data-Driven Modeling of Frequency Dynamics Observed in Operating Microgrids: A South African University Campus Case Study

South Africa has been experiencing an energy crisis since 2007. Utility loadshedding became the main control for under-frequency events due to a mismatch in generation and consumption. Rolling blackouts are further supported by failing electrical infrastructure and illegal (non-metered) connections to the distribution network. A common remedy to mandatory South African loadshedding, from the perspective of university campuses, is to deploy hybrid photovoltaic-diesel (PV-diesel) microgrids that allow for an uninterrupted power supply for a few hours. Campus microgrids are typically smaller compared to national utilities (less inertia) and require sensitive control schemes to remain stable. In this paper, frequency recordings associated with the operating microgrid of the University of the Free State QwaQwa campus are analysed. A simplistic stochastic mathematical model is presented as a model describing the observed frequency dynamics, describing the transition between the utility grid and the microgrid state, the microgrid frequency controller response, and the influence of the PV generators. Moreover, inter-campus synchronous frequency measurements are showcased and the future implications thereof are discussed. The main contributions of this paper focus on the recording and modelling of the frequency dynamics of fully functioning campus microgrids, and the showcasing of continuous synchronous measurements of frequency at two different campuses.
Does Smoking Fool You? The Smoking Habits Influence on the Cognitive Abilities of Indonesians

This study aims to analyze the influence of smoking habits on adolescents' cognitive abilities. The data used in this research is cross-section data from the Indonesia Family Life Survey batch 5 2014. The high rate of cigarette consumption for the age range 15 years and over in Indonesia has become a very serious concern. The smoking habit has many negative impacts on human brain development which in the long term will affect the quality of human resources in Indonesia. by exploring IFLS 2014 data, we found 6,908 teenage respondents who smoke. This figure is quite large, reaching 8% of all respondents. This research uses logistic regression analysis to see the impact of the independent variable on the dependent variable. The research results show that together smoking habits, education, history of hypertension, sleep quality and age have a significant effect on a person's cognitive abilities. Partially, smoking habits, history of hypertension, and age have a significant negative effect on a person's cognitive abilities. Meanwhile, education and sleep quality have a significant positive effect on a person's cognitive abilities. Gender partially has no effect on cognitive abilities.
Research on a Fault Diagnosis Method for Crankshafts Based on Improved Multi-Scale Permutation Entropy

As the crucial part of a transmission assembly, the monitoring of the status of the crankshaft is essential for the normal working of a reciprocating machinery system. In consideration of the interaction between crankshaft system components, the fault vibration feature is typically non-stationary and nonlinear, and the single-scale feature extraction method cannot adequately assess the fault features, therefore a novel impact feature extraction method based on genetic algorithms to optimize multi-scale permutation entropy is proposed. Compared with other traditional feature extraction methods, the proposed method illustrates good robustness and high adaptability in the signal processing of crankshaft vibrations. Firstly, the improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) method is developed on the signal to obtain several intrinsic mode function (IMF) components, and the IMF components with a large kurtosis are selected for array reorganization. Then, the parameters of multi-scale permutation entropy (MPE) are optimized based on genetic algorithm (GA), the multi-scale permutation entropy is calculated and the feature vector set is constructed. The feature vector set is input into the support vector machine (SVM) and optimized by a particle swarm optimization (PSO) model for training and final pattern recognition, where the Variational Mode Decomposition(VMD)-GA-MPE with a PSO-SVM recognition model and the ICEEMDAN-MPE with PSO-SVM recognition model without GA optimization are constructed for a comparison with the proposed method. The research result illustrates that the proposed method, which inputs the genetic algorithm optimized multi-scale permutation entropy extracted from the ICEEMDAN decomposition into the PSO-SVM, performs well in impact feature extraction and the pattern recognition of crankshaft vibrations.
Bilateral versus unilateral upper limb training in (sub)acute stroke: A systematic and meta-analysis

Background Integrating high dosage bilateral movements to improve upper limb (UL) recovery after stroke is a rehabilitation strategy that could potentially improve bimanual activities. Objectives This study aims to compare the effects of bilateral with unilateral UL training on upper limb impairments and functional independence in (sub)acute stroke. Method Five electronic databases (PubMed, Scopus, PEDro, ScienceDirect, Web of Science) were systematically searched from inception to June 2023. Randomised controlled trials comparing the effect of bilateral training to unilateral training in stroke survivors (< 6 months poststroke) were included. The treatment effect was computed by the standard mean differences (SMDs). Results The review included 14 studies involving 706 participants. Bilateral training yielded a significant improvement on UL impairments measured by FMA-UE compared to unilateral training (SMD = 0.48; 95% CI: 0.08 to 0.88; P = 0.02). In addition, subgroup analysis based on the severity of UL impairments reported significant results in favour of bilateral UL training in improving UL impairments compared to unilateral training in “no motor capacity” patients (SMD = 0.66; 95% CI: 0.16 to 1.15; P = 0.009). Furthermore, a significant difference was observed in favour of bilateral UL training compared to unilateral UL training on daily activities measured by Functional Independence Measure (SMD = 0.45; 0.13 to 0.78; P = 0.006). Conclusion Bilateral UL training was superior to unilateral training in improving impairments measured by FMA-UE and functional independence in daily activities measured by Functional Independence Measure in (sub)acute stroke. Clinical implications Bilateral upper limb training promotes recovery of impairments and daily activities in (sub)acute phase of stroke.