Miracle-dz/UniFAR-FTUs huggingface dataset:
Microbial quality of fish along with the Tilapia, African catfish and Sardinella artisanal value chains in Kpong and James Town, Ghana

Abstract. Aboagye E, Tano-Debrah K, Kunadu APH. 2018. Microbial quality of fish along with the Tilapia, African catfish and Sardinella artisanal value chains in Kpong and James Town, Ghana. Bonorowo Wetlands 10: 1-17. Fish from artisanal sources constitute the most critical animal protein in the Ghanaian diet. The availability and safety of fish on the Ghanaian market is, however now unpredictable owing to potential rapid microbial growth which results from high ambient temperatures and poor handling along the artisanal value chains. Little is know about the small-scale fish value chains as well as the food safety knowledge and processing practices of key stakeholders involved. This study aimed at mapping out the artisanal fish value chains of Tilapia (Oreochromis niloticus), African catfish (Clarias gariepinus) and sardinellas (Sardinella aurita), and assessing the food safety knowledge and handling practices of key stakeholders along the selected value chains. A survey using semi-structured questionnaires and involving 93 fishers, 40 retailers, 40 processors, and 120 consumers was carried out to investigate stakeholders’ knowledge and practices of food safety along the value chain. Samples of the selected fish species were taken along their respective value chains to test for the presence of safety indicators (Salmonella, Vibrio, and Listeria species), hygiene indicators (Staphylococcus aureus and Escherichia coli), and spoilage organisms (Pseudomonas spp. and Proteus spp.). The mean scores for food safety of retailers, processors, and consumers were found to be generally insufficient at 55%, 43%, and 67.3% respectively. The stakeholders also scored poorly in their handling practices with mean scores of 41.2%, 63.0% and 58.6% for fishers, processors, and consumers, respectively. Estimated fish losses were highest at the retailer and consumer stages of the value chain with reported injuries as high as 35 to 100%. Pathogens such as Clostridium perfringens, enteropathogenic Escherichia coli, Staphylococcus aureus, Listeria spp. And Aeromonas sobria were isolated from fresh and on processed ready-to-eat fish samples. Salmonella spp. and Vibrio spp. not detected on any of the samples tested. Mesophilic counts in the range of 7.96 ± 0.68 to 2.95 ± 0.23 log cfu/g reported from fresh fish samples, with similarly high fecal coliform counts averaging 3.11 log cfu/g. Processed fish samples had average total counts, fecal coliform counts, and yeasts and mold counts of 3.11, 2.27, and 2.45 log cfu/g respectively. Proteus vulgaris and Proteus mirabilis were the predominant spoilage organisms present in almost all the fresh fish samples. This study provided much-needed insight into the unsatisfactory safety and quality of artisanal fish on the Ghanaian market and the specific microorganisms associated with them along the value chain. It also established the link between the food safety knowledge and handling practices of stakeholders within the value chain, and the actual quality and safety of fish on the market.
Inferring the properties of the pterosaur wing membrane

Abstract The preservation of the wing membrane of pterosaurs is very poor and the available fossil evidence does not allow its properties to be reconstructed. In contrast, the fossil record for the wing bones is relatively good and the advent of CT scanning has made it possible to build high-fidelity structural models of the wing spar. The bending strength of the wing spar of a 6 m wingspan ornithocheirid pterosaur is used to infer the likely membrane tension. The tensions required to suppress aeroelastic flutter and to minimize ballooning of the membrane under flight loads are also estimated. All three estimates are of similar magnitude and imply that the membrane must have contained high-modulus material, supporting the view that the reinforcing aktinofibrils were keratinous.
The relationship between pregnancy stress and mental health of the pregnant women: the bidirectional chain mediation roles of mindfulness and peace of mind

Objective This study aimed to investigate the relationship between pregnancy stress and mental health of the pregnant women, employing a positive psychology perspective. Specifically, the study sought to explore how the two positive psychological qualities of mindfulness and peace of mind may serve as potential mediators in the association between pregnancy stress and mental health of the pregnant women. Methods Seven hundreds and thirteen pregnant women seeking care at the First Affiliated Hospital of Sun Yat-Sen University were included in this study. The participants completed a self-report demographic questionnaire, as well as several validated scales including the Pregnancy Pressure Scale (PPS), Mindful Attention Awareness Scale (MAAS), Peace of Mind Scale (PoMS), and Chinese Health Questionnaire (CHQ). The Amos 23.0 system was utilized to construct structural equation models. Results A total of 713 participants had an average age of 29.46 ± 4.81 years and an average gestational age of 24.26 ± 22.66 weeks. Out of the pregnant women, 163 (22.9%) experienced moderate or higher levels of pregnancy stress (PPS > 1), while 212 (29.7%) exhibited mental distress (CHQ > 3). Pregnancy stress exhibited a positive association with mental distress, while displaying negative associations with mindfulness and peace of mind. Mindfulness and peace of mind were negatively associated with mental distress. By employing structural equation modeling, the analysis revealed that mindfulness and peace of mind acted as partial mediators in the relationship between pregnancy stress and mental health. Furthermore, the identified models exhibited bidirectional sequential mediating pathways, suggesting that the pathways of mindfulness ↔ peace of mind mitigated the harmful influence of pregnancy stress on the mental health of pregnant women. Conclusion This study adds to the current body of knowledge by investigating the relationships among mindfulness, peace of mind, pregnancy stress, and mental health in pregnant women. From a positive psychology framework, it provides valuable understanding of the intricate dynamics between pregnancy stress and protective factors of mental health. Consequently, interventions aimed at bolstering positive psychological qualities in pregnant women should prioritize the cultivation of mindfulness to foster peace of mind, or alternatively, the cultivation of peace of mind to enhance mindfulness, ultimately leading to improved mental health outcomes.
Implementation of a Novel Multilevel Inverter Topology With Minimal Components—An Experimental Study

Voltage source inverters are currently gaining popularity in a variety of power system applications, including renewable energy, HVdc, and microgrid. Among all the renewable energy applications, multilevel inverters (MLIs) are the most popular converters for high- and medium-power industries. This article reviews and compares many of the recently developed topologies for renewable energy integration with energy storage systems (ESSs). In addition, a new design of a seven-level inverter is proposed. It utilizes only six power electronic switches in its design of which four have unidirectional voltage-blocking capability and two have bidirectional voltage-blocking capability. Various simulation results of the proposed topology along with the total harmonic distortion (THD) contents of voltage and current are presented in detail under different loading conditions. Afterward, a new factor of comparison is proposed in which component ratings are also considered. Finally, a hardware prototype is built to check the authenticity of the proposed design, and satisfactory results are presented.
The colonial origins of deforestation: an institutional analysis

ABSTRACT This paper investigates whether inherited colonial legacies influence deforestation rates in 60 former colonized developing countries. It is hypothesized that differences in deforestation among countries can be attributed to their colonial legacies shaping the current impact of the institutional background on deforestation. Overall, the author finds that institutions defined as the extent of democracy, the quality of property rights and the quality of government functioning (e.g., corruption), have a differential impact on deforestation rates according to colonial legacies as defined by the identity of the colonizer. More precisely, it is found that: (1) in countries characterized by ‘bad’ governance, former French colonies deforest relatively less than former British and Spanish colonies; whereas (2) in countries characterized by ‘good’ governance, the result is reversed. These results are robust when geography features are controlled for since the process of colonization was not random and depended on initial geographic and climatic conditions.
Outcome of eight working dogs with fibrotic myopathy following extracorporeal shockwave and rehabilitation therapy: a case series

Introduction Fibrotic myopathy of the gracilis, semitendinosus, and semimembranosus is described primarily in working German Shepherd dogs. The purpose of this case series is to describe the rehabilitation modalities and treatments utilized in working dogs with fibrotic myopathy and the time frame they were able to continue working. Methods Medical records of patients with hindlimb lameness that were presented to the Schwarzman Animal Medical Center in New York City from 2012 to 2023 were retrospectively searched. Signalment, history, clinical evaluation, gait analysis, goniometry of stifles, and follow-up evaluation were compared among patients. Ten male working dogs met inclusion criteria. Extracorporeal Shockwave Therapy (ECSWT) was administered under sedation or general anesthesia. Rehabilitation therapy (RT), including massage, hamstring stretch, photobiomodulation, pulsed electromagnetic field therapy, warm compress, therapeutic ultrasound, underwater treadmill, and therapeutic exercises, were performed once every one to 3 weeks with varying protocols according to patient assessments. Follow-up phone calls and emails were conducted to determine long-term outcome. Results On average, dogs were able to work full-time for 32.1 months (range 6–82; SD 23.6) from the time of diagnosis. No activity limitation was reported by the owners/handlers. Discussion This report is the first to describe non-invasive medical treatments that may extend the working ability of dogs diagnosed with fibrotic myopathy. Further prospective randomized controlled studies are needed to demonstrate the efficacy of ECSWT and RT for treating fibrotic myopathy. Conclusion The results of this retrospective study suggest that the combination of ECSWT and RT may allow working dogs with fibrotic myopathy to continue their working capacity for an extended period of time.
Characterization of a loss-of-function NSF attachment protein beta mutation in monozygotic triplets affected with epilepsy and autism using cortical neurons from proband-derived and CRISPR-corrected induced pluripotent stem cell lines

We investigated whether a homozygous recessive genetic variant of NSF attachment protein beta (NAPB) gene inherited by monozygotic triplets contributed to their phenotype of early-onset epilepsy and autism. Induced pluripotent stem cell (iPSC) lines were generated from all three probands and both parents. The NAPB genetic variation was corrected in iPSC lines from two probands by CRISPR/Cas9 gene editing. Cortical neurons were produced by directed, in vitro differentiation from all iPSC lines. These cell line-derived neurons enabled us to determine that the genetic variation in the probands causes exon skipping and complete absence of NAPB protein. Electrophysiological and transcriptomic comparisons of cortical neurons derived from parents and probands cell lines indicate that loss of NAPB function contributes to alterations in neuronal functions and likely contributed to the impaired neurodevelopment of the triplets.
On-Device Signal Quality Guided and Embedded Physiologic Information for High Fidelity Continuous PPG Compression

Photoplethysmography (PPG) is widely popularized in wearable gadgets for continuous health monitoring. The main challenge before the PPG-based measurements is motion artifact (MA) corruption, which often suppress vital physiological information like heart rate (HR) and respiratory rate (RR), which makes their extraction difficult and sometime erroneous. This work introduces a new approach of PPG multiclass signal quality assessment (SQA) using reservoir computing (RC) and tunable ${Q}$ -factor wavelet transform (TQWT) for PPG compression. To ensure the post compression clinical usage, HR and RR are embedded in the compressed bit stream, at every 10 s PPG frame. For the evaluation, a total of 200 records were utilized from three public datasets, namely, MIMIC II/III waveform, PPG RR benchmark (PRRB), BIDMC, and 20 volunteers at our laboratory, spanning a total duration of 7740 min. The technique showed good on-device (ARM v6 controller) performance on SQA (accuracy of 99.97%) and PPG compression (CR of 38.28 and percentage root mean squared difference (PRD) of 3.04 at 125 Hz sampling) using MIMIC data, which are competitive with published works. The low end-to-end latency (51 ms) and run time memory (19.99 kB) per 1 s PPG shows the usefulness for real-time deployment. It was also showed that embedding the physiologic information in compressed data may reduce the post compression processing error in RR and HR by an amount of 5.61% and 31.23% respectively in corrupted PPG. The proposed technique can be utilized in high fidelity PPG monitoring applications under ambulatory measurement.
Virtual Machine Placement for Minimizing Image Retrieval Cost and Communication Cost in Cloud Data Center

—In virtual machine (VM) deployment, the physical machine (PM) usually first retrieves VM image files from the central image server through block transfer, and the VM image retrieval and communication are the two main factors that consume network bandwidth resources, In this paper, we propose a heuristic-based algorithm to minimize both image retrieval cost and communication cost for VM placement in a fat-tree network. It consists of three phases: PM clustering, VM partitioning, 1) We first cluster the PMs based on the possible longest communication distance, which is estimated by a pre 2) To reduce the traffic between PM clusters, a semidefinite programming algorithm is used to place the coarsened VMs to PM Here coarsening means packing the resources of smaller VMs as a whole, so as to accelerate the solving process. 3) In each PM cluster, the VMs are mapped to PMs one by one, and the VMs with common blocks and communication traffic between each other are more likely to be placed together. Extensive simulations show that our algorithm is more effective and efficient than the state-of-the-art.
Light-Weight Low-Cost Drive Control Modules Design and Mass Production Research in SAR Satellites

In order to adapt to the development trend of light-weight and low-cost SAR (Synthetic Aperture Radar) satellites, products of drive control modules, especially drive control modules of SAR antenna deployment mechanism and solar array, are required to be light-weight and low-cost. At the level of product design, the mechanical structure of light-weight drive control module and low-cost hardware circuit design are given. The design scheme mainly involves the electromechanical integration interface of the drive control module and the drive mechanism, and the protection and reinforcement of the industrial components of the hardware circuit. At the level of product production, firstly, the product is designed according to modularization. Secondly, a series of standard systems from production to test are established. Finally, automatic production lines and automatic testing equipment are used for mass production and testing of products. The above design and production optimization measures reduce the weight and cost of drive control module products. The light-weight and low-cost drive control modules is conducive to carrying more payloads on SAR satellites and networking between satellites.
Identification of Putative Quantitative Trait Loci for Improved Seed Oil Quality in Peanuts

Improving seed oil quality in peanut (Arachis hypogaea) has long been an aim of breeding programs worldwide. The genetic resources to achieve this goal are limited. We used an advanced recombinant inbred line (RIL) population derived from JH5 × KX01-6 to explore quantitative trait loci (QTL) affecting peanut oil quality and their additive effects, epistatic effects, and QTL × environment interactions. Gas chromatography (GC) analysis suggested seven fatty acids components were obviously detected in both parents and analyzed in a follow-up QTL analysis. The major components, palmitic acid (C16:0), oleic acid (C18:1), and linoleic acid (C18:2), exhibited considerable phenotypic variation and fit the two major gene and minor gene mixed-inheritance model. Seventeen QTL explained 2.57–38.72% of the phenotypic variation in these major components, with LOD values of 4.12–37.56 in six environments, and thirty-five QTL explained 0.94–32.21% of the phenotypic variation, with LOD values of 5.99–150.38 in multiple environments. Sixteen of these QTL were detected in both individual and multiple environments. Among these, qFA_08_1 was a novel QTL with stable, valuable and major effect. Two other major-effect QTL, qFA_09_2 and qFA_19_3, share the same physical position as FAD2A and FAD2B, respectively. Eleven stable epistatic QTL involving nine loci explained 1.30–34.97% of the phenotypic variation, with epistatic effects ranging from 0.09 to 6.13. These QTL could be valuable for breeding varieties with improved oil quality.
An Improved Method for Digital Water Meter Reading Area Segmentation Based on U~2-Net

: With the continuous development of intelligent technology, the recognition of water meter readings has brought convenience to people's lives. By automatically reading water meter data, work efficiency can be improved. However, due to the varying shapes and sizes of the recognition areas, it is difficult to achieve good recognition results. Therefore, in response to the problem of varying sizes of water meter reading recognition areas, this paper proposes a method for digital water meter reading recognition area segmentation based on an improved U 2 -Net. Firstly, in terms of capturing data features, an improved Double-RSU module based on the RSU module is designed. This module increases depth and complexity compared to the original RSU module, thereby improving generalization and robustness. Secondly, in terms of model training, a combination of cross-entropy loss function, Jaccard coefficient and Dice loss function is used to comprehensively evaluate the entire model by considering binary classification, segmentation accuracy and segmentation area overlap. Experimental results show that the proposed method has good performance in MIoU, MAE and F1Score indicators, with the MIoU indicator increasing from 0.878 to 0.91, the MAE indicator increasing from 0.001 to 0.0009, and the F1Score indicator increasing from 0.9431 to 0.9455. These results indicate that the improved model has better performance compared to the original U 2 -Net model and can more accurately perform water meter reading area segmentation.
Electromagnetic Method for Detecting Black Piece on Monocrystalline Silicon Photovoltaic Panels

In the process of installation and application of a photovoltaic (PV) power generation system, damage and replacement of PV panels are inevitable. The black piece is one type of malfunction that indicates complete damage to the PV cell and failure in electricity generation. The intuitive impact is that it affects the power generation of PV panels. For PV power plants with a large number of PV panels, PV panels are connected in series and parallel to converters, the monitoring of PV panels is limited, and each PV panel is not equipped with sensors, but only at the terminal of converters. Once a problem arises, it needs to be investigated PV panel individually. In this research, an electromagnetic detection method for monocrystalline silicon PV panels is proposed. First, the electromagnetic signals of monocrystalline silicon PV cells are simulated, according to this signal, a coil sensor is designed to pick up electromagnetic signals. Then, an experimental platform is constructed indoors, and the PV cell is covered with black tape to simulate the black piece. The electromagnetic signals are obtained and analyzed, and it has been concluded that the signal frequency of the black piece is at least twice that of a normal PV cell. Finally, the real damaged PV panel is measured and compared with the electroluminescence (EL), thermal imaging, and current–voltage ( $I-V$ ) methods to verify the effectiveness of the proposed method.
Two long sedimentary records from Jersey, Channel Islands : Stratigraphic and pedological evidence for environmental change during the last 200 kyr

Examination of coastal cliff sections at Portelet and Belcroute on the south-west coast of Jersey, Channel Islands, has allowed the construction of a detailed sequence of environmental change extending back to the Late Middle Pleistocene. Recognition of two marine units in superposition suggests two temperate high sea-level phases in the Channel representing Stages 7 and 5. Detailed examination of soil micromorphology has allowed recognition of climatic fluctuations late in Stage 5 times which probably equate to Stages 5d to 5a. Comparison with equivalent successions in western France and southern England are proposed.
Social Recommender System Based on CNN Incorporating Tagging and Contextual Features

The Internet's rapid growth has led to information overload, necessitating recommender systems for personalized suggestions. While content-based and collaborative filtering have been successful, data sparsity remains a challenge. To address this, this article presents a novel social recommender system based on convolutional neural networks (SRSCNN). This approach integrates deep learning and contextual information to overcome data sparsity. The SRSCNN model incorporates user and item factors obtained from a neural network architecture, utilizing features from item titles and tags through a CNN. The authors conducted extensive experiments with the MovieLens 10M dataset, demonstrating that the SRSCNN approach outperforms state-of-the-art baselines. This improvement is evident in both rating prediction and ranking accuracy across recommendation lists of varying lengths.