Miracle-dz/UniFAR-FTUs huggingface dataset:
Distribution of heavy metals (arsenic, cobalt, copper and zinc) composition and bacterial communities in sediments along tropical river east coast Malaysia

Sediment samples were collected from 19 sampling stations of Pahang River, east coast Malaysia to determine the concentration of arsenic (As), cobalt (Co), copper (Cu), zinc (Zn) and bacterial colony forming unit (CFU) distribution. Sampling was conducted during pre and post of North-East monsoon season for the years 2013 and 2022. Heavy metal concentrations were determined by using inductively coupled plasma mass spectrometry (ICP-MS). The concentration of heavy met- als was compared with the world average concentration of shale values. The dry weight concentration of As ranged between 4.387 ± 0.586 to 15.922 ± 8.738 µg·g –1 during pre-monsoon. While it was 3.989 ± 0.758 to 11.336 ± 6.748 µg·g –1 during post-monsoon. The range of dry weight concentration for Co was found between 1.730 ± 0.318 and 4.569 ± 0.586 µg·g –1 during pre-monsoon while 1.476 ± 0.063 and 4.620 ± 0.951 µg·g –1 during post-monsoon. The dry weight concentration of Cu ranged between 1.182 ± 0.510 to 10.722 ± 5.664 µg·g –1 and 0.900 ± 0.222 to 6.514 ± 3.749 µg·g –1 during pre-monsoon and post-monsoon, respectively. The range dry weight concentration for Zn was found between 7.964 ± 4.857 and 26.289 ± 2.636 µg·g –1 during pre-monsoon while 8.187 ± 3.010 and 28.347 ± 15.665 µg·g –1 during post-monsoon. The bacterial community in sediments along Pahang River was determined using culture-based method. The bacterial CFU range was found between 1526.67 ± 64.68 and 16146.67 ± 225.71 CFU/g during pre-monsoon while 1013.33 ± 38.51 and 28826.67 ± 418.47 CFU/g during post-monsoon. This study revealed that the concentration of heavy metals does not influ- ence the distribution of bacteria in the Pahang River sediments. Even though the concentrations of heavy metals studied are typically below reported toxic levels, ongoing monitoring of river ecosys- tems is an essential to safeguard this ecosystem and ensure that the pollution from heavy metals is under conducive condition throughout these increased industrialization and urbanization.
Analysis of Network Attached Storage Performance with NFS Protocol in Integrated Business Start-Up

The need for data storage due to individual and group computing work is increasing, so storage media with reliable capabilities and good performance are needed. The way that can be solution is shared storage, which is using one storage to be used together. One of the commonly used shared storage is NAS (Network Attached Storage). IBS (Integrated Business Start Up) uses NAS as a backup storage medium that will store important data that supports the performance of IBS services as a whole, so it is necessary to analyze to find out how the performance of the NAS system uses the NFS Protocol as the basis of the service. whereas in this study the focus of performance testing was carried out by looking at the results of measuring packet loss, throughput, CPU usage, and memory usage on the NAS server used. the performance level of the system used is running well, as seen from the results of the throughput test of 1.1 GB, packet loss of around 0%, CPU usage of 0.5%, and memory usage of 382.5Mb. The results of this performance test are also by Telecommunications standards and Internet Protocol Harmonization Through Networks
Analisis Sistem S-Commerce pada Tiktok Shop untuk Meningkatkan Daya Saing Menggunakan Metode SWOT

Internet telah menjadi teknologi yang banyak digunakan dalam kehidupan kita sehari-hari karena meningkatnya penggunaan internet saat ini. Baik pemasar internet maupun klien sendiri menikmati kenyamanan belanja online di mana mereka memiliki akses ke berbagai alat sosial dan berbelanja online. Sebagai social commerce yang memiliki reputasi mendunia, TikTok bukan satu-satunya pemain di sektor bisnis. Agar dapat bertahan di tengah persaingan digital yang cepat. Oleh karena itu akan dilakukan analisis dengan menggunakan S.W. O.T untuk mengidentifikasi kekuatan, kelemahan,peluang atau bahaya yang dapat terjadi di tiktok. Dari hasil tersebut, Anda dapat mencoba mengurangi kelemahan dan bahaya, serta meningkatkan kekuatan dan peluang yang dimiliki tiktok dengan mempraktikkan strategi S-O, WO, S-T, dan WT.
Current Understanding of the Roles of Gut–Brain Axis in the Cognitive Deficits Caused by Perinatal Stress Exposure

The term ‘perinatal environment’ refers to the period surrounding birth, which plays a crucial role in brain development. It has been suggested that dynamic communication between the neuro–immune system and gut microbiota is essential in maintaining adequate brain function. This interaction depends on the mother’s status during pregnancy and/or the newborn environment. Here, we show experimental and clinical evidence that indicates that the perinatal period is a critical window in which stress-induced immune activation and altered microbiota compositions produce lasting behavioral consequences, although a clear causative relationship has not yet been established. In addition, we discuss potential early treatments for preventing the deleterious effect of perinatal stress exposure. In this sense, early environmental enrichment exposure (including exercise) and melatonin use in the perinatal period could be valuable in improving the negative consequences of early adversities. The evidence presented in this review encourages the realization of studies investigating the beneficial role of melatonin administration and environmental enrichment exposure in mitigating cognitive alteration in offspring under perinatal stress exposure. On the other hand, direct evidence of microbiota restoration as the main mechanism behind the beneficial effects of this treatment has not been fully demonstrated and should be explored in future studies.
Parameters optimization of volumetric reconstruction technique for L-SPECT imaging

Light field SPECT (L-SPECT) is an improved version of SPECT and works by introducing the concept of plenoptic imaging to reduce scanning time and to increase the amount of detected information. In L-SPECT, a tungsten pinhole array is used as a collimator to differentiate the incoming direction of radiation, rather than only allowing radiation from a set direction dictated by a conventional tube collimator. The distance of the pinhole array to the sensors’ plane is so that the sensors behind each pinhole are only exposed through that pinhole alone. This paper investigates the effects of the pinholes’ diameter and pitch over the reconstruction resolution using simulation experiments. In this proposed reconstruction algorithm, a ray is back projected from the centre of each detector with non-zero pixel value via the corresponding pinhole’s centre, and towards the area of interest with 128×128×128 voxels. The projected rays’ intersections are identified by using ray tracing and the voxels at which they intersect are updated by incrementing with the sum of the pixel values from each detector involved. Experiments are conducted with pinhole arrays of 100×100, 50×50, 30×30 and pinhole diameter of 0.5mm, 1mm and 2mm. Reconstruction is conducted for various simulated objects. Results indicate that when the number of pinholes is increased, the diameter of the pinholes should be reduced to maintain spatial resolution. Moreover, a reconstruction performed by using only 12 projections shows similar quality for the same with 36 and 72 projections. The analysis of the proposed reconstruction algorithm shows that it improves spatial resolution over the filtered back projection algorithm. Reconstruction quality can be further improved by considering scattering loss and photon attenuation.
Mules and Permission Laundering in Android: Dissecting Custom Permissions in the Wild

—Android implements a permission system to regulate apps’ access to system resources and sensitive user data. One salient feature of this system is its extensibility: apps can deﬁne their own custom permissions to expose features and data to other apps. However, little is known about how widespread the usage of custom permissions is, and what is the impact that these permissions can have on users’ privacy and security. In this paper, we empirically study the usage of custom permissions at large scale, using a dataset of 2.2M pre-installed and app-store-downloaded apps. We ﬁnd the usage of custom permissions to be widespread, and seemingly growing over time. Despite this prevalence, we ﬁnd that custom permissions are virtually invisible to end users, and their purpose mostly undocumented. This lack of transparency can lead to serious security and privacy problems: we show that custom permissions can facilitate access to permission-protected system resources to apps that lack those permissions without user awareness. To detect this practice, we design and implement two static analysis tools, and highlight multiple concerning cases spotted in the wild. We conclude this study with a discussion of potential solutions to mitigate the privacy and security risks of custom permissions.
Profiling the Australasian paramedicine tertiary academic sector and workforce: A cross-sectional study

Introduction In 1994, the first Australasian paramedicine tertiary program commenced as an off-campus offering not required as an entry-to-practice qualification A quarter of a century later, university programs have proliferated with tertiary qualifications becoming mandatory to acquire Australian Health Practitioner Regulation Agency registration. Despite this progression, concerns have been voiced regarding student enrolment volume and sustainability of the paramedicine academic workforce. To date, a census of the sector and the workforce has not been conducted, limiting capacity for data-informed strategic planning. The aim of this study was to profile the Australasian paramedicine tertiary sector and describe the academic workforce working in it. Methods A cross-sectional study was conducted in May 2022 using an online survey designed specifically for this research. The participants were discipline leaders from 19 universities or polytechnics offering entry-to-practice courses in Australia and New Zealand. Participants were asked to provide data on their course structure, organisational position, student enrolment loads and academic and non-academic staffing profiles. Simple descriptive statistics were generated to describe these data. Results Of the 19 eligible programs, 18 participated (response rate 90%). All but one course was at the undergraduate level; of the undergraduate courses, all but one were 3 years in duration. The academic workforce comprised 161 full-time or fractional and 727 casual paramedicine academics. Of the full-time academics, 131/161 were registered, with 45% of those holding ‘non-practicing’ status. Twenty-nine paramedicine academics (18%) had PhDs. There was 1 Professor and 10 Associate Professors, whilst 65% overall were Lecturers or Associate Lecturers. Conclusion This analysis represents the first description of the Australasian paramedicine tertiary sector. It reveals a diverse sector with large student enrolments and diverse course structures. The seniority of the academic workforce is skewed substantially towards lower academic levels; this shortfall in senior academics creates risk for the sector and may be symptomatic of a workforce sustainability issue.
Inférence bayésienne pour la caractérisation du comportement vibratoire des structures

En raison des erreurs de mesure et de modele, la caracterisation du comportement vibratoire des structures est effectuee dans un cadre bayesien. Un modele modal non-deterministe est introduit pour prendre en compte l’erreur de modele. L’inference bayesienne des parametres du modele et de l’erreur de modele pour une structure lineaire est effectuee dans le domaine frequentiel. L’utilisation du chaos polynomial permet d’accelerer l’evaluation requise par l’inference bayesienne. La methodologie developpee est illustree numeriquement sur une poutre encastree.
Exosomes as an Emerging Plasmid Delivery Vehicle for Gene Therapy

Despite its introduction more than three decades ago, gene therapy has fallen short of its expected potential for the treatment of a broad spectrum of diseases and continues to lack widespread clinical use. The fundamental limitation in clinical translatability of this therapeutic modality has always been an effective delivery system that circumvents degradation of the therapeutic nucleic acids, ensuring they reach the intended disease target. Plasmid DNA (pDNA) for the purpose of introducing exogenous genes presents an additional challenge due to its size and potential immunogenicity. Current pDNA methods include naked pDNA accompanied by electroporation or ultrasound, liposomes, other nanoparticles, and cell-penetrating peptides, to name a few. While the topic of numerous reviews, each of these methods has its own unique set of limitations, side effects, and efficacy concerns. In this review, we highlight emerging uses of exosomes for the delivery of pDNA for gene therapy. We specifically focus on bovine milk and colostrum-derived exosomes as a nano-delivery “platform”. Milk/colostrum represents an abundant, scalable, and cost-effective natural source of exosomes that can be loaded with nucleic acids for targeted delivery to a variety of tissue types in the body. These nanoparticles can be functionalized and loaded with pDNA for the exogenous expression of genes to target a wide variety of disease phenotypes, overcoming many of the limitations of current gene therapy delivery techniques.
Practical Considerations for Next-Generation Adjuvant Development and Translation

Over the last several years, there has been increased interest from academia and the pharmaceutical/biotech industry in the development of vaccine adjuvants for new and emerging vaccine modalities. Despite this, vaccine adjuvant development still has some of the longest timelines in the pharmaceutical space, from discovery to clinical approval. The reasons for this are manyfold and range from complexities in translation from animal to human models, concerns about safety or reactogenicity, to challenges in sourcing the necessary raw materials at scale. In this review, we will describe the current state of the art for many adjuvant technologies and how they should be approached or applied in the development of new vaccine products. We postulate that there are many factors to be considered and tools to be applied earlier on in the vaccine development pipeline to improve the likelihood of clinical success. These recommendations may require a modified approach to some of the common practices in new product development but would result in more accessible and practical adjuvant-containing products.
AI image generation boosts Kansei engineering design process

Methods of Kansei engineering help the design process by surveying users’ latent Kansei, then reflecting it on product and service development and continuous elaborations of them (Nagamachi, 1991, 2012). Through our applications of Kansei engineering to product development, we have learned that there are several common difficulties. 1. Evaluation samples’ lack of variety: products in the market have limitations in design. 2. Everyone is encouraged to participate in the design process with Kansei engineering: non-designers participation greatly contributes to successful products. 3. Designers are few and too busy: designers’ efforts should be reduced and make time to think more innovatively. In this study, to ease these problems, we have applied AI image generators, a recent development of artificial intelligence, to the Kansei engineering design process.Milkcarton Kansei studies result (Ishihara et al., 1996) is the starting point of this study. First, we examine StableDiffusion (Rombach et al. 2021), an image generation artificial intelligence system. StableDiffusion (SD) seems to lack milkcarton’s shape knowledge. Then we made incremental learning of its shape with the “Hypernetworks” framework. A common method to make innovative ideas is borrowing ideas from neighboring areas. Milkcarton in red is quite a few. On the other hand, our Beer can Kansei study (Ishihara, 1998) shows that Red color has strong relation between Kansei of Premium, Gorgeous, Affected, and Showy. Then, we try to apply a red color. The AI-generated “Red flower milkcarton” is nicely designed. Our 1996 study showed that blue has the preferred color for milkcarton. Blue abstract shapes are too often used for it; then people have Kansei as “simple”, “proper” and “monotonous”. In this attempt, we seek a “modern” and “refined” touch to blue and abstract design. The AI-generated design successfully incorporated modern touch to blue-based design. Also, we have tried more novel ideas of “Colorful painting modern milkcarton”. Milkcartons have different colors and have been implicitly or explicitly intended for “Juvenile” and “Tender” Kansei. This trial also adds modern touch, and novel designs are obtained. Finally, “Jackson Pollock painting milkcarton” was examined. The result reflects his abstract painting in the 1940s, before his invention of “drop painting”. In its long-year quest for Kansei engineering, KE methodology shows its stimulating role of innovative and problem-solving design. This study challenged the use of cutting-edge AI technology to boost more innovative designs. Along with AI technology extends, further methods for boosting innovative creation interacting with humans.
Frequency of Caesarean Section Classified by Robson’s Ten Group Classification System: A Scoping Review

The prevalence of caesarean section (CS) is rising rapidly. However, it should be carried out only under valid obstetric indications due to the various complications associated with it. Therefore, to record CS incidences, Robson’s Ten Group Classification System (TGCS) was implemented. This review focuses on the prevalence of CS rates found in various studies and identifies the clinically important groups that were most involved in CS deliveries. Preferred Reporting Items for Systematic Review and Meta-Analysis Extension for Scoping Review (PRISMA-ScR) guidelines were followed in this review. "Caesarean delivery" OR "Robson's Ten Group" OR "Classification System" were keywords used to search literature. Twenty-one studies were included in this review based on eligibility criteria. We concluded that group 5 was the major contributing factor for the increase in CS rates followed by group 10, group 4, group 2, and group 1. Previous CS was the most common factor responsible for increasing CS rates. We emphasize that Robson's TGCS is an essential parameter for recording CS rates and is simple to use for CS rate comparison.
Multivariate deep learning for reconstruction of spatial missing climate data

Complete meteorological data is essential for meteorological research. However, due to sensor failure or occlusion, data loss always occurs. In order to deal with this problem, geoscience often uses Kriging and other traditional interpolation methods. Nevertheless, because the traditional method only considers the existing data, it cannot provide accurate reconstruction results when the spatial missing rate is large. Inspired by image inpainting algorithms, we propose a new deep learning method that combines other variables related to missing meteorological variables to provide more effective information for missing regions and proves the good effect of the method through a series of experiments. To illustrate that our method can maintain good performance under different missing rates, we use the reanalysis data of the European Centre for Medium-Range Weather Forecasts to create a data set with three different missing rates of 30%, 50%, and 70% through the artificial mask. Under different missing rates, the average RMSE of the method based on deep learning decreased by 77% and 31% respectively compared with Kriging and DINEOF. In addition, by combining relevant variables, the accuracy of the deep learning model can be further improved by about 16%.
Dual-Layer Path Planning With Pose SLAM for Autonomous Exploration in GPS-Denied Environments

Robot exploration in GPS-denied environments is a significant challenge due to the lack of reliable localization strategies. In this article, we propose a dual-layer planning approach with pose SLAM for autonomous robot exploration, which consists of local and global planners. The local planner uses the iteratively built local tree to generate candidate paths, and assesses the optimal path using a utility function that trades off exploration efficiency with localization accuracy. When the local planner is unable to return the admissible paths, the global planner is engaged to search an incrementally built graph for a path, which can reposition the robot to a previously identified valuable pose. For global path searching, we improve the Dijkstra algorithm and propose a cost function that considers localization uncertainty to generate a path with low localization error. In addition, we present a mixed filter on Lie group to estimate state information of paths for planners online. Finally, the proposed method is evaluated in challenging simulations and real-world environments. Comparison experiments show that our method is more efficient than the existing methods in exploring GPS-denied environments.
Biodegradable Packaging Materials for Foods Preservation: Sources, Advantages, Limitations, and Future Perspectives

Biodegradable packaging materials generally comprise a solution to the environmental problem caused by the consecutive use of conventional packaging materials (petroleum-based materials) even though these have a high cost. The monomers resulting from the slow degradation of petroleum-based materials contribute to the pollution of the environment. Biodegradable packaging materials distinguished by high biodegradability and biocompatibility can successfully replace the aforementioned packaging materials and thus solve the environmental problems caused by their use or deposition. Although several of the biodegradable packaging materials present defective properties, mainly mechanical and barrier properties, these are reduced or even eliminated by the addition of various improving additives and by blending them with other biopolymers. Various natural preservatives such as essential oils or other phytochemical extracts can also be incorporated into the biopolymer network to increase its efficacy. This treatment is particularly beneficial since it contributes to the increasing of the shelf life and storability of packaged foods such as fruits, vegetables, dairy products, meat and its products, poultry, and fish. For all the above reasons, the preferences of consumers and the critical thinking/decisions of the food product manufacturing industries in favor of the potential use of biodegradable packaging materials in foods are increasing more and more. In this context, the present review article addresses the most recently used biodegradable packaging materials for foods preservation by presenting their sources, advantages, limitations, and future perspectives.