Miracle-dz/UniFAR-FTUs huggingface dataset:
An operational search and rescue model system for Shanghai coast and adjacent seas

A meso-scale numerical weather prediction model WRF(Weather Research and Forecasting Model),a finite-volume,unstructured grid coastal and ocean model FVCOM,and a Leeway search and rescue(SAR) model,based on a Monte Carlo technique to generate an ensemble that accounts for the uncertainties in forcing fields,were adopted to establish an operational search and rescue modeling system for Shanghai coast and adjacent sea areas.The trajectories of drifting objects were predicted based on high-resolution wind and surface water current fields.The uncertainties including initial time and position,direction of leeway,state of SAR objects and errors of forecasted wind field were taken into account to generate the ensemble search areas.The successfully rescued cases of maritime incidents in recent years were used to evaluate the performance of the operational model system.The good agreements between model results and observation data proved the applicability of using Leeway model to predict SAR areas in Shanghai coast and adjacent seas.Meanwhile,the results indicated that the modeling system has a wide operational application prospect with advantages of high precision,high efficiency and convenient to be used.
Ecological Suitablility Research of Herba Rabdosia serraeby TCMGIS

Objective:To analyze the suitable producing area of Rabdosia lophanthoides var graciliftorus for regionalization of its production.Methods:Raoping county of Guangzhou province was regarded as the analytical basal place,basing on the database of ecological factors and spatial analysis methods in Georgraphic Information System for Traditional Chinese Medicine(TCMGIS). Results:The result showed that the optimal district of Rabdosia lophanthoides var graciliftorus have been determined to be located in 164 counties from Guangdong,Guangxi,Fujian,Hainan provinces.The aim of investigation was to get the appropriate producing areas of in China.And this would provide a scientific reference for the introduction and cultivation of Rabdosia lophanthoides var graciliftorus.Conclusion:The suitable producing area of Rabdosia lophanthoides var graciliftorus for large scale cultivation mainly located in Guangdong,Guangxi,Fujian and Hainan provinces.
Classification of Pineapple Fiber Woven Fabrics on Raspberry Pi Based on Convolutional Neural Network

Nowadays, deep learning plays an important role in artificial intelligence applications. This research introduces methods for classifying three types of pineapple fiber woven fabrics using Convolutional Neural Networks (CNN) on Raspberry Pi. The pineapple fiber woven fabrics have three categories which are pure pineapple fiber woven fabrics, connected-pure pineapple fiber woven fabrics, and blended pineapple fiber-cotton textile fabric. Each type corresponds to distinct qualities and prices of these fabrics. The proposed method involves three key steps: modifying the VGG16 CNN, creating and training the model with our fabric dataset, and deploying the model onto Raspberry Pi for real-world implementation. In conclusion, the experimental results demonstrate a class accuracy of 83.33 percent on average.
Guidelines for the diagnosis and treatment of knee osteoarthritis with integrative medicine based on traditional Chinese medicine

Knee osteoarthritis (KOA) is a common geriatric disease in middle-aged and elderly people. Its main pathological characteristics are articular cartilage degeneration, changes in subchondral bone reactivity, osteophyte formation at joint edges, synovial disease, ligament relaxation or contracture, and joint capsular contracture. The prevalence rate of symptomatic KOA in middle-aged and elderly people in China is 8.1%, and this is increasing. The main clinical manifestations of this disease are pain and limited activity of the knee joint, which seriously affect the quality of life of patients and may cause disability, posing a huge burden on society and the economy. Although the pathogenesis of KOA is not clear, the treatment of KOA is diverse, and Chinese medicine, which mainly relies on plant-based natural products, has a relatively stable and reliable curative effect. This guideline aims to emphasize the evidence-based staging and stepped treatment of KOA and the therapeutic effect of integrative medicine based on traditional Chinese medicine on KOA. We make recommendations that include the adoption of manual therapy, acupuncture, external application of herbs, herbal plasters, exercise therapy, and other integrative medicine based on traditional Chinese medicine. Users of the above guidelines are most likely to include clinicians and health managers in healthcare settings.
Plant-wax hydrogen isotopic evidence for postglacial variations in delivery of precipitation in the monsoon domain of China

The Asian monsoon is a key component of the Earth's climate system that directly affects the livelihood of 60% of the world population. Reliable reconstruction of changes in monsoon precipitation during the Holocene is required to better understand the present climate conditions and to predict future climate processes in the Asian monsoon domain. Reconstruction of changes in Holocene monsoon precipitation has been done in various regions of this domain using a variety of paleoclimate proxies. However, different proxies have yielded different paleoclimate records of long-term monsoon rainfall variability. We apply compound-specific stable hydrogen isotope compositions of the plant wax n -alkanes isolated from the Hongyuan peat sequence in eastern Tibet to reevaluate the regional carbonate oxygen isotopic and lake-level records. The D/H ratios of the n -alkanes resolve the apparent discrepancy among the different paleoclimate proxies. Our result indicates that lake-level fluctuation is a reliable recorder of changes in the amount of summer monsoonal precipitation while long-term isotope records largely reflect large-scale changes in the source of water vapor rather than a local precipitation signal. Combining lake-level, biomarker, and carbonate isotopic records, we conclude that the early Holocene monsoon precipitation in southwest China has been greatly influenced by the Indian monsoon.
Implementing First-Person Shooter Game AI in WILD-SCAV with Rule-Enhanced Deep Reinforcement Learning

Deep Reinforcement Learning (DRL) algorithms have achieved remarkable performance in various types of games. However, in First-Person Shooter (FPS) games the progress is relatively limited due to the partial observability, sparsity of reward function, complexity in state and action spaces brought by a 3D open environment, and the lack of satisfactory training and testing benchmarks. To this end, Wilderness Scavenger (WILD-SCAV), a novel FPS game environment was developed and used for an online competition held by Inspire-AI and IEEE Conference on Games 1, in which we introduced a rule-based agent and wined all three tracks as navigation, supply gathering, and supply battle. In this work, we propose a rule-enhanced deep reinforcement learning algorithm, adopting localization and reconstruction techniques to create 3D occupancy grid maps based on visual observations, and uses them together with heat map and other game variables as the input of a reinforcement learning neural network to conduct basic navigation tasks. Further enhanced and expanded by rules, this navigation agent can handle even more complicated supply gathering and battle tasks. Pre-trained with the previously proposed winning rules in the competition through imitation learning, then trained with distributed PPO algorithm, our agent has better performance over multiple rule-based and RL-based agents, including the agent using winning policy.
Molecular characterization and epidemiology of Toxoplasma gondii isolates from free-range chickens in the southwest region of Goiás: new genotypes

Abstract The purpose of this study was to isolate Toxoplasma gondii from tissues of free-range chickens in the southwestern region of Goiás, to detect and molecularly characterize the genetic material of the parasite, and to determine the seroprevalence of the protozoan parasite in these animals. A seroprevalence of T. gondii antibodies of 76% (19/25) was found among the chickens, while genetic material from their tissues was detected in 56% (14/25). A total of 14 isolates was obtained in the bioassay, ten of which were considered acute, eight were considered isolates of high virulence lethal to mice, and four of low virulence, considered non-lethal but with the ability to chronify the infection. Seven of the ten isolates showed significant morphometric differences from the RH strain, in terms of nucleus-complex-apical distance, length and width. Genotyping of the acute isolates was performed by RFLP-PCR, using 11 genetic markers: SAG1, SAG2 (3’SAG2 and 5’SAG2), alt.SAG2, SAG3, BTUB, GRA6, c22-8, c29-2, L358, PK1, and APICO. The results were compared and classified according to the genotypes listed on the ToxoDB Platform, where different profiles were observed indicating the presence of two known genotypes (#7 and #63) and five new genotypes (NEW 3, NEW4, NEW5, NEW6, NEW 7). The results showed high seroprevalence, isolation rate, molecular detection and genotypic variations of T. gondii in free-range chickens in the southwestern region of Goiás.
Regional variation of whole rock chemistry of the Miocene felsic igneous rocks in the Kii Peninsula, southwest Japan

紀伊半島の中新世珪長質火成岩について全岩主成分，微量元素組成を報告し，その広域的特徴について検討した．その結果，外帯花崗岩質岩には重希土類元素の枯渇が見られず瀬戸内火山岩類の流紋岩は重希土類元素に極めて枯渇すること，外帯域のSタイプ，Iタイプ花崗岩の分布境界は北東・南西方向であり，高マグネシア安山岩の分布および現在の和達ベニオフ面の等深度線と沿うことを見出した．さらに外帯Sタイプ珪長質火成岩および瀬戸内火山岩類の流紋岩の希土類元素組成について，堆積岩の部分融解実験に基づくモデル計算を行い，融解が起こった深度の違いにより，前者は斜長石に富む溶融残渣を，後者はざくろ石に富む溶融残渣を持つことで，説明できることを示した．外帯Iタイプ花崗岩の希土類元素組成についても玄武岩質岩の部分融解実験に基づくモデル計算を行い，やや軽希土類元素に富む起源物質の部分融解で説明できる事を示した．
Knowledge of Complications of Diabetes Mellitus Among Patients Visiting the Diabetes Clinics: A Cross-Sectional Study in the Qassim Region

Background and objectives Diabetes mellitus (DM) is a chronic complex metabolic disease characterized mainly by hyperglycemia. It appears to be a global epidemic and an increasingly major non-communicable disease, posing a threat to both affluent and nonaffluent societies. Diabetes dramatically increases the risk of developing stroke, chronic kidney disease, and coronary artery disease. These complications include chronic kidney disease, retinopathy, coronary artery disease, stroke, and diabetic foot ulcers. Compared to people without diabetes, adults with diabetes have a two to four times greater risk of dying from heart disease and stroke. This study aimed to assess the knowledge and attitude regarding complications among patients with diabetes visiting the Diabetes Clinics at King Fahad Specialist Hospital (KFSH) in the Qassim Region, Saudi Arabia. Methodology A cross-sectional study was conducted in which patients with DM who visited the Diabetic Clinics at KFSH from February 2023 to July 2023 were recruited using a nonprobability sampling technique. A validated questionnaire from previous research was used to collect data on the sociodemographic features of the participants and their knowledge regarding diabetic complications. Data were described using mean with standard deviation for continuous variables and proportion for categorical variables. Results A total of 368 patients were recruited. The majority of the respondents (144, 39.1%) had been living with diabetes for over 10 years, followed by 23.1% (85) of those with less than one year. Exactly 239 (64.9%) reported having a family history of diabetes. About 75% (276) of participants knew about diabetic complications, and 247 (67.1%) reported that their doctor had addressed them about diabetes complications. Among the sources of diabetes complication information, diabetologists were reported by 131 (35.6%) of the respondents, followed by 81 (22.0%) through social media, 65 (17.7%) from relatives, and 39 (10.6%) from family medicine doctors. On the other hand, the findings reveal that the different age groups have different levels of knowledge of hyperglycemia and hypoglycemia as diabetic complications (P = 0.031). However, there were no significant differences in the level of knowledge regarding complications between male and female patients (P > 0.05). Conclusions The study found that while the studied population had a relatively good knowledge of diabetic complications, some still lacked knowledge. The study also supports the need for individuals with a family history of diabetes to be aware of their risk and take steps for prevention, as a large proportion of participants reported having a family history of diabetes. Healthcare providers and diabetologists were the most frequent sources of information on diabetic complications. However, some also turned to social media. Focused education and awareness actions are crucial to ensure that people with diabetes have access to reliable information from various sources.
Contracts for First-Class Classes

First-class classes enable programmers to abstract over patterns in the class hierarchy and to experiment with new forms of object-oriented programming such as mixins and traits. This increase in expressive power calls for tools to control the complexity of the software architecture. A contract system is one possible tool that has seen much use in object-oriented programming languages, but existing contract systems cannot cope with first-class classes. On the one hand, the typical contract language deals only with plain values such as numbers, while classes are higher-order values. On the other hand, contract specifications are usually contained within class definitions, while classes as values call for a separate contract language. This article presents the design and implementation of a contract system for first-class classes as well as a two-pronged evaluation. The first one states and proves a “blame correctness” theorem for a model of our language. The theorem shows that when the contract system assigns blame to a component for a contract violation, the component is indeed responsible for providing the nonconforming value. The second part, consisting of benchmarks and case studies, demonstrates the need for the rich contract language and validates that our implementation approach is performant with respect to time.
New Formulation of a Subunit Vaccine Candidate against Lawsonia intracellularis Increases Humoral and Cellular Immune Responses

Previously, we designed a subunit vaccine candidate based on three L. intracellularis antigens with promising results in pigs. In this study, antigens were produced individually to achieve an even antigen ratio in the formulation. The emulsion characterization included the drop size and the mechanical and thermal stability. Immune response was evaluated by indirect and sandwich ELISAs, qPCR, and flow cytometry. The vaccine candidate’s safety was assessed by histopathology and monitoring the clinical behavior of animals. The average production yielded for the chimeric antigen as inclusion bodies was around 75 mg/L. The formulation showed mechanical and thermal stability, with a ratio Hu/Ho > 0.85 and a drop size under 0.15 nm. Antigens formulated at a ratio of 1:1:1 induced a significant immune response in inoculated pigs that persisted until the end of the experiment (week 14). The dose of 200 μg significantly activated cellular response measured by transcriptional and translational levels of cytokines. The cell proliferation assay revealed an increment of lymphocytes T CD4+ at the same dose. Animals gained weight constantly and showed proper clinical behavior during immunization assays. This research demonstrated the immunological robustness of the new subunit vaccine candidate against Porcine Proliferative Enteropathy evenly formulated with three chimeric antigens of L. intracellularis.
Successful treatment of acute respiratory failure following hypertensive crisis in a dog with presumed pheochromocytoma or paraganglioma

Background: Acute respiratory failure has been reported as one of the manifestations of hypertensive crisis in pheochromocytoma in human medicine. In dogs, no reports have been described as acute respiratory failure following hypertensive crisis. Here, we report the clinical presentation, course, and treatment of acute respiratory failure following the hypertensive crisis in a dog with presumed pheochromocytoma or paraganglioma. Case Description: A 12-year-old neutered male toy poodle was referred for the diagnostic evaluation of a right adrenal gland mass. The dog suddenly exhibited severe dyspnea with abnormal hypertension (systolic blood pressure >200 mmHg) 15 minutes after recovery from the anesthesia for the computed tomography (CT) examination. Pulmonary CT and ultrasonography findings suggested acute onset of severe pulmonary edema. Pulmonary edema was treated with mechanical ventilation (pressure-support ventilation with continuous positive airway pressure) and negative fluid balance after the administration of furosemide. Weaning from mechanical ventilation was successful 24 hours after the onset of respiratory failure. Finally, the dog was discharged 3 days after weaning from ventilation without complications. Conclusion: This report outlines a case of acute respiratory failure following a hypertensive crisis requiring mechanical ventilatory management in a dog. The onset and progression of pulmonary edema were extremely rapid. However, improvement in pulmonary edema was also rapid. Hemodynamic stability, in addition to prompt diagnosis and aggressive therapeutic intervention, including mechanical ventilation, may have contributed to the good prognosis of pulmonary edema following hypertensive crisis in a dog, which we attribute to a catecholamine storm.
Multi-scale Feature Fusion Extraction Structure for the Leather Defect Detection Algorithm

Detection of surface defects using computer vision is a pivotal technology for achieving intelligent manufacturing. Leather products are one of the most widely traded goods in the world, and automatic identification, localization, and detection of surface defects in leather are indispensable for achieving intelligent manufacturing of leather products. This research paper proposes FG-DETR, a multi-scale feature fusion extraction structure for small target detection algorithms. Given the recent success of deep learning methods in various related fields and that certain defects and flaws in leather pictures in our dataset are relatively small. FG-DETR is based on DETR with some improvements as follows, Initially, DETR's ResNet50 network performs feature extraction on the original image and produces four scales of feature maps. Second, we apply a modified Feature Pyramid Network (FPN) to downsample and upsample the four scales of feature maps, followed by the fusion and output of a single feature map. A Gaussian kernel and output then process the fused feature maps as the final feature maps. Finally, the feature maps are merged with the position encoding information and combined into the Transformer encoder-decoder architecture, resulting in the detection outcomes through the Position-wise Feed-Forward Networks (FFN). In our leather dataset, the FG-DETR model is more effective in detecting small targets than DETR, as our leather images are large, and the original DETR is nearly ineffective for images with relatively small defects. The average detection accuracy of medium and large targets also improved, with a 7.6 percentage point improvement at AP50. The experimental findings demonstrate that the multi-scale feature fusion extraction structure significantly enhances the detection accuracy of DETR.
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: This paper describes the three-step synthesis of TBS-MAC, a masked acyl cyanide (MAC) and a versatile one-carbon oxidation state three synthon. We have developed a scalable and detailed synthesis that involves: (1) acetylation of malononitrile to form the sodium enolate, (2) protonation of the enolate to form acetylmalononitrile, and (3) epoxidation of the enol, rearrangement to an unstable alcohol, and TBS-protection to form the title compound. Both the sodium enolate and acetylmalononitrile are bench-stable precursors to the intermediate hydroxymalononitrile, which can be converted to other MAC reagents beyond TBS by varying the protecting group (Ac, MOM, EE, etc.).
BECT : A Balanced Energy Consumption Algorithm by Threshold-Tuning for Mobile Ad Hoc Networks

1. 서 론 이동 Ad Hoc 네트워크에서 배터리로 동작하는 노드들은 에너 지가 제한되어 있기 때문에, 최근 MAC, 네트워크 프로토콜, 또 는 응용 계층에 걸쳐서 에너지 또는 전력 절감을 목표로 한 연 구들이 진행되었다 [2,3,5,6,7]. 기존 Ad Hoc 라우팅 프로토콜 은 최단 경로를 통해 데이터 패킷을 송수신한다. 이 경우 일부 노드들에 패킷의 흐름이 집중되면 이 노드들은 다른 노드들에 비하여 에너지 소모가 심하게 되고, 따라서 전체 네트워크의 에 너지 불균형이 초래된다. 본 논문에서는 네트워크 계층에서 에 너지 소모의 균형을 통하여 전체 네트워크 수명(lifetime)을 증 가시키기 위한 알고리즘을 제안한다. 즉 라우팅 경로를 설정함 에 있어 에너지가 어느정도 이상 되는 노드들로 이루어진 경로 를 선택함으로써 전체 네트워크의 수명을 연장함을 목표로 한 다. 이와 관련하여 에너지가 충분한 라우팅 경로 설정과 설정된 경로를 통한 데이터 전송중 경로의 에너지가 부족해지는 경우 새로운 경로를 찾아 목적지 노드까지 경로를 유지해 주는 기능 을 간단하고 효과적인 Threshold-Tuning 기법을 이용한 알고 리즘(BECT : A Balanced Energy Consumption Algorithm by Threshold-Tuning)을 제안한다. 2장에서는 Ad Hoc 라우 팅 프로콜인 DSR(Dynamic Routing Protocol)[1]에 대해 알 아보고, 3장에서는 BECT를 소개하며, 4장에서는 시뮬레이션 결과와 분석하고, 마지막으로 5장에서는 결론 및 향후 연구 방 향을 제시한다.
A Survey on Trust Management in Flying Ad Hoc Networks: Challenges, Classifications, and Analysis

Flying Ad Hoc Networks (FANETs) have emerged as a transformative technology, offering versatile applications across surveillance, communication, disaster relief, and more. However, the dynamic and decentralized nature of FANETs, coupled with their vulnerability to various threats, necessitates robust trust management techniques to ensure reliable and secure communication among unmanned aerial vehicles (UAVs). Nevertheless, the current literature still lacks a comprehensive study on trust management techniques in FANET. In this survey paper, we review the existing literature on trust management techniques for FANETs, focusing on the challenges, requirements, and trust evaluation solutions. We first provide an overview of FANETs, their features, applications, and standards. Then, we discuss the security challenges and threats in FANETs and how trust management can help mitigate them. Next, we propose a novel classification of the existing schemes based on their design objectives, methodologies, architecture, and performance metrics: reasoning models, machine learning models, and blockchain-based schemes. This survey paper aims to provide a comprehensive and systematic overview of the state-of-the-art trust management techniques for FANETs and to inspire new ideas and insights for further research in this emerging field.
Freeform direct-write and rewritable photonic integrated circuits in phase-change thin films

Photonic integrated circuits (PICs) with rapid prototyping and reprogramming capabilities promise revolutionary impacts on a plethora of photonic technologies. We report direct-write and rewritable photonic circuits on a low-loss phase-change material (PCM) thin film. Complete end-to-end PICs are directly laser-written in one step without additional fabrication processes, and any part of the circuit can be erased and rewritten, facilitating rapid design modification. We demonstrate the versatility of this technique for diverse applications, including an optical interconnect fabric for reconfigurable networking, a photonic crossbar array for optical computing, and a tunable optical filter for optical signal processing. By combining the programmability of the direct laser writing technique with PCM, our technique unlocks opportunities for programmable photonic networking, computing, and signal processing. Moreover, the rewritable photonic circuits enable rapid prototyping and testing in a convenient and cost-efficient manner, eliminate the need for nanofabrication facilities, and thus promote the proliferation of photonics research and education to a broader community.