Miracle-dz/UniFAR-FTUs huggingface dataset:
An Enhanced Convolutional Neural Network for Accurate Classification of Grape Leaf Diseases

: Grape leaf diseases can significantly reduce grape yield and quality, making accurate and efficient identification of these diseases crucial for improving grape production. This study proposes a novel classification method for grape leaf disease images using an improved convolutional neural network. The Xception network serves as the base model, with the original ReLU activation function replaced by Mish to improve classification accuracy. An improved channel attention mechanism is integrated into the network, enabling it to automatically learn important information from each channel, and the fully connected layer is redesigned for optimal classification performance. Experimental results demonstrate that the proposed model (MS-Xception) achieves high accuracy with fewer parameters, achieving a recognition accuracy of 98.61% for grape leaf disease images. Compared to other state-of-the-art models such as ResNet50 and Swim-Transformer, the proposed model shows superior classification performance, providing an efficient method for intelligent diagnosis of grape leaf diseases. The proposed method significantly improves the accuracy and efficiency of grape leaf disease diagnosis and has potential for practical application in the field of grape production.
Relationship between mental fatigue and burnout syndrome in remote workers during the COVID-19 pandemic: an integrative review

This study aimed to analyze the scientific evidence available in the literature addressing the relationship between mental fatigue and burnout associated with teleworking during the COVID-19 pandemic through an integrative review. This review searched the following databases: PubMed, Scopus, Taylor & Francis, Embase, ScienceDirect, and SciELO using the DeCS and MeSH health sciences descriptors. The included articles were published between March and December 2021, during the pandemic. Of a total of 224 results, 215 articles were excluded and 9 were considered for the preparation of this integrative review. Mental fatigue was related to technostress, somatic symptoms such as anxiety and insomnia (p < 0.05), and loss of motivation (p < 0.05). Burnout was positively associated with work overload, high interdependence, and lower role clarity. The presence of a stressful factor and a protective factor was evidenced in burnout: intrusive leadership and workaholism, respectively. Greater exhaustion was observed in workers belonging to generation X (41 to 55 years old). Mental fatigue is related to exhaustion in the productive, physical, and psychological dimensions of individuals. Addiction to work has moderated this phenomenon, however, it is urgent to limit and optimize work hours as well as promote disconnection and rest among workers within the framework of a healthy work policy.
Kernel regression for cause-specific hazard models with nonparametric covariate functions

We study the local kernel pseudo-partial likelihood approach for the cause-specific hazard model with nonparametric covariate functions. The derivative of the covariate function is estimated first, and the estimator of the nonparametric covariate function is then derived by integrating the derivative estimator. The consistency and pointwise asymptotic normality of the local kernel estimator for the interested failure types are obtained. Moreover, numerical studies show that the proposed kernel estimator performs well under a finite sample size. And we compare the local kernel estimator with the regression B-splines estimator. We also apply the proposed method to analyse the kidney and renal pelvis cancer data with composite endpoints.
Within Chinese Social Media, Do the Gendered Gaze Impact the Female Appearance Anxiety of Chinese Z Generation?

Based on the observation of social media, the male gaze and female gaze have become two essential factors that trigger the appearance anxiety of young Chinese women. Considering the conventional patriarchal ideologies in China, the male gaze is primarily deemed the root of female appearance anxiety. However, with social media development, the female gaze has also become the origin of female appearance anxiety. Hence, the study utilized a mixed-method and took the Tik Tok as an example to lunch the research to determine whether the gendered gaze impacts their appearance anxiety while using social media for the Chinese female Z generation. Therefore, the study sent out 206 questionnaires and collected 175 effective responses; further, it did 19 in-depth female interviews aged 18 to 24 from different backgrounds. These data analyses pointed out that the female gaze is generally and gradually more influential than the male gaze, but the male gaze still invisibly and stiffly affects females in social media. In conclusion, the paper argued that the male gaze does not disappear but becomes unseen; global media promotes female empowerment so that the gaze and evaluation in the female community are increasing. In the future, for audiences, it is crucial to think of how to escape the "shackles" of media on females within the era of digital feminism.
Spherical Box-Counting: Combining 360° Panoramas with Fractal Analysis

In this paper, a new box-counting method to achieve a highly specific topological fingerprinting of architecture in relation to the position of the observer and in the context of its surroundings is proposed. Central to this method is the use of 360-degree spherical panoramas as a basis for fractal measurement. Thus, a number of problems of the comparative analysis of the fractal dimension in the field of architecture are explicitly and implicitly addressed, first and foremost being the question of choosing image boundaries while considering adjacent vegetation, urban elements, and other visually present objects for Gestalt analysis of a specific building. Second, the problem of distance and perspective as part of the aesthetic experience based on viewer and object location were taken into account and are addressed. The implications of the use of a spherical perspective as described in this research are also highly relevant for other methods of aesthetic measures in architecture, including those implementing collaborative design processes guided by digital tools and machine learning, among others.
The Twilight of Shenzhens Great Urban Village: Renovation of Baishizhou to Sustain Local Vitality and Improve Living Conditions

This paper examines the ongoing demolition of Shenzhens largest urban village, Baizhizhou, where poor living conditions and local vitality coexist. We focus on peoples attitudes towards the demolition project and investigate how to renovate Baishizhou to enhance living conditions and sustain local vitality simultaneously. By conducting field research through surveys and interviews with current residents of Baishizhou, we find that people are concerned about their displacement and the disappearance of community culture. Also, people reckon natural lighting and overcrowdedness are the main needed-for-improvement aspects of their current living conditions. In discussion, we propose our replan of Baishizhou in zoning and architectural design to solve the issues we found. We believe that the renovation of Baishizhou should be both human-oriented and practicality centered, which would have multiple implications for the redevelopment of urban villages in modern China.
Prebiotic and Probiotic Modulation of the Microbiota–Gut–Brain Axis in Depression

Emerging evidence demonstrates that alterations to the gut microbiota can affect mood, suggesting that the microbiota–gut–brain (MGB) axis contributes to the pathogenesis of depression. Many of these pathways overlap with the way in which the gut microbiota are thought to contribute to metabolic disease progression and obesity. In rodents, prebiotics and probiotics have been shown to modulate the composition and function of the gut microbiota. Together with germ-free rodent models, probiotics have provided compelling evidence for a causal relationship between microbes, microbial metabolites, and altered neurochemical signalling and inflammatory pathways in the brain. In humans, probiotic supplementation has demonstrated modest antidepressant effects in individuals with depressive symptoms, though more studies in clinically relevant populations are needed. This review critically discusses the role of the MGB axis in depression pathophysiology, integrating preclinical and clinical evidence, as well as the putative routes of communication between the microbiota–gut interface and the brain. A critical overview of the current approaches to investigating microbiome changes in depression is provided. To effectively translate preclinical breakthroughs in MGB axis research into novel therapies, rigorous placebo-controlled trials alongside a mechanistic and biochemical understanding of prebiotic and probiotic action are required from future research.
Similarity Checking Algorithm in Item Bank Based on Vector Space Model

With a wide use of item bank system and the increment of items in item bank system,how to avoid duplicate items becomes an important research topic.This paper first gets text with vectors with TF-IDF formula through the algorithm based on vector space mode(VSM) theory.Then,it gets the similarity of items by using cosine theory,which is used for the comparison with the threshold value initialized to get similarity checking resulting.Based on the existing item bank system,the experiment with this algorithm shows that the exact rate of 94%is gained,which is a good result compared with expert checking.
IMPLEMENTATION OF E-FORECASTING ON JIMMY FISH USING THE WIEGHTED MOVING AVERAGE METHOD

Abstract: This research is a development of previous research, where the results of previous studies have only arrived at the application design stage. Jimmy Fish UMKM is a business that sells fish seeds, while the fish seeds that are sold are: catfish, tilapia, goldfish, mujaer fish, catfish, and carp. Jimmy Fish UMKM has several activities to support its business, one of which is determining how much stock of fish fry is needed for each period. Jimmy Fish SMEs have problems in determining the amount of fish seed stock, Jimmy Fish SMEs still use estimates without definite calculations to determine the number of fish seed stocks. As a result of this problem, when someone wants to buy fish seeds, the number of stocks is not fulfilled (less), the number of fish seeds is depleted, and there is even an excess stock of fish seeds (only a few sold), so that activities at Jimmy Fish SMEs become less effective. The solution to the existing problems is to build an e-forecasing application using the wieghted moving average (WMA) method. The e-forecasting application is very important because it can predict the number of fish seed stocks for the next period using calculations from previous data. The e-forecasting application also provides convenience, speed and as a support system for making decisions on how many fish seed stocks must be fulfilled for the next period.Keywords: applications; e-forecasting; WMA Abstrak: Penelitian ini merupakan pengembangan dari penelitian sebelumnya, dimana hasil dari penelitian sebelumnya baru sampai pada tahap desain aplikasi. UMKM Jimmy Fish merupakan usaha yang menjual bibit ikan adapun bibit ikan yang dijual yaitu: ikan lele, ikan nila, ikan emas, ikan mujaer, ikan patin, dan ikan gurame. UMKM Jimmy Fish mempunyai beberapa aktifitas untuk mendukung usahanya salah satunya penentuan berapa jumlah stok bibik ikan yang diperlukan untuk setiap periodenya. UMKM Jimmy fish mempunyai permasalahan dalam menentukan jumlah stok bibit ikan, UMKM Jimmy Fish masih menggunakan perkiraan tanpa perhitungan yang pasti untuk menentukan jumlah stok bibit ikan. Akibat yang ditimbulkan dari permasalah tersebut, ketika ada yang ingin membeli bibit ikan jumlah stok tidak terpenuhi (kurang), jumlah stok bibit ikan habis, dan bahkan ada jumlah stok bibit ikan yang berlebih (hanya terjual sedikit), sehingga aktifitas pada UMKM Jimmy Fish menjadi kurang efektif. Solusi dari permasalah yang ada, dengan membangun aplikasi e-forecasing menggunakan metode wieghted moving average (WMA). Aplikasi e-forecasting sangat penting karena dapat prediksikan jumlah stok bibit ikan untuk periode selanjutnya menggunakan perhitungan dari data-data sebelumnya. Aplikasi e-forecasting juga memberikan kemudahan, kecepatan dan sebagai support system pengambilan keputusan berapa jumlah stok bibit ikan yang harus terpenuhi untuk periode selanjutnya.Kata kunci: aplikasi; e-forecasting; WMA
Pyrolysis of Oils from Unconventional Resources

In this study, oils from various sources were subjected to pyrolysis conditions; that is, without oxidizer, as the samples were heated to 500 °C, and held at that temperature. The oils studied included: (1) heavy oil from Grassy Creek, Missouri; (2) oil from tar sands of Asphalt Ridge in Utah; (3) mid-continent oil shales of three formations (two of Chattanooga formation, Pennsylvanian (age) formation, and Woodford formation); and (4) a Colorado Piceance Basin shale. Differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA) with either gas chromatography (GC) or mass spectrometry (MS) were used to quantify the produced gases evolved in the tests. Purge gases of helium, argon, and humid carbon dioxide were utilized. Larger scale pyrolysis tests were conducted in a tube furnace coupled to a MS and a GC. The results consistently showed that pyrolysis occurred between 300 °C and 500 °C, with the majority of gases being mainly hydrogen and light alkanes. This behavior was essentially consistent, regardless of the oil source.
Hurricane-induced lahars at Volcán de Colima (México): seismic characterization and numerical modeling

The Volcán de Colima, one of the most active volcanoes in Mexico, has experienced several volcanic crises over the last century with the emplacement of voluminous block-and-ash flow deposits providing large volumes of loose material along the main ravines. During the rainy season, this material is easily eroded forming lahars. Over 40 events with variable magnitude (105-106 m3) have been detected each year. The largest events that cause damages to infrastructure are usually triggered during the hurricane season (from mid-August to October) when more than 250 mm of rain usually are accumulated over a few days. On 23 October 2015, Hurricane Patricia hit the Volcán de Colima. The hurricane was announced as having reached category 5 thereby representing the largest ever recorded hurricane event in Mexico. It rapidly weakened after landfall but followed a straight trajectory toward the volcano. Up to 400 mm of rain were recorded over 30 hours. The event was recorded at a monitoring station located in the middle reaches of the La Lumbre ravine on the SW flank of the volcano, which was equipped with a rain gauge, a geophone (10 Hz), and a video camera. A multi-pulse lahar started around 8 pm (GMT) and lasted for more than five hours. The seismic signal and the video images were analyzed to identify the timing of the main pulses, the sediment concentrations, and maximum flow peak discharge. Data show that the lahar was characterized by three main pulses, in the range of debris flows with maximum flow-depth of 8 m, interspersed by more dilute tails as hyperconcentrated flow, as also observed from the frequency contents of the seismic signal. A total volume of 2.5 × 106 m3 was estimated based on the strong correlation between the seismic amplitude and the flow discharge. The lahar destroyed one bridge and ~500 m of the interstate road leaving several villages cut off for a few days. Based on the flow magnitude, duration, and the associated damage, this event probably represents the largest one recorded over the last 20 years. The FLO-2D model was used to replicate the observed event to estimate the maximum inundation limits of lahars along the five principal ravines of the volcano, in an attempt to design a hazard map for catastrophic hurricane-induced events.
From Perfect Secrecy to Perfect Safety & Security: Cryptography-Based Analysis of Endogenous Security

In this paper, we propose a conjecture that endogenous security without any prior knowledge is similar to perfect secrecy without any prior knowledge. To prove the conjecture, we ﬁrst establish a cryptography model of instinct function security to transform the security problem in the network domain into an encryption problem in the cryptographic domain. Then, we inherit and apply the established ideas and means of Perfect Secrecy, and propose the concept, deﬁnition and corollaries of the perfect instinct function security (PIFS) corresponding to Perfect Secrecy. Furthermore, we take the DHR system as a concrete implementation of PIFS and propose the DHR Perfect Security Theorem corresponding to Shannon’s Perfect Secrecy Theorem. Finally, we prove that the DHR satisfying the “One-Time Reconstruction” constraint is the suﬃcient and necessary condition to achieve perfect security. This means that the existence of PIFS is also proven. The analysis shows that any reconﬁgurable system can be encrypted by its construct and that the PIFS converts the one-way transparent superiority of the attacker into a double-blind problem for both the attacker and the defender, which leads to that the attacker is impossible to obtain useful construction information from the attacks and unable to ﬁnd a better way than blind trial-and-error or brute-force attacks. Since the attackers are required to have the new powerful ability to crack the structure cryptogram, the threshold of cyber security is raised to at least the same level as cryptogram deciphering, thereafter the ubiquitous cyber threats are destined to be signiﬁcantly reduced.
Bacillus paralicheniformis RP01 Enhances the Expression of Growth-Related Genes in Cotton and Promotes Plant Growth by Altering Microbiota inside and outside the Root

Plant growth-promoting bacteria (PGPB) can promote plant growth in various ways, allowing PGPB to replace chemical fertilizers to avoid environmental pollution. PGPB is also used for bioremediation and in plant pathogen control. The isolation and evaluation of PGPB are essential not only for practical applications, but also for basic research. Currently, the known PGPB strains are limited, and their functions are not fully understood. Therefore, the growth-promoting mechanism needs to be further explored and improved. The Bacillus paralicheniformis RP01 strain with beneficial growth-promoting activity was screened from the root surface of Brassica chinensis using a phosphate-solubilizing medium. RP01 inoculation significantly increased plant root length and brassinosteroid content and upregulated the expression of growth-related genes. Simultaneously, it increased the number of beneficial bacteria that promoted plant growth and reduced the number of detrimental bacteria. The genome annotation findings also revealed that RP01 possesses a variety of growth-promoting mechanisms and a tremendous growth-promoting potential. This study isolated a highly potential PGPB and elucidated its possible direct and indirect growth-promoting mechanisms. Our study results will help enrich the PGPB library and provide a reference for plant–microbe interactions.
New enhancement algorithm for infrared image based on double plateaus histogram

The characteristics of the infrared dim-small targets images were analyzed.A new contrast enhancement algorithm was presented based on double plateaus histogram equalization.By setting a higher threshold value as the upper limit,the algorithm could constrain the background and noises.By setting a lower threshold value as the lower limit,the algorithm could magnify the dim-small targets and the details of the image.Then,the gray intervals of the histogram were equalized.The disadvantages of histogram equalization were overcame with the proposed method.Compared with the algorithm based on single plateau histogram,the new method can enhance image contrast,and preserve image detail simultaneously.
Space-Charge Simulations for the Spallation Neutron Source (SNS) Ring Using Unified Accelerator Libraries

The latest designs for high-intensity proton rings require minimal beam loss. Although the tune depression in the ring is very small compared with highintensity linacs, space-charge contributions to beam loss through halo formation may be signi cant. The goal of achieving low-level beam loss becomes especially challenging in the presence of both the space charge and magnet imperfections. This puts very high expectations on the code used for computer simulations. The Spallation Neutron Source (SNS) ring dynamics presents a complex combination of several physical e ects and dynamic processes. Some of them, such as eld errors and misalignments are supported in general-purpose accelerator codes. Other e ects, such as space charge, are actual only for high intensity hadron rings and distributed into a set of independent specialized programs. A new SNS package, based on Uni ed Accelerator Libraries (UAL) environment, addresses all these e ects together. This paper describes some basic features of the SNS simulation environment and demonstrates its application for the space-charge simulations in the SNS accumulator ring.
CFD modeling of Vertical Axis Wind Turbine Wake Interaction

Since wind turbines placed in wind farms need to minimize their footprint on the ground, the effects of the wake must be considered. Placement optimization, turbine spacing, and direction of rotation are known to affect the performance of vertical-axis wind turbines (VAWTs). However, rigorous numerical modeling methodologies that investigate the influence of these characteristics are lacking, especially in the case of large wind turbines. The goal of this study is to analyze turbine configurations that might enhance the power production of VAWT farms using 2-Dimensional CFD models based on the Star CCM+ package. The novelty of this work is to analyze wind farm configurations for very large turbines. This is important because large turbines are much more performant than small turbines and have a high value of the power coefficient. Results show that CFD simulations capture adequately the performance of wind turbines in farms with multiple VAWTs. In general, if a second rotor is spaced more than 10 turbine diameters downstream of the first rotor, the effect of the wake is less significant. Furthermore, a specific farm configuration with 5 VAWTs is investigated and shows a 20% increase in power output compared to the same number of turbines operating in isolation.
Vision-Based Defect Measurement of Drilled CFRP Composites Using Double-Light Imaging

Drilling-induced defects in carbon fiber-reinforced polymers (CFRP) composite laminate can lead to the risk of aircraft structural failure and even aviation disaster. Measuring these defects is, then, inevitable for aerospace vehicle assembly. Tear is a representative drilling-induced delamination defect. But the most widely used measurement method is still based on human vision and vernier calipers. With low measurement efficiency and large measurement error, this is no longer suitable for industrialized large-scale production. Machine vision provides a new technology to address this problem. However, the semi-specular and textured surface around the drilled holes in CFRP laminates makes machine vision-based tear measurement difficult. To address these issues, we propose a novel automatic tear measuring system to obtain the tear point with maximum radial length (TPMRL). The method consists of three parts: 1) a double-light imaging frame is designed to illuminate the object hole under two different lighting conditions and acquire images; 2) a series of image processing procedures are proposed to accurately obtain inner hole information and tear edge information; and 3) combined processing of inner hole information and tear edge information is performed to obtain the maximum radial length of the tear area (MRLTA). The experimental results show that the proposed system is able to measure the MRLTA and is superior to some existing relative approaches.