Miracle-dz/UniFAR-FTUs huggingface dataset:
Data-Driven Detection of Stealthy False Data Injection Attack Against Power System State Estimation

Power system state estimation (PSSE) is the foundation of energy management system applications. Hence, operators impose stringent requirements on PSSE data integrity. False data injection attacks (FDIAs) can cause risks to PSSE data-driven operations and demand mitigation. In this article, we present a two-step FDIA detector design. In step one, we study a novel stealthy attack policy by simultaneously considering the attacker’s cost reduction and damage production. In step two, with the aid of a deep autoencoding Gaussian mixture model (DAGMM), we design an unsupervised detection scheme to detect the stealthy attack. The DAGMM-based detector can meet the requirement of rapidity, unsupervisedness, and data imbalance tolerance. Eventually, we simulate and validate the stealthy attack policy and the corresponding detector using the benchmark IEEE 39-bus and 118-bus systems.
Analysis and Prediction of the Interval Duration between the First and Second Accidents considering the Spatiotemporal Threshold

Studying the time interval duration between the first accident and the second accident caused by it can provide decision makers with valuable information on how to effectively deal with high-risk second accidents. This paper is aimed to explore the potential influencing factors of the interval duration between the two accidents and predict it. First, the spatiotemporal definition method is applied to identify the cascaded first accident and the second accident. Then, on the basis of using Kaiser-Meyer-Olkin (KMO) measure and Bartlett’s sphere test statistics to ensure the applicability of the data to the factor analysis method, the explanatory variables that can significantly affect the interval duration are obtained through the factor analysis method. Finally, the random forest model (RF), which combines the advantages of machine learning methods, is employed to predict the duration of the interval. Traffic accident data set collected in Los Angeles city from February 2016 to June 2020 is used to validate prediction performance in this study. Bayesian method is applied to optimize the hyperparameters in the RF, while three evaluation indicators, including the Root Mean Squared Error (RMSE), Mean Squared Error (MSE), and Mean Absolute Percentage Error (MAPE), are used to estimate the prediction effect. The test results and comparative experiments confirm that RF is able to predict the interval well and has better prediction performance. This is of great significance for the prediction of the duration of the interval between one accident and the second accident.
Advancements in the Treatment of Triple-Negative Breast Cancer: A Narrative Review of the Literature

Triple-negative breast cancers (TNBCs) are aggressive tumors that are more common in young women, African American populations, and those with hereditary mutations. These tumors are notable for their high recurrence rate and predilection for chemoresistance. The goal of this narrative review is to describe the current treatment options for patients diagnosed with TNBC and to review the studies that have put forward these recommendations. We searched PubMed and Cochrane databases for free full-text, English-language studies published within the last several years pertaining to the search items “triple negative breast cancer” and “treatment”. We included clinical trials and retrospective reviews that had clear designs and assessed their findings against a gold standard or placebo and included evidence of overall response and/or survival outcomes. Patients with early-stage (I-III) TNBC still benefit from treatment with chemotherapeutic regimens involving anthracyclines, taxanes, and antimetabolites. Platinum-based therapies have been shown to improve the overall pathologic complete response (pCR), but there is conflicting evidence with regard to their contribution to disease-free survival (DFS) and overall survival (OS), even with the addition of a poly (ADP-ribose) polymerase (PARP) inhibitor. Patients with residual disease after neoadjuvant chemotherapy and surgical intervention have shown a significant improvement in OS when treated with adjuvant capecitabine. The high mutation burden in metastatic TNBC (mTNBC) allows for targeted therapies and immune checkpoint inhibitors. mTNBCs that express programmed death ligand-1 (PD-L1) receptors may achieve improved response and survival if their regimen includes a monoclonal antibody. Antibody-drug conjugates (ADCs) can deliver high doses of chemotherapy and significantly impact survival in mTNBC regardless of the level of biomarkers expressed by the tumor cells. PARP inhibitors significantly improve survival in newly diagnosed, treatment-naive mTNBC, but have shown mixed results in patients with a history of previous therapy. PARP inhibitors may also target patients with somatic breast cancer (BRCA) and partner and localizer of BRCA-2 (PALB2) mutations, which would allow for more options in this subset of patients. While other rare targets have shown mixed results, the future of treatment may lie in anti-androgen therapy or the development of cancer vaccinations that may increase the immunogenicity of the tumor environment. The management of TNBC includes treatment with multimodal chemotherapy, immune checkpoint inhibitors, and ADCs. The optimal approach depends on a multitude of factors, which include the stage of the tumor, its unique mutational burden, comorbid conditions, and the functional status of the patient. Physicians should be familiar with the advantages and disadvantages of each therapy in order to appropriately counsel and guide their patients.
Immunoproliferative Small Intestinal Disease Diagnosed by Double-balloon Endoscopy with Biopsy Sampling

We herein report an 80-year-old man diagnosed with immunoproliferative small intestine disease (IPSID) via small bowel endoscopy with a biopsy. He developed persistent diarrhea and subsequently presented with hypoproteinemia and moderate anemia. Transanal double-balloon endoscopy showed prominent villous edema in the middle and lower ileum, while a histological examination showed high lymphocyte/plasma cell infiltration in the mucosal layer. Furthermore, an immunostaining analysis showed that Cluster of differentiation (CD)3 and CD20 were partially positive, while CD138 was diffusely positive. Immunoglobulin A positivity was also observed. He was diagnosed with IPSID and received a nutritional agent and minocycline. After three months, the patients' symptoms improved.
Sustainability Assessment of a Low-income Building: A BIM-LCSA-FAHP-based Analysis

The construction industry is one of the most significant consumers of environmental resources worldwide. Faced with the need to produce new buildings, but without further burdening the environment, attempts to improve social, economic, and environmental indicators have turned attention to building construction in recent decades. The objective of this research is to develop a novel framework to assess the most sustainable choice of materials applied to the construction of low-income buildings, according to the three pillars of the Triple Bottom Line (TBL). A BIM-LCSA-FAHP-based model was proposed with the creation of nine different scenarios, where the materials of the structure (precast concrete, cast-in-place concrete, and structural masonry), painting (PVA water-based and acrylic), and roofing (ceramic and fiber cement tiles) varied. The proposed procedure consists of the elaboration of a 3D Building Information Modeling (BIM) model, for which the parameters described above were evaluated according to the Life Cycle Sustainability Assessment (LCSA)-TBL-based criteria, divided into ten sub-criteria, that includes: (1) environmental (acidification, eutrophication, global warming, ozone depletion, smog formation, primary energy, non-renewable energy, and mass total), (2) economic (construction cost) and (3) socio-political issues (community impact). Finally, the Fuzzy Analytical Hierarchy Process (AHP) was used as a multi-criteria decision-making technique that helps in aggregating and classifying the impacts of each scenario in a sustainability index (SI). Regarding the best option for low-income construction, the results indicated that precast concrete when combined with acrylic paint and fiber cement tiles (scenario 3) proved to be the most advantageous and achieved first place in the sustainability index (SI) developed in this work. This methodology is replicable for different construction typologies and several categories of materials, making it a robust decision-aiding tool for engineers, architects, and decision makers.
Performance of WHO-Endorsed Rapid Tests for Detection of Susceptibility to First-Line Drugs in Patients with Pulmonary Tuberculosis in Bangladesh

The fast and accurate detection of susceptibility in drugs is a major challenge for a successful tuberculosis (TB) control programme. This study evaluated the performance of WHO-endorsed rapid diagnostic tools, such as BACTEC MGIT 960 SIRE (MGIT SIRE), GenoType MTBDRplus (MTBDRplus) and Xpert MTB/RIF (Xpert), for detecting susceptibility to first-line anti-TB drugs among pulmonary TB patients in Bangladesh. A total of 825 sputum samples with results from drug susceptibility testing (DST) against first-line anti-TB drugs in the MGIT SIRE, MTBDRplus and Xpert assays were evaluated and compared with the gold standard proportion susceptibility method of the Lowenstein–Jensen (LJ) medium. The overall sensitivities of MGIT SIRE were 97.6%, 90.0%, 61.3% and 44.9%, while specificities were 89.9%, 94.5%, 91.3% and 92.2% for detection of susceptibility to isoniazid (INH), rifampicin (RIF), streptomycin (STR) and ethambutol (EMB), respectively. For MTBDRplus, the sensitivities were 88.0% and 88.7%, and the specificities were 97.4% and 97.8% for the detection of susceptibility to INH and RIF, respectively. Xpert demonstrated a sensitivity and specificity of 94.8% and 99.5%, respectively, for the detection of RIF susceptibility. All tests performed significantly better in retreated TB patients compared with primary TB cases. For detection of RIF and INH susceptibility, all three assays showed almost perfect agreement with the LJ method, although MGIT SIRE exhibited low agreement for STR and EMB. Considering the high performance, shorter turnaround time and ease of use, molecular-based approaches Xpert and MTBDRplus can be widely implemented throughout the country for the rapid detection of drug-resistant TB.
IOT home automation – Smart homes and Internet of Things

With the establishment of international of things (IOT) concept and the development of 5G, ipv6, etc., some companies or organizations are starting to put IOT into reality by embedding IOT chips and functions into furniture such as LED light and door security lock. Due to the size limit of the chips inside the furniture, only those chips with very basic specs can be used. Consequently, data collected by the sensors inside the furniture have to be uploaded to the cloud for calculation or analysis. Plus, people want to monitor and take control of their house even when they are out. As a result, cloud services such as IOT hub and servers must be deployed to make it possible for people to receive and send data from or to the house. However, IOT is a quite new concept. Its industry is still immature at present. Not all of the protocols are suitable for IOT devices, which forces companies to cope with those protocols in a very complex way in order to make a product which can be widely used. In this article, we summarize and discuss about the industry of IOT furniture and its mechanism, by giving a few examples to see the current ecosystem of IOT-related industry and the technical problems companies still need to face.
Channel estimation of MIMO time-frequency-selective channels based on data-dependent superimposed training

A new channel estimating method which is based on data-dependent superimposed training(DDST)and least square(LS)is proposed.Firstly the multiple input multiple output(MIMO)time-frequency fading system was built based on basis expansion model(BEM). Then the channel matrix was estimated using the DDST method,and the bit error rate was also analysed.The periodic exponential sequence with the same magnitude was used as the training sequence and another periodic sequence based on the information sequence was added to eliminate the effect of the unknown information sequence on the training sequence.The simulating experiment indicates that the estimating method proposed obviously reduces the mean square error and the bit error rate compared with the traditional superimposed training(ST)method,and does not waste the system bandwidth.
Diagnóstico de câncer de próstata em uma análise de incidência nos estados da Bahia e Rio Grande do Norte: houve influência do COVID-19?

Introdução: O Câncer de Próstata ocorre por meio de uma multiplicação desordenada das células da glândula prostática. Este possui uma evolução silenciosa, sendo o segundo mais comum entre os homens e, é considerado uma patologia da terceira idade. Objetivo: Este estudo trata-se de uma análise transversal com objetivo de caracterizar a incidência do câncer de próstata durante a pandemia. Metodologia: Foi utilizado o painel de Oncologia do Datasus do período de 2018 a 2021, homens entre 60 e 64 anos com neoplasia maligna de próstata, dos estados da Bahia (BA) e Rio Grande do Norte (RN). Resultados: Os resultados do presente estudo contribuíram para verificar a diminuição no número de casos diagnosticados de câncer devido a diversos fatores como estresse, ansiedade e principalmente o isolamento social imposto pela pandemia. Conclusão: Mostrou-se que a pandemia dificultou o acesso aos exames de rotina e prevenção para o diagnóstico deste, que é um dos principais em letalidade masculina.
FenceKV: Enabling Efficient Range Query for Key-Value Separation

LSM-tree is widely used in key-value stores for big data storage, but it suffers from write amplification brought by frequent compaction operations. An effective solution for this problem is key-value separation, which decouples values from the LSM-tree and stores them in a separate value log. However, existing key-value separation schemes achieve poor range query performance, especially for small key-value pairs, because they focus on mitigating write amplification but neglect access characteristics of the SSD. In this article, we propose FenceKV, which aims to achieve better range query performance while maintaining reasonable update performance for update-intensive workloads. FenceKV employs a new partition method to map values to the storage space based on the key-range to achieve efficient update and range query. Moreover, it adopts a key-range garbage collection policy to mitigate the garbage collection overhead and maintain sequential access for range queries. We compare FenceKV with modern key-value stores with various workloads, and results show that FenceKV can improve the range query performance significantly, while maintaining reasonable update performance compared to the existing designs of key-value separation.
Whole Genome DNA Methylation Profiling of D2 Medium Spiny Neurons in Mouse Nucleus Accumbens Using Two Independent Library Preparation Methods

DNA methylation plays essential roles in various cellular processes. Next-generation sequencing has enabled us to study the functional implication of DNA methylation across the whole genome. However, this approach usually requires a substantial amount of genomic DNA, which limits its application to defined cell types within a discrete brain region. Here, we applied two separate protocols, Accel-NGS Methyl-Seq (AM-seq) and Enzymatic Methyl-seq (EM-seq), to profile the methylome of D2 dopamine receptor-expressing medium spiny neurons (D2-MSNs) in mouse nucleus accumbens (NAc). Using 40 ng DNA extracted from FACS-isolated D2-MSNs, we found that both methods yielded comparably high-quality methylome data. Additionally, we identified numerous unmethylated regions (UMRs) as cell type-specific regulatory regions. By comparing the NAc D2-MSN methylome with the published methylomes of mouse prefrontal cortex excitatory neurons and neural progenitor cells (NPCs), we identified numerous differentially methylated CpG and non-CpG regions. Our study not only presents a comparison of these two low-input DNA whole genome methylation profiling protocols, but also provides a resource of DNA methylome of mouse accumbal D2-MSNs, a neuron type that has critical roles in addiction and other neuropsychiatric disorders.
A combined simulated annealing and tabu search strategy to solve a network design problem with two classes of users

A methodology to solve a transportation network design problem (TCNDP) with two classes of users (passenger cars and trucks) is developed: Given an existing highway system, with a capital investment budget constraint, the methodology selects the best links to be expanded by an extra lane by considering one of three types of traffic operations: exclusive for passenger cars, exclusive for trucks, and for both passenger cars and trucks such that the network total user equilibrium (UE) travel time is minimized. The problem is formulated as an NP-hard combinatorial nonlinear integer programming problem. The classical branch and bound methodology for the integer programming problem is very inefficient in solving this computationally hard problem. A combined simulated annealing and tabu search strategy (SA-TABU), was developed which is shown to perform in a robust and efficient manner in solving five networks ranging from 36 to 332 links. A comprehensive heuristic evaluation function (HEF), a core for the heuristic search strategy, was developed which can be adjusted to the characteristics of the problem and the search strategy used. It is composed of three elements: the link volume to capacity ratio, the historical contribution of the link to the objective function, and a random variable which resembles the error term of the HEF. The principal characteristics of the SA-TABU are the following: HEF, Markov chain length, "temperature" dropping rate and the tabu list length. Sensitivity analysis was conducted in identifying the best parameter values of the main components of the SA-TABU. Sufficiently "good" solutions were found in all the problems within a rather short computational time. The solution results suggest that in most of the scenarios, the shared lane option, passenger cars and trucks, was found to be the most favored selection. Expanding approximately 10% of the links, results in a very high percentage improvement ranging from 73% to 97% for the five test networks.
The Influence of Plant Age and Microbes-Enzymatic Additives on Fermentation of Total Mixed Ration Silages of Capiaçu Grass (Pennisetum purpureum, Schum)

The conservation of elephant grass cultivar Capiaçu in the form of total mixed ration (TMR) silage can help to improve the quality of the fermentative process and optimize feed management. However, the best cutting age of grass and the necessity of using microbes-enzymatic additives to aid in the process have not been determined thus far. Therefore, the objective of this study was to evaluate cutting age and different microbes-enzymatic additives on the fermentative and nutritional quality of total mixed ration (TMR) silages based on BRS Capiaçu. A completely randomized design was used in a 3×3 factorial scheme, with three cutting ages of grass (60, 90, and 120 days of regrowth), associated with three types of additives [CON (control), HOM (homofermentative inoculant + fibrolytic enzyme), and COMBO (homofermentative inoculant + heterofermentative inoculant + fibrolytic enzyme)]. The fermentative losses, the production of organic acids, chemical composition, and the aerobic stability of the tested silages were measured. The TMR silages containing 60-day-old grass showed the lowest dry matter contents, highest effluent production, and lower aerobic stability. The COMBO inoculant application provided higher acetic acid contents and greater aerobic stability of the 90and 120-day-old grass silages. The highest lactic acid concentrations were observed in silages produced with the 60and 90-day-old grass silages. It is concluded that the TMR produced with BRS Capiaçu at 90 days of age and in association with COMBO is the best option to balance the nutritional and fermentative quality of this type of silage.
Sulfur in Seeds: An Overview

Sulfur is a growth-limiting and secondary macronutrient as well as an indispensable component for several cellular components of crop plants. Over the years various scientists have conducted several experiments on sulfur metabolism based on different aspects of plants. Sulfur metabolism in seeds has immense importance in terms of the different sulfur-containing seed storage proteins, the significance of transporters in seeds, the role of sulfur during the time of seed germination, etc. The present review article is based on an overview of sulfur metabolism in seeds, in respect to source to sink relationships, S transporters present in the seeds, S-regulated seed storage proteins and the importance of sulfur at the time of seed germination. Sulfur is an essential component and a decidable factor for seed yield and the quality of seeds in terms of oil content in oilseeds, storage of qualitative proteins in legumes and has a significant role in carbohydrate metabolism in cereals. In conclusion, a few future perspectives towards a more comprehensive knowledge on S metabolism/mechanism during seed development, storage and germination have also been stated.
Biochemical Characterization and Cold-Adaption Mechanism of a PL-17 Family Alginate Lyase Aly23 from Marine Bacterium Pseudoalteromonas sp. ASY5 and Its Application for Oligosaccharides Production

As an important enzyme involved in the marine carbon cycle, alginate lyase has received extensive attention because of its excellent degradation ability on brown algae, which is widely utilized for alginate oligosaccharide preparation or bioethanol production. In comparison with endo-type alginate lyases (PL-5, PL-7, and PL-18 families), limited studies have focused on PL-17 family alginate lyases, especially for those with special characteristics. In this study, a novel PL-17 family alginate lyase, Aly23, was identified and cloned from the marine bacterium Pseudoalteromonas carrageenovora ASY5. Aly23 exhibited maximum activity at 35 °C and retained 48.93% of its highest activity at 4 °C, representing an excellent cold-adaptation property. Comparative molecular dynamics analysis was implemented to explore the structural basis for the cold-adaptation property of Aly23. Aly23 had a high substrate preference for poly β-D-mannuronate and exhibited both endolytic and exolytic activities; its hydrolysis reaction mainly produced monosaccharides, disaccharides, and trisaccharides. Furthermore, the enzymatic hydrolyzed oligosaccharides displayed good antioxidant activities to reduce ferric and scavenge radicals, such as hydroxyl, ABTS+, and DPPH. Our work demonstrated that Aly23 is a promising cold-adapted biocatalyst for the preparation of natural antioxidants from brown algae.