Miracle-dz/UniFAR-FTUs huggingface dataset:
Weakly Supervised Building Semantic Segmentation Based on Spot-Seeds and Refinement Process

Automatic building semantic segmentation is the most critical and relevant task in several geospatial applications. Methods based on convolutional neural networks (CNNs) are mainly used in current building segmentation. The requirement of huge pixel-level labels is a significant obstacle to achieve the semantic segmentation of building by CNNs. In this paper, we propose a novel weakly supervised framework for building segmentation, which generates high-quality pixel-level annotations and optimizes the segmentation network. A superpixel segmentation algorithm can predict a boundary map for training images. Then, Superpixels-CRF built on the superpixel regions is guided by spot seeds to propagate information from spot seeds to unlabeled regions, resulting in high-quality pixel-level annotations. Using these high-quality pixel-level annotations, we can train a more robust segmentation network and predict segmentation maps. To iteratively optimize the segmentation network, the predicted segmentation maps are refined, and the segmentation network are retrained. Comparative experiments demonstrate that the proposed segmentation framework achieves a marked improvement in the building’s segmentation quality while reducing human labeling efforts.
Beyond backpropagate through time: Efficient model‐based training through time‐splitting

Model‐based policy gradient (MBPG) has been employed to seek an approximate solution to the optimal control problem. However, there is coupling between adjacent states due to temporal dependencies, making the training time grow linearly with the time horizon. This paper reshapes the training process of MBPG with the time‐splitting technique to establish a time‐independent algorithm called Training Through Time‐Splitting (T3S). First, copy the coupled variables to obtain two independent variables. Meanwhile, an extra variable together with an equivalence constraint is introduced for problem consistency. Then, the transformed problem divides into subproblems with carefully derived loss functions. Subproblems own decoupled variables and shared policy networks, which means they can be optimized concurrently. Guided by the algorithm design, this paper further proposes an asynchronous parallel training scheme to accelerate training efficiency. Numerical simulation shows that the T3S algorithm outperforms the MBPG algorithm by 83.6% in wall‐clock time with a trajectory tracking task.
Fabrication and Evaluation of Voriconazole Loaded Transethosomal Gel for Enhanced Antifungal and Antileishmanial Activity

Voriconazole (VRC) is a broad-spectrum antifungal agent belonging to BCS class II (biopharmaceutical classification system). Despite many efforts to enhance its solubility, this primary issue still remains challenging for formulation scientists. Transethosomes (TELs) are one of the potential innovative nano-carriers for improving the solubility and permeation of poorly soluble and permeable drugs. We herein report voriconazole-loaded transethosomes (VRCT) fabricated by the cold method and followed by their incorporation into carbopol 940 as a gel. The prepared VRCT were evaluated for % yield, % entrapment efficiency (EE), surface morphology, possible chemical interaction, particle size, zeta potential, and polydispersity index (PDI). The optimized formulation had a particle size of 228.2 nm, a zeta potential of −26.5 mV, and a PDI of 0.45 with enhanced % EE. Rheology, spreadability, extrudability, in vitro release, skin permeation, molecular docking, antifungal, and antileishmanial activity were also assessed for VRCT and VRC loaded transethosomal gel (VTEG). Ex-vivo permeation using rat skin depicted a transdermal flux of 22.8 µg/cm2/h with enhanced efficiency up to 4-fold. A two-fold reduction in inhibitory as well as fungicidal concentration was observed against various fungal strains by VRCT and VTEG besides similar results against L-donovani. The development of transethosomal formulation can serve as an efficient drug delivery system through a topical route with enhanced efficacy and better patient compliance.
A Structural Potential of Rare Trinucleotide Repeat Tracts in RNA

Among types of trinucleotide repeats, there is some disproportion in the frequency of their occurrence in the human exome. This research presents new data describing the folding and thermodynamic stability of short, tandem RNA repeats of 23 types, focusing on the rare, yet poorly analyzed ones. UV-melting experiments included the presence of PEG or potassium and magnesium ions to determine their effect on the stability of RNA repeats structures. Rare repeats predominantly stayed single-stranded but had the potential for base pairing with other partially complementary repeat tracts. A coexistence of suitably complementary repeat types in a single RNA creates opportunities for interaction in the context of the secondary structure of RNA. We searched the human transcriptome for model RNAs in which different, particularly rare trinucleotide repeats coexist and selected the GABRA4 and CHIC1 RNAs to study intramolecular interactions between the repeat tracts that they contain. In vitro secondary structure probing results showed that the UAA and UUG repeat tracts, present in GABRA4 3′ UTR, form a double helix, which separates one of its structural domains. For the RNA CHIC1 ORF fragment containing four short AGG repeat tracts and the CGU tract, we proved the formation of quadruplexes that blocked reverse transcription.
A study on supereulerian digraphs and spanning trails in digraphs

A Study on Supereulerian Digraphs and Spanning Trails in Digraphs Omaema Lasfar A strong digraph D is eulerian if for any v ∈ V (D), d+D(v) = d − D(v). A digraph D is supereulerian if D contains a spanning eulerian subdigraph, or equivalently, a spanning closed directed trail. A digraph D is trailable if D has a spanning directed trail. This dissertation focuses on a study of trailable digraphs and supereulerian digraphs from the following aspects. 1. Strong Trail-Connected, Supereulerian and Trailable Digraphs. For a digraph D, D is trailable digraph if D has a spanning trail. A digraph D is strongly trailconnected if for any two vertices u and v of D, D posses both a spanning (u, v)-trail and a spanning (v, u)-trail. As the case when u = v is possible, every strongly trail-connected digraph is also supereulerian. Let D be a digraph. Let S(D) = {e ∈ A(D) : e is symmetric in D}. A digraph D is symmetric if A(D) = S(D). The symmetric core of D, denoted by J(D), has vertex set V (D) and arc set S(D). We have found a well-characterized digraph family D each of whose members does not have a spanning trail with its underlying graph spanned by a K2,n−2 such that for any strong digraph D with its matching number α′(D) and arc-strong-connectivity λ(D), if n = |V (D)| ≥ 3 and λ(D) ≥ α′(D)− 1, then each of the following holds. (i) There exists a family D of well-characterized digraphs such that for any digraph D with α′(D) ≤ 2, D has a spanning trial if and only if D is not a member in D. (ii) If α′(D) ≥ 3, then D has a spanning trail. (iii) If α′(D) ≥ 3 and n ≥ 2α′(D) + 3, then D is supereulerian. (iv) If λ(D) ≥ α′(D) ≥ 4 and n ≥ 2α′(D) + 3, then for any pair of vertices u and v of D, D contains a spanning (u, v)-trail. 2. Supereulerian Digraph Strong Products. A cycle vertex cover of a digraph D is a collection of directed cycles in D such that every vertex in D lies in at least one dicycle in this collection, and such that the union of the arc sets of these directed cycles induce a connected subdigraph of D. A subdigraph F of a digraph D is a circulation if for every vertex v in F , the indegree of v equals its outdegree, and a spanning circulation if F is a cycle factor. Define f(D) to be the smallest cardinality of a cycle vertex cover of the digraph D/F obtained from D by contracting all arcs in F , among all circulations F of D. In [International Journal of Engineering Science Invention, 8 (2019) 12-19], it is proved that if D1 and D2 are nontrivial strong digraphs such that D1 is supereulerian and D2 has a cycle vertex cover C′ with |C′| ≤ |V (D1)|, then the Cartesian product D1 and D2 is also supereulerian. We prove that for strong digraphs D1 and D2, if for some cycle factor F1 of D1, the digraph formed from D1 by contracting arcs in F1 is hamiltonian with f(D2) not bigger than |V (D1)|, then the strong product D1 and D2 is supereulerian.
A Hierarchical Training-Convolutional Neural Network for Imbalanced Fault Diagnosis in Complex Equipment

Complex equipment is important in industry and fault diagnosis is a key technology for maintenance. Convolutional neural network (CNN) is a common manner for fault diagnosis. But due to the imbalanced data, it cannot be applied to complex equipment directly. Generally, CNNs require balanced data, and imbalanced data will mislead the models and ignore actual faults. In complex equipment, since fault occurs rarely, the fault data are imbalanced. This impedes the application of CNNs greatly. To overcome this problem, a hierarchical training-CNN is proposed in this article. The proposed method uses an effective number-resampling to balance fault data, which avoids invalid samples, and introduces a magnet-loss pretraining to address the overlap of features between different faults. Based on these improvements, the proposed method achieves good diagnosis performances with an average accuracy of 96.56%, and has been developed into a real-world case successfully with an accuracy of 94.28%.
Monitoring haemodynamic changes in rodent models to better inform safety pharmacology: Novel insights from in vivo studies and waveform analysis

Animal models are essential for assessing cardiovascular responses to novel therapeutics. Cardiovascular safety liabilities represent a leading cause of drug attrition and better preclinical measurements are essential to predict drug-related toxicities. Presently, radiotelemetric approaches recording blood pressure are routinely used in preclinical in vivo haemodynamic assessments, providing valuable information on therapy-associated cardiovascular effects. Nonetheless, this technique is chiefly limited to the monitoring of blood pressure and heart rate alone. Alongside these measurements, Doppler flowmetry can provide additional information on the vasculature by simultaneously measuring changes in blood flow in multiple different regional vascular beds. However, due to the time-consuming and expensive nature of this approach, it is not widely used in the industry. Currently, analysis of waveform data obtained from telemetry and Doppler flowmetry typically examines averages or peak values of waveforms. Subtle changes in the morphology and variability of physiological waveforms have previously been shown to be early markers of toxicity and pathology. Therefore, a detailed analysis of pressure and flowmetry waveforms could enhance the understanding of toxicological mechanisms and the ability to translate these preclinical observations to clinical outcomes. In this review, we give an overview of the different approaches to monitor the effects of drugs on cardiovascular parameters (particularly regional blood flow, heart rate and blood pressure) and suggest that further development of waveform analysis could enhance our understanding of safety pharmacology, providing valuable information without increasing the number of in vivo studies needed.
Detection of vehicles using fisheye cameras

An image processing system capable of detecting vehicles within the vicinity of the ego vehicle for use in a surround view camera system (SVC) is presented in this thesis. Image processing based object detection can be challenging when working with fisheye cameras due the effect of changes in perspective of the object combined with image distortion. In the proposed system, several featurebased vehicle detection methods are used to augment an industry-standard AdaBoost classifier. These vehicle detection methods are deployed in image regions where they have been found to perform optimally, thus ensuring the increased field of view offered by the SVC system can be fully exploited for vehicle detection purposes. The Hough Circle Transform (HCT) is used to detect target vehicle wheels due to their circular appearance when the vehicle is situated laterally with respect to the ego vehicle. A novel approach entitled Wheel Arch Contour Detection (WACD) detects target vehicle wheels in regions to the front/rear of the ego vehicle where both AdaBoost and HCT based detection methods produce weaker detection rates. Ellipse Based Wheel Detection (EBWD) is also used in specific circumstances to ensure continued detection between the AdaBoost classification and the HCT based techniques as well as side views. Harris Corner/Optical Flow techniques are used as visual tracking techniques in the event of detection not occurring in a given frame. Kalman filter prediction provides additional support for visual tracking. Novel and robust testing methodologies have also been developed to ensure spatial accuracy across the entire field of view of the SVC system. Such methods quantify performance of the proposed detection methods as a function of spatial displacement of the ego vehicle. The proposed improvements are useful when developing detection algorithms involving automotive sensors. Thorough testing has been carried out using a large dataset of various driving environments and has proven the effectiveness of the proposed approaches across the entire SVC field of view. Declaration of Originality I hereby declare that the work contained in this thesis has not been submitted by me in pursuance of any other degree.
Climate Change Vulnerability Assessment of Patuakhali Municipality in Bangladesh

Climate change will create adversative impact on the growth and development of future cities due to the proliferation of the extreme events, which will increase human, social, and economic losses over time. Therefore, it is necessary to move towards sustainable urbanization processes to reduce the impact of climate change. This research is aimed at carrying out climate change vulnerability assessment (CCVA) for Patuakhali Municipality, which is one of the most vulnerable municipalities in Bangladesh located in the southcentral coastal region of Bangladesh. The vulnerability of the study area is derived by overlaying the factor maps using equal class interval weighted index (ECIWI) and principal component analysis (PCA). Both methods show similar results in case of exposure and adaptive capacity assessment, but the results of vulnerability assessment are slightly different for some of the wards due to variation in the level of sensitivity obtained from two different methods. ECIWI and PCA show that Ward 9 and Ward 1 are the most and least vulnerable wards, respectively. Although exposure to hazards is similar in the study area, the degree of sensitivity and adaptive capacity for these two areas are different, which mainly contributes to their vulnerability. CCVA will help the local government to build resilience for the urban poor to reduce climate change-induced vulnerability, which can be utilized by the policymakers to increase awareness and to mitigate risk through planned interventions. The Dhaka University Journal of Earth and Environmental Sciences, Centennial Special Volume June 2022: 187-198
AN H∞ DESIGN METHOD FOR THE PITCH ATTITUDE HOLD AUTOPILOT OF A FLYING UAV

The paper presents an H∞ loop shaping method for the design of the automatic flight control system of an unmanned air vehicle's (UAV's) longitudinal dynamics. The design objectives include robust stabilization with respect to modeling uncertainties, pitch angle tracking of an ideal model and reduced sensitivity with respect to low frequency measurement errors. The design is illustrate by a case study for a flying wing UAV. The applications based on Unmanned Air Vehicle's (UAV's) received much attention over the last decades. Among them, the flying wing configuration of the UAVs was intensively analyzed due to their advantages concerning the reduced drag and the fuel consumption. A disadvantage of this configuration with respect to the classical one is its instability which fact requires an automatic control system able to stabilize the aircraft and to provide acceptable maneuverability qualities. The design problem of such a system has been previously considered in the control literature (see e.g. (1), (2), (3)). The proposed design methods include both classical techniques based for instance on the well- known PID (Proportional Integral Derivative) control laws, optimal approaches based on the linear quadratic problem, the H∞ norm minimization and nonlinear methods including nonlinear inversion, etc ((4), (5), (6), (7), (8)). The methods mentioned above have advantages and drawbacks; the main difficulty in choosing the control design method is to ensure a trade-off between the complexity of the automatic flight control system and its performances. The actual applications require a wide spectrum of performances including not only the stabilization of the aircraft but also robustness with respect to modeling uncertainties and flying conditions changes, time response performances and reduced sensitivity to disturbances and measurement errors. The aim of this paper is to present a design methodology for the Pitch Attitude Hold (PAH) autopilot of a flying wing configuration. The design procedure is illustrated and investigated for the Hirrus UAV designed and manufactured by a private Romanian company in collaboration with academics from Faculty of Aerospace Engineering of University "Politehnica" of Bucharest. The design approach is based on a modified version of the so-called two degrees of freedom (2 DOF) H∞ loop-shaping able to accomplish simultaneously several objectives as robustness stability, model tracking and disturbances attenuation requirements. The original 2 DOF H∞ method presented in (9) have been previously used for the autopilot design of the aircraft longitudinal and lateral SCIENTIFIC RESEARCH AND EDUCATION IN THE AIR FORCE-AFASES 2016
Effects of Bacillus subtilis T6-1 on the Rhizosphere Microbial Community Structure of Continuous Cropping Poplar

Simple Summary Long-term continuous cropping of poplar has led to a decline in soil fertility, the timber yield of poplar has decreased, and diseases and pests have increased. We aimed to develop a biological agent that regulates the structure of the microbial community of the poplar rhizosphere and alleviates the effects of continuous poplar cropping. The research showed that T6-1 could improve the structure of the microbial community of the poplar rhizosphere and promote the growth of poplars. Thus, it could be used as a biological control agent against continuous cropping obstacles for poplar trees. Abstract The continuous cropping obstacles in poplar cultivation cause declines in wood yield and serious soil-borne diseases, mainly because of structural alterations in the microbial community and the aggregation of pathogenic fungi. Bacillus subtilis T6-1, isolated from poplar rhizospheric soil, has strong antagonistic effects on poplar pathogens. We aimed to investigate the effects of B. subtilis T6-1 on the structure of the microbial community in the poplar rhizosphere. Poplar seedlings were replanted in three successive generations of soil. The diameter at breast height, plant height, and the number of culturable bacteria of the poplars inoculated with T6-1 exceeded those in the non-inoculated control group. qPCR analysis revealed that the total abundance of T6-1 bacteria in the treated poplars was remarkably higher in contrast to that in the control group. Illumina MiSeq sequencing was employed to track the alterations in diversity and structure of the total microbial community in the poplar rhizosphere inoculated with B. subtilis T6-1. Fungal diversity and abundance in the T6-1 rhizosphere were remarkably lower in contrast with those in the control rhizosphere. The proportion of Bacillus sp. in the total bacterial community in the T6-1 and control groups was 3.04% and 2.38%, respectively, while those of the Rhizoctonia sp. was 2.02% and 5.82%, respectively. In conclusion, B. subtilis T6-1 has the potential to serve as a microbial agent, enhancing the structure of the rhizosphere microbial community as well as promoting tree growth in poplar cultivation.
GJB2 Is a Major Cause of Non-Syndromic Hearing Impairment in Senegal

Simple Summary The prevalence of GJB2-related (MIM: 121011) congenital non-syndromic hearing impairment (NSHI) accounts for close to 50% in populations of Asian and European ancestry. However, in sub-Saharan Africa, except for Ghana, previous data showed that the prevalence of GJB2-associated NSHI is close to zero. To investigate the contribution of GJB2 mutations in autosomal recessive NSHI in Senegal, we screened 129 affected and 143 unaffected individuals from 44 multiplex families, 9 sporadic cases, and 148 hearing controls with no personal or family history of hearing impairment, by targeted gene sequencing. We identified three pathogenic GJB2 variants in 34% (n = 15/44) of multiplex families, of which 80% (n = 12/15) were consanguineous. The most common variant, GJB2: c.94C>T: p.(Arg32Cys), accounted for 27.3% (n = 12/44) of familial cases. We also identified the previously reported “Ghanaian” founder variant, GJB2: c.427C>T: p.(Arg143Trp), in four multiplex Senegalese families. Relatively high allele frequencies of c.94C>T. and c.427C>T variants were observed among the screened hearing controls: 1% (n = 2/148 ∗ 2), and 2% (n = 4/148 ∗ 2), respectively. No GJB6-D13S18 deletion was identified in any of the hearing-impaired participants. The data suggest that GJB2: c.94C>T: p.(Arg32Cys) should be routinely tested in NSHI in Senegal. Abstract This study aimed to investigate GJB2 (MIM: 121011) and GJB6 (MIM: 604418) variants associated with familial non-syndromic hearing impairment (HI) in Senegal. We investigated a total of 129 affected and 143 unaffected individuals from 44 multiplex families by segregating autosomal recessive non-syndromic HI, 9 sporadic HI cases of putative genetic origin, and 148 control individuals without personal or family history of HI. The DNA samples were screened for GJB2 coding-region variants and GJB6-D3S1830 deletions. The mean age at the medical diagnosis of the affected individuals was 2.93 ± 2.53 years [range: 1–15 years]. Consanguinity was present in 40 out of 53 families (75.47%). Variants in GJB2 explained HI in 34.1% (n = 15/44) of multiplex families. A bi-allelic pathogenic variant, GJB2: c.94C>T: p.(Arg32Cys) accounted for 25% (n = 11/44 families) of familial cases, of which 80% (n = 12/15) were consanguineous. Interestingly, the previously reported “Ghanaian” founder variant, GJB2: c.427C>T: p.(Arg143Trp), accounted for 4.5% (n = 2/44 families) of the families investigated. Among the normal controls, the allele frequency of GJB2: c.94C>T and GJB2: c.427C>T was estimated at 1% (2/148 ∗ 2) and 2% (4/148 ∗ 2), respectively. No GJB6-D3S1830 deletion was identified in any of the HI patients. This is the first report of a genetic investigation of HI in Senegal, and suggests that GJB2: c.94C>T: p.(Arg32Cys) and GJB2: c.427C>T: p.(Arg143Trp) should be tested in clinical practice for congenital HI in Senegal.