Miracle-dz/UniFAR-FTUs huggingface dataset:
Antibiotic Resistance Pattern of Clinical Isolates - Escherichia coli, Enterobacter, Pseudomonas and Staphylococcus aureus in the Western of Bangladesh

The present study was carried out to analyze the antibiotic susceptibility of four pathogenic bacteria Escherichia coli, Enterobacter, Pseudomonas and Staphylococcus aureus respectively. Escherichia coli strains from 35 samples, Staphylococcusaureus strains from 35 samples, Enterobacter strains from 39 samples and Pseudomonas strains from 39 samples were isolated from 200 suspected infected individuals. Pure cultures of isolate were done by isolating single colony from the stored bacteria. Identification of strains were confirmed by various microscopic, colonial and biochemical tests. Finally identified four varieties of pathogenic strains Escherichia coli, Enterobacter, Pseudomonas and Staphylococcus aureus were subjected to the antibiotic sensitivity test by antibiotic disc diffusion method. Approximately 15 commonly used antibiotics were used in the tests. For this study it was observed that 94% of Escherichia coli were resistant to Cefixime, 86% to Cefuroxime Sodium, 77% to Ceftriaxone, 71% to Ceftazidime, 66% to Amoxycillin-Clavulanic acid and Ciprofloxacin, 63% to Levofloxacin, 57% to Doxycycline, 49% to Co-trimoxazole andonly 37% to Gentamicin. No Escherichia coli samples were found resistant against Meropenem having highest sensitivity (100%). Only 7 Escherichia coli samples were resistant to Amikacin having sensitivity 80% and 10 Escherichia coli samples were resistant to Nitrofurantion with the third highest sensitivity 71%. Staphylococcus aureus were observed to show maximum resistant (100%) towards Azithromycin, next to Ceftriaxone 74%, Ciprofloxacin and Oxacillin 71%, Co-trimoxazole 63%, Levofloxacin 57% and Amoxycillin-Clavulanic acid 49%. Only 5 Staphylococcus aureus samples were resistant to Gentamicin with a maximum sensitivity 86% and 7 Staphylococcus aureus samples were resistant to Amikacin having second highest sensitivity 80% and third highest sensitivity Cephalexin 63%. Enterobactor showedmaximum resistant towards Amoxycillin-Clavunic acid 100%, Cefixime 100%, Ceftadizime 100%, Ceftriaxone 95%, Amikacin 85%, Co-trimoxazole 79%, Ciprofloxacine 77%, Doxycyclin 72%, Gentamicin51%, Levofloxacin 46%, and Nitrofurantion 41%. There were found to be no Enterobacter Samples that resistant to Meropenem having highest sensitivity (100%). Only 16 Entarobacter samples were resistant to Nitrofurantion having second highest sensitivity59% and third highest sensitivity Levofloxacin 54%. Pseudomonus were observed to maximum resistant towards Amoxicillin 100%, Ceftazidime 100%, Cefixime 100%, Doxycycline 100%, Co-trimoxazole 100%, Ciprofloxacin 83%, Ceftriaxone 83%, Levofloxacin 83%, Nitrofurantion 83%, and Amikacin 67%. There were found to be no Pseudomonus Samples that resistant to Meropenem having highest sensitivity (100%). Only 13 Pseudomonus samples were resistant to Gentamicin with a maximumsensitivity 67%.
Single-Channel Multispeaker Separation with Variational Autoencoder Spectrogram Model

This paper deals with single-channel speaker-dependent speech separation. While discriminative approaches using deep neural networks (DNNs) have recently proved powerful, generative approaches, including methods based on non-negative matrix factorization (NMF), are still attractive because of their ﬂexibility in handling the mismatch be-tween training and test conditions. Although NMF-based methods work reasonably well for particular sound sources, one limitation is that they can fail to work for sources with spectrograms that do not comply with the NMF model. To address this problem, attempts have recently been made to replace the NMF model with DNNs. With a similar motivation to these attempts, we propose in this paper a variational autoencoder (VAE)-based monaural source separation (VASS) method using a conditional VAE (CVAE) for source spectrogram modeling. We further propose an extension of the VASS method, called the discriminative VASS (DVASS) method, which uses a discriminative criterion for model training so that the separated signals directly become optimal. Experimental results revealed that the VASS method performed better than an NMF-based method, and the DVASS method performed better than
Adaptive Preamble Embedding With MIMO to Support User-Defined Functionalities in WLANs

As the Wi-Fi technology transitions into its sixth generation (Wi-Fi 6), there is a growing consensus on the need to support security and coordination functions at the Physical (PHY) layer. In contrast to the costly approach of extending the PHY-layer header to support new functions (e.g., Spatial Reuse field in the Wi-Fi 6 frame), we propose to turn specific parts of the frame preamble into a reliable data field while maintaining its primary functions. Specifically, in this paper, we develop a scheme called <italic>extensible preamble modulation (eP-Mod)</italic> for 802.11n/ac/ax protocols that are built on multiple-input-multiple-output (MIMO) and orthogonal frequency-division multiplexing (OFDM). For each frame, <italic>eP-Mod</italic> can embed up to 144 user bits into the 802.11ac preamble of an <inline-formula><tex-math notation="LaTeX">$8\times 8$</tex-math><alternatives><mml:math><mml:mrow><mml:mn>8</mml:mn><mml:mo>×</mml:mo><mml:mn>8</mml:mn></mml:mrow></mml:math><inline-graphic xlink:href="zhang-ieq1-3095459.gif"/></alternatives></inline-formula> MIMO <inline-formula><tex-math notation="LaTeX">$40\;$</tex-math><alternatives><mml:math><mml:mrow><mml:mn>40</mml:mn><mml:mspace width="0.166667em"/></mml:mrow></mml:math><inline-graphic xlink:href="zhang-ieq2-3095459.gif"/></alternatives></inline-formula>MHz transmission. The proposed scheme is adaptive to channel conditions and enables several promising PHY-layer services, such as PHY-layer encryption and channel/device authentication, and PHY-layer signaling. At the same time, it allows legacy (<italic>eP-Mod</italic>-unaware) devices to continue to process the received preamble as normal by guaranteeing that the proposed preamble waveforms satisfy the structural properties of a standardized preamble. Through numerical analysis, extensive simulations, and hardware experiments, we validate the practicality and reliability of <italic>eP-Mod</italic>.
Acceptable Behavior or Workplace Bullying?—How Perpetrator Gender and Hierarchical Status Affect Third Parties’ Attributions and Moral Judgments of Negative Behaviors

Workplace bullying consists of repeated, long-term exposure to a variety of negative behaviors. However, it remains unclear when behaviors are seen as morally acceptable vs. become bullying. Moral judgments affect whether third parties deem it necessary to intervene. In this qualitative study, we first conceptualize and then explore via 27 interviews with Austrian HR professionals and employee representatives whether twelve diverse negative behaviors elicit distinct causal attributions and moral judgments. In particular, we examine how a perpetrator’s hierarchical position and gender shape the third parties’ evaluations. A qualitative content analysis reveals the behaviors vary in their perceived acceptability and associations with workplace bullying. Ambiguous behaviors require specific cues such a perpetrator’s malicious intent to be labeled workplace bullying. Overall, third parties judge behaviors by supervisors more harshly, particularly when managerial role expectations are violated. The majority of informants reject the notion that their perceptions are affected by perpetrator gender. Still, women who engage in behaviors associated with anger or a lack of empathy are often perceived as acting with intent. The findings suggest that the violation of social role expectations amplifies the attribution of dispositional causes (e.g., malicious intent). We discuss the relevance of perpetrator intent for research and practice.
Image Captioning Algorithm Based on Multi-Branch CNN and Bi-LSTM

SUMMARY The development of deep learning and neural networks has brought broad prospects to computer vision and natural language processing. The image captioning task combines cutting-edge methods in two ﬁelds. By building an end-to-end encoder-decoder model, its description performance can be greatly improved. In this paper, the multi-branch deep convolutional neural network is used as the encoder to extract image features, and the recurrent neural network is used to generate descriptive text that matches the input image. We conducted experiments on Flickr8k, Flickr30k and MSCOCO datasets. According to the analysis of the experimental results on evaluation metrics, the model proposed in this paper can e ﬀ ectively achieve image caption, and its performance is better than classic image captioning models such as neural image annotation models.
The contribution of ocean‐leaving DMS to the global atmospheric burdens of DMS, MSA, SO2, and NSS SO4=

The contribution of ocean‐derived DMS to the atmospheric burdens of a variety of sulphur compounds (DMS, MSA, SO2, and nss SO4=) is quantified from season to season. Such quantification, especially for nss SO4= (the climate‐relevant product of DMS oxidation), is essential for the quantification of the radiative forcing of climate that may be attributable to marine phytoplankton under possible future climate conditions. Three‐dimensional chemical transport modeling up to the stratosphere is used as a tool in realizing this aim. Global data sets on oceanic and terrestrial sulphur sources are used as input. We find that the contribution of ocean‐leaving DMS to the global annually averaged column burdens of the modeled compounds is considerable: 11.9 μmol m−2 (98% of total global burden) for DMS; 0.95 μmol m−2 (94% of total global burden) for MSA; 2.8 μmol m−2 (32% of total global burden) for SO2 and 2.5 μmol m−2 (18% of total global burden) for nss SO4=. The mean annual contribution of DMS to the climate‐relevant nss SO4= column burden is greatest in the relatively pristine Southern Hemisphere, where it is estimated at 43%. This contribution is only 9% in the Northern Hemisphere, where anthropogenic sulphur sources are overwhelming. The marine algal‐derived input of the other modeled sulphur compounds (DMS, MSA, and SO2) is also greatest in the Southern Hemisphere where a lower oxidative capacity of the atmosphere, a larger sea‐to‐air transfer of DMS and a larger emission surface area lead to an elevation of the atmospheric DMS burden.
Shared Authorship in Research through Art, Design, and Craft

Conducting research through creative and artistic practices is becoming an established approach used to advance knowledge in various domains of the Arts. Although this approach tends to highlight the voice of the author through the ﬁrst-person singular, practitioner-researchers working in the ﬁelds of art, design, and craft often involve other stakeholders in their practices, such as lay people, workshop participants, workshop co-organizers, other practitioners, and other informants. In some cases, these stakeholders can be said to attain the status of co-authors since their contribution not only informs the development of the practice but also inﬂuences the direction of the research. In this paper, we examine what other voices contribute to the production of knowledge through not always accounted forms of authorship. By discussing the inclusion of various stakeholders as co-authors at different stages of the investigative process, we explore the spectrum of shared authorship in research through art, design, and craft. The discussion draws on ﬁve research cases conducted by the authors of this paper. We conclude that examining shared authorship champions the emergence of more inclusive research practices, which not only propel the diversiﬁcation of distinct ways of knowing but also value their operational role in the generation of new knowledge.
Analytical Modeling of Line-Tunneling TFETs Based on Low-Bandgap Semiconductors

The combination of two techniques: low-bandgap semiconductor and line-tunneling structure is an effective way to achieve the highest on-current in TFETs. In this paper, design of low-bandgap line-tunneling TEFT and its analytical modeling of drain current equation is proposed. The previously suggested drain current equation for the low-bandgap line-tunneling TEFT has been explained in a relatively complex form based on the minimum tunnel path that is an effective factor in determining band-to-band tunneling (BTBT). It has been simplified in this paper and reformulated based on gate-to-source voltage. Important design factors such as source doping concentration, material and thickness of the gate-insulator were examined by simulation and numerical calculations based on the minimum tunnel path for two low-bandgap In0.88Ga0. 12As and relatively high-bandgap GaSb semiconductors. The comparison of the results obtained from simulations with the proposed analytical drain current model show a good agreement. Drain doping concentration, is an effective factor on the off-state current of low-bandgap TFET. This factor was examined in order to reduce the off-current.
Ensemble Skill Gains Obtained From the Multi‐Physics Versus Multi‐Model Approaches for Continental‐Scale Hydrological Simulations

Multi‐physics ensembles have emerged as a promising approach to hydrological simulations. As multi‐physics ensembles are constructed by perturbing the model physics, the ensemble members share a substantial portion of the same physics and hence are not independent of each other. It is unknown whether and to what extent this nonindependence affects the skill gain of the ensemble method, especially compared with the multi‐model ensemble approach. This study compares a multi‐physics ensemble configured from the Noah land surface model with multi‐parameterization options (Noah‐MP) with the North American Land Data Assimilation System (NLDAS) multi‐model ensemble. The two ensembles are evaluated in terms of the annual cycle and interannual anomaly at 12 River Forecast Centers over the conterminous United States. The ensemble skill gain is measured by the difference between the performance of the ensemble mean and the average of the ensemble members' performance, and the inter‐member independence is measured by error correlations. Results show that, due to the improved model physics, the Noah‐MP configurations outperform, on average, the NLDAS models, especially in the snow‐dominated areas. The Noah‐MP ensemble almost always obtains an outstanding member that performs the best among the two ensembles, reflecting its dense sampling of the feasible model physics space. However, these two performance superiorities do not lead to a superiority of the ensemble mean. The Noah‐MP ensemble has a lower ensemble skill gain, which corresponds to the lower inter‐member independence. These results highlight the importance of inter‐member independence, particularly when most hydrological ensemble methods have overlooked it.
Composite‐observer‐based sampled‐data control for uncertain upper‐triangular nonlinear time‐delay systems and its application

This article studies the sampled‐data control problem for upper‐triangular nonlinear time‐delay systems with unknown output function and external disturbances. Different from the existing literature, the composite observers are proposed to deal with the unmeasurable states and disturbances. Next, the sampled‐data controller is elaborately constructed step‐by‐step. After selecting appropriate scaling gain L and sampling period T , the global uniform ultimate boundedness of system states can be skillfully proved. Finally, simulation examples are presented to demonstrate the effectiveness of the design method.
DEVELOPING MEASURES FOR THE EFFECTIVENESS OF DISTANCE EDUCATION AS REGARDS SUSTAINABILITY: THE MIXED METHOD APPROACH

Distance education has been acknowledged as a mechanism through which sustainable development can be achieved. The objective of the study is to develop the instrument that measures the effectiveness of distance education in inculcating sustainability among distance learners as the researchers have observed the absence of comprehensive and contextually appropriate measures for the effectiveness of distance education in nurturing sustainability. A mixed method research design was employed by following the six-phase sequential exploratory instrument development process. The quantitative validation of the instrument was done via a survey on 663 learners from the selected public universities in Malaysia. The SmartPLS 3 used by the researchers, produced a new 61-item measure of the effectiveness of distance education as regards sustainability. The findings have enabled the establishment of a comprehensive and contextually appropriate measurement tool applicable to a larger population of distance learners. It also provides an evaluation tool for practitioners in determining the effectiveness of distance education programs and courses that have led to the attainment of sustainability outcome among learners. Future studies may pursue further processes to improve the rigor and construct validation of the instrument besides uncovering other areas which are necessary to be incorporated in the scope of the measures.
Association of Cognitive Dysfunction with Cardiovascular Autonomic Nerve Abnormalities in Early Parkinson Disease

Parkinson disease (PD) is a movement disorder that affects about 1%-2% of individuals older than 60 years and is characterised by cardinal motor manifestations of rigidity, bradykinesia, postural instability and tremor [1-6,7-9,10-22]. In addition to these motor symptoms, many patients suffer from a wide range of nonmotor symptoms that sometimes even precede the typical movement disorder, such as dementia, gastroparesis, sleep disturbances (i.e. rapid eye movement sleep behavior disorder), depression, constipation, and other dysautonomic symptoms [2]. Dementia is one of the most prevalent nonmotor symptoms in PD patients (PDD), with the prevalence and annual incidence are estimated at respectively 30-40% and 10% of PD patients [16]. Previous studies suggested that cognitive dysfunction occur in the later course of disease [11]. However, recent researches found that patients with PD are susceptible to cognitive dysfunction, even early in the disease [13]. This indicates that such potentially disabling nonmotor symptoms of PD should be carefully addressed in clinical management.
ESCORT-1st: A randomized, double-blind, placebo-controlled, phase 3 trial of camrelizumab plus chemotherapy versus chemotherapy in patients with untreated advanced or metastatic esophageal squamous cell carcinoma (ESCC).

4000 Background: The current standard first-line therapy for advanced or metastatic ESCC is doublet chemotherapy, and prognosis remains poor. Camrelizumab, a humanized anti-PD-1 monoclonal antibody, has shown promising antitumor activity in previously treated advanced or metastatic ESCC (Huang et al. Lancet Oncol 2019). Immunotherapy may work synergistically with chemotherapy, but lacking clinical evidences in ESCC. Here, we report the findings of the phase 3 ESCORT-1st study which evaluated the efficacy and safety of camrelizumab plus chemotherapy vs chemotherapy in patients with untreated advanced or metastatic ESCC. Methods: Eligible patients were randomized 1:1 to receive camrelizumab 200 mg or placebo, both combined with up to 6 cycles of paclitaxel (175 mg/m2) and cisplatin (75 mg/m2). All were given intravenously Q3W. Tumor response was assessed every 6 weeks according to RECIST v1.1. Co-primary endpoints were OS and independent review committee (IRC)-assessed PFS. Efficacy was assessed in all randomized patients and safety was assessed in all treated patients. Data cutoff date for the prespecified interim OS and final PFS analysis was Oct 30, 2020. Results: From Dec 3, 2018 to May 12, 2020, 596 patients were randomized. 298 patients were treated with camrelizumb-chemotherapy and 297 patients with placebo-chemotherapy. With a median follow-up of 10.8 months, camrelizumab plus chemotherapy significantly improved OS compared with placebo plus chemotherapy (median, 15.3 month [95% CI 12.8-17.3] vs 12.0 months [11.0-13.3]; HR, 0.70 [95% CI, 0.56-0.88]; one-sided P = 0.0010). Camrelizumab plus chemotherapy was also superior for PFS (per IRC) vs placebo plus chemotherapy (median, 6.9 months [95% CI, 5.8-7.4] vs 5.6 months [95% CI, 5.5-5.7]; HR, 0.56 [95% CI, 0.46-0.68]; one-sided P < 0.0001). ORR per investigator was 72.1% in camrelizumab-chemotherapy group vs 62.1% in placebo-chemotherapy group, and median DoR was 7.0 vs 4.6 months. Incidences of grade ≥3 treatment-related AEs were comparable between the two groups (63.4% vs 67.7%), with decreased neutrophil count (39.9% vs 43.4%) as the most common one. Serious treatment-related AEs occurred in 30.2% vs 23.2% of patients, and treatment-related deaths occurred in 3.0% vs 3.7% of patients, respectively. Conclusions: Addition of camrelizumab to chemotherapy provided superior OS and PFS vs placebo plus chemotherapy, with a manageable safety profile. Camrelizumab in combination with paclitaxel and cisplatin has the potential to become a new standard first-line therapy in patients with advanced or metastatic ESCC. Based on this trial, we are submitting NDA to seek the approval from China National Medical Products Administration for camrelizumab plus chemotherapy in the treatment of untreated advanced or metastatic ESCC. Clinical trial information: NCT03691090.
Responding to Covid‑19: Experiences of Ashesi University’s Student Affairs Team

The Covid‑19 pandemic has revealed the abilities or lack thereof of many higher education institutions to adequately support the academic and co‑curricular needs of students in times of crisis. In this reflective practitioner account, Schlossberg’s Transition Theory is used to analyse the transitional experiences of students amid the Covid‑19 pandemic and how the Office of Student and Community Affairs (OSCA) team at Ashesi University successfully supported students as they navigated the academic semester. One-to-one interviews with department heads of the five OSCA units were conducted alongside focus group discussions with a cross-section of 17 students. The findings suggest that (i) advising, (ii) engagement, and (iii) timely online support interventions contributed immensely to students’ success in transitioning from in‑person to remote learning.
Abnormal Ship Behavior Detection after the Closure of AIS Based on Radar Data

In marine transportation, most ships are equipped with AIS devices. The AIS data sent by these devices can help maritime authorities to manage ships in relevant sea areas. However, AIS is a self-reporting system, when a ship is engaged in illegal activities, the AIS device may be turned off. Therefore, after the AIS is closed, if the ship's behavior during a certain period of time is different from the ship's behavior before the closure of AIS, the different behavior is likely to represent that the ship is conducting illegal activities. This behavior is considered abnormal and needs to be detected in time. Based on radar trajectory data, the detection of abnormal ship behavior is studied from two aspects: speed and direction. In order to improve the intelligent level of abnormal ship behavior detection, the abnormal speed behavior detection algorithm combined with rules and clustering (ASBD-RC) and the abnormal direction behavior detection algorithm combined with partition and the earth mover's distance (ADBD-PE) are proposed. The ASBD-RC algorithm can reduce the influence of noise and sea clutter on abnormal speed behavior detection. The ADBD-PE algorithm can effectively partition and identify trajectory segments with abnormal direction. In the experiment, based on the real and simulated radar trajectories, the abnormal behaviors of ships under different scenarios are generated. The experimental results show that in most scenarios, the ASBD-RC algorithm and the ADBD-PE algorithm can effectively detect abnormal ship behavior. And compared with other algorithms, the proposed two algorithms have better and more stable detection results.